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Contents

1

Introduction

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1-1

Design Optimization and Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1-1
Terminology   . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1-2
Design Optimization Process   . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1-3
Sensitivity Studies  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1-3
Features of the Design Optimization and Sensitivity Module (OPTSTAR)  .1-4

Limits  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1-8

2

Elements of Optimization and Sensitivity

. . . . . . . . . . . .  2-1

Design Optimization  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2-1
Design Variables  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2-2
Objective Function   . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2-5
Behavior Constraints  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2-5
Sensitivity Study  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2-6
Sensitivity Types  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2-8

3

Procedures and Examples

 . . . . . . . . . . . . . . . . . . . . . . .  3-1

Introduction  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3-1
Overview of Process for Design Optimization and Sensitivity . . . . . . . . . . .3-2
Overview of Commands for Design Optimization and Sensitivity . . . . . . . .3-3
Procedures for Performing Design Optimization   . . . . . . . . . . . . . . . . . . . . .3-5
Procedures for Performing Sensitivity Studies  . . . . . . . . . . . . . . . . . . . . . .3-12
Special Features for Optimization and Sensitivity   . . . . . . . . . . . . . . . . . . .3-14

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Numerical Aspects

. . . . . . . . . . . . . . . . . . . . . . . . . . . . .  4-1

Introduction  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-1
Basic Statements of Optimization Problems  . . . . . . . . . . . . . . . . . . . . . . . . .4-2
Function Approximation  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-2
Singular Value Decomposition  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-4
The Modified Feasible Direction Method  . . . . . . . . . . . . . . . . . . . . . . . . . . .4-4

Overall Process   . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-4
Search Direction   . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-5
Convergence to the Optimum   . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-6
Satisfaction of Kuhn-Tucker Conditions  . . . . . . . . . . . . . . . . . . . . . . . . . .4-7

The Sequential Linear Programming Method  . . . . . . . . . . . . . . . . . . . . . . . .4-9
Move Limits of Design Variables  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-10
Constraint Trimming  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-11
Convergence Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-12
References  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4-14

5

Additional Problems

. . . . . . . . . . . . . . . . . . . . . . . . . . . .  5-1

Introduction  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5-1

Index   . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1-1

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Introduction

Design Optimization and Sensitivity

Before starting the topic of design optimization and sensitivity, it is important to 
distinguish between analysis and design. Analysis is the process of determining the 
response of a specified system to its environment. Design, on the other hand, is the 
actual process of defining the system. Analysis is therefore a subset of design.

Engineering design in general, is an iterative process as shown in Figure 1-1. The 
design is continuously modified until it meets evaluation and acceptance criteria set 
by the engineer. Mathematical and empirical formulas aided by years of 
engineering judgment and experience have been useful in the traditional design 
processes to verify the adequacy of designs. However, a fully automated design 
optimization and sensitivity is used when engineers are trying to modify a design 
which level of complexity exceeds their ability to make appropriate changes. It is 
not surprising that even what might appear as extremely simple design task may 
easily be a real challenge to the designer during the decision-making process. 

The design optimization and sensitivity capability provides many design options. 
Whether you wish to design a simple truss or a complicated three dimensional solid 
model, COSMOSM or COSMOSFFE will modify both the size and geometrical 
shape in search for an improved design.

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Figure 1-1. Iterative Process of Engineering Design

The following sections provide more information on the design optimization and 
sensitivity module (OPTSTAR). They include brief explanations of terminology, 
the optimization process, and sensitivity studies. There is also a summary of the 
important features of the OPTSTAR module.

Terminology

The terminology frequently used in design optimization and sensitivity study are: 
design variables, objective function, behavior constraints, response quantities, 
feasible design, optimum design, and sensitivity type. Chapter 2, Elements of 
Design Optimization and Sensitivity, explains these terminology in more detail.

Initial Design

Requirements

Satisfied

?

Any 

Room for

Improvments

?

Final Design

Yes

Yes

No

Change Design

No

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Design Optimization Process

The process of design optimization can be pictorially represented as shown in the 
following figure.

Figure 1-2. Design Optimization Process

Refer to Chapter 3, Procedures and Examples, for general guidelines to performing 
design optimization.

Sensitivity Studies

The process of sensitivity study is similar in principle to the design optimization 
process illustrated previously. The procedure is summarized in Figure 1-3.

POSTPROCESSING

GEOMETRY 

MESHING

APPROXIMATION 

AND OPTIMIZATION

O P TIMIZATIO N LO O P

GEOMETRY, MESHING, 

AND ANALYSIS

DEFINE

OPTIMIZATION 

PARAMETERS

ANALYSIS

Yes

Is

Convergence

Achieved

?

No

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Figure 1-3. Sensitivity Process

Chapter 3, Procedures and Examples, describes more details about performing 
sensitivity studies.

Features of the Design Optimization and 
Sensitivity Module (OPTSTAR)

The process of finite element analysis, evaluation of analysis results and design 
changes, and modifications for yet another solution phase are performed 
automatically in COSMOSM. OPTSTAR performs two-dimensional and three-
dimensional sizing and shape optimization and sensitivity for structural and thermal 
applications. The following are some of the module's capabilities:

Full interaction with GEOSTAR for model creation, results manipulation and 
display (pre- and postprocessing)

Access to COSMOSM and COSMOSFFE solvers, element and material 
libraries

POSTPROCESSING

GEOMETRY 

MESHING

No

S E NS ITIV ITY  LO O P

Yes

Is

Required 

Number of Runs 

Executed

?

GEOMETRY, MESHING, 

AND ANALYSIS

DEFINE

SENSITIVITY 

PARAMETERS

ANALYSIS

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Type of analyses:

– Linear Static (including multiple load cases)

– Linear Dynamic (natural frequencies and mode shapes)

– Linearized Buckling

– Heat Transfer

– Nonlinear

– Fatigue

– Advanced Dynamic

– Dynamic Stress

Design variables:

– Side constraints (upper and lower limits of design variables) 

– Move limits control

– Shape Applications

- Dimensions and parameters used in building the model's geometry

–Sizing Applications

- Parameters used to define the model other than the shape parameters

- For linear static analysis, predefined sizing options include:

Cross-sectional area of truss elements

Thickness of 2D continuum elements

Thickness of shell elements

Width and height of beam elements with rectangular cross-sections

Thickness and radius of pipe elements

Optimization behavior constraints:

– Trimming control 

– Different sets (with lower and upper limits) of:

- Displacements

- Relative displacements

- Stresses

- Strains

- Reaction forces

- Fatigue usage factors

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- Natural frequencies

- Linearized buckling load factors

- Velocities

- Accelerations

- Temperatures

- Temperature gradients

- Heat Fluxes

- Weight

- Volume

- User-defined quantities

Optimization objective function:

– Minimization and maximization of one type composed of different sets with 

user-specified weight factors.

- Volume

- Weight

- Displacement

- Relative displacement

- Stress

- Strain

- Reaction force

- Fatigue usage factors

- Velocity

- Acceleration

- Natural frequency

- Linearized buckling load factor

- Temperature

- Temperature gradient

- Heat flux

- User-defined quantity

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Sensitivity options:

– Global, local and offset pre-optimization sensitivity studies, in addition to 

optimization sensitivity results.

– Sensitivity response quantities include:

- Displacements

- Relative displacements

- Stresses

- Strains

- Reaction forces

- Fatigue usage factors

- Velocities

- Accelerations

- Natural frequencies

- Linearized buckling load factors

- Temperatures

- Temperature gradients

- Heat fluxes

- Volume

- Weight

- User-defined quantities

Numerical techniques:

– Modified Feasible Directions

– Singular Value Decomposition technique

– Linear, quadratic and cubic approximations

– Restart and restore options

Results:

– Output  file

– X-Y convergence and sensitivity plots

– Color filled, colored line contour plots, and vector plots of displacement, 

stress, strain, temperature, temperature gradient, and heat flux for the current 
model.

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– Animation and plots of deformed shapes for linear static analysis and mode 

shapes for frequency and buckling analyses.

–Tabular data reports

Limits

25 design variables

60 constraint sets

100 objective function sets

60 sensitivity response quantities

75 design sets for optimization

20 increments for global sensitivity

20 sets for offset sensitivity

32,000 and 64,000 nodes and elements on PCs 

3000 nodes and 3000 elements for EXPLORER

64,000 nodes and 64,000 elements on EWS (Unix workstations)

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Elements of Optimization 
and Sensitivity

Design Optimization

Design optimization refers to the automated redesign process that attempts to 
minimize or maximize a specific quantity (objective function) subject to limits or 
constraints on the response by using a rational mathematical approach to yield 
improved designs. Figure 2-1 shows minimum weight design of a structure.

Figure 2-1. Minimum Weight Design of a Structure

t

Fina l D e sign

Remov able Material

Neutral Axis

Initia l D e sign

3

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2

1

t

1

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feasible design is a design that satisfies all of the constraints. A feasible design 
may not be optimal. An optimum design is defined as a point in the design space for 
which the objective function is minimized or maximized and the design is feasible. 
If relative minima exist in the design space, other optimal designs can exist.

Basic terminology in design optimization are: Design variables, objective function, 
and behavior constraints. They are explained in the following sections.

Design Variables

Design variables are the parameters (independent quantities) that users seek to find 
their values for an optimum design. Figure 2-2 shows a structure having four 
geometry dimensions defined as design variables. 

Upper and lower bounds are specified for each design variable. Lower and upper 
bounds are also referred to as side constraints.

For example:

Figure 2-2. A Structure with Four Design Variables

10

≤ T1 ≤ 25

Lower Bound

Upper Bound

t

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t

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t

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3

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Depending on design variables, there are two types of optimization applications: 
sizing optimization and shape optimization.

Sizing optimization refers to the class of problems where a change in design 
variables does not change the problem's geometry or mesh as shown in Figure 2-3.

Figure 2-3. Initial and Final Geometry and Mesh for a Sizing Optimization Problem

For linear static analysis, predefined sizing options are summarized in Table 2-1.

Table  2-1. Predefined Sizing Options

Shape optimization refers to the class of problems where any change in design 
variables causes change in the problem's geometry or mesh as shown in Figure 2-4.

COSMOSM Element Type and Name 

Design Variable

Truss TRUSS2D, 

TRUSS3D

Cross-Sectional 
Area

Beam 

(rectangular 

cross-sections)

BEAM2D, BEAM3D

Width, Height

2D Continuum 

TRIANG, PLANE2D

Thickness

Shell 

SHELLAX, SHELL3, SHELL3T, SHELL4, 
SHELL4T, SHELL6, SHELL9

Thickness 

Pipe PIPE

Thickness, 

Radius 

Final Ge ome try  and Me sh

Initial Ge ome try and Me sh

=

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Figure 2-4. Initial and Final Geometry and Mesh for a Shape Optimization Problem

Besides purely sizing optimization and shape optimization mentioned above, there 
is a class of problems where both sizing and shape parameters are defined as design 
variables as shown in Figure 2-5.

Figure 2-5. Initial and Final Geometry for Sizing/Shape Optimization Problems

Final Geometry

Initial Geometry and Mesh

Initial Geometry

    

Sizing Parameter: Thickness

Sizing Parameter: Cross-Section Area

Final Geometry

Initial Geometry

Final Geometry

Truss Elements

Shell Elements

or Continuum Elements

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Objective Function

Objective function is a single quantity that the optimizer seeks to minimize or 
maximize. The objective function must be a continuous function of the design 
variables. The weight (or volume) of a structure is an example of the commonly 
used objective functions. Other quantities are:

Stress,

Strain,

Displacement,

Reaction Force,

Velocity,

Acceleration,

Natural Frequency,

Linearized Buckling 
Load Factor,

Temperature,

Temperature Gradient,

Heat Flux,

Fatigue Usage Factor, 
and

User-Defined Functions.

The objective function can be composed of different sets of the same type, and can 
reflect different weight (importance) factors for different portions of the model as 
shown in Figure 2-6.

Behavior Constraints

A behavior constraint is defined as an inequality that must be satisfied in order to 
have a feasible design. The behavior constraints are typically response quantities 
that are functions of the design variables. Von Mises stress is a typical example in 
structural problems: 

von Mises stress 

≤ allowed stress

Rg

3

Rg

2

Rg

1

Figure 2-6. A Structure Composed of Three Regions

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Other quantities are: 

Volume,

Weight,

Stress,

Strain,

Displacement,

Reaction Force,

Velocity,

Acceleration,

Natural Frequency,

Linearized Buckling Load Factor,

Temperature,

Temperature Gradient,

Heat Flux,

Fatigue Usage Factor, and

User-Defined Functions.

Multiple constraint sets of different types can also be specified.

In COSMOSM, users have to specify lower and upper limits for behavior 
constraints.

For example:

≤ von Mises stress ≤ allowed stress

Sensitivity Study

A sensitivity study is the procedure that determines the changes in a response 
quantity
 for a change in a design variable. Figure 2-8 shows a sensitivity study of a 
control arm bracket and Figure 2-9 shows its result.

Figure 2-7.  An Optimization Problem with Stress 

and Displacement Constraint

Deflection

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Figure 2-8. Sensitivity Study of a Control Arm Bracket in Frequency Analysis

Figure 2-9. Fundamental Frequency versus Design Variable-1, t

1

Basic terminology in sensitivity study are: Design variables and response 
quantities. The definition of design variables is the same as that in design 
optimization. Response quantities are functions of the design variables. All the 
postprocessing quantities which are suitable for the objective function and behavior 
constraints
 are also suitable for the sensitivity response quantities.

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Sensitivity Types

There are four types of sensitivity study, namely, global sensitivity, offset 
sensitivity, local sensitivity, and optimization sensitivity results. They are explained 
in the following paragraphs.

Global sensitivity - where design variables are changed between their lower and 
upper bounds in a user-specified number of steps. The number of steps is the same 
for all the design variables. Under this type of sensitivity, the user can change all the 
design variables simultaneously or one at a time.

Have the frequency analysis of a control arm bracket as an example where:

0.5 

≤ design variable-1 ≤ 2.5 and

1.5 

≤ design variable-2 ≤ 3.5 

The plots of response quantity versus design variable are shown in Figure 2-10 
through Figure 2-12.

Figure 2-10. Global Sensitivity - One at a Time: Fundamental Frequency 

versus Design Variable-1, t

1

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Figure 2-11. Global Sensitivity - One at a Time: Fundamental Frequency 

versus Design Variable-2, t

2

Figure 2-12. Global Sensitivity - Simultaneously: Fundamental Frequency 

versus Normalized Design Variable-1and -2

Offset sensitivity - where users specify the values of a series of design variables in 
a user-defined sets. The design variables are defined either by the actual values or 
by a perturbation ratio with respect to the initial value.

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Have the frequency analysis of a control arm bracket as an example where the 
series of design variables are:

The plot of response quantity versus sensitivity set is shown in Figure 2-13.

Figure 2-13. Offset Sensitivity: Fundamental Frequency versus 

Sensitivity Set Number

Local sensitivity - where a design variable is perturbed at a time by a user-
specified value while the rest of the design variables are kept unchanged. The 
perturbed design variables are defined either by the actual values or by a 
perturbation ratio with respect to the initial value. The gradients of the response 
quantities with respect to the design variables are computed based on the finite 
difference method.

Have the frequency analysis of a control arm bracket as an example where:

Sensitivity Set 

Number

Design 

Variable-1

Design 

Variable-2

1

0.5

3.5

2

1.0

3.0

3

1.5

2.5

4

2.0

2.0

5

2.5

1.5

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The plot of gradient of the response quantity versus design variable set is shown in 
Figure 2-14.

Figure 2-14. Local Sensitivity: Gradient of Fundamental Frequency 

versus Design Variable Number

Optimization sensitivity results - where gradients of behavior constraints and 
objective function are computed during the optimization process. The gradients are 
obtained by taking the derivatives of the approximation functions with respect to 
the design variables. This type of sensitivity study is available only when the design 
optimization is to be performed.

Initial Value:

design variable-1=2.5,
design variable-2=3.5

Perturbation Ratio:

design variable-1=+0.1,
design variable-2=+0.1

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3

Procedures and Examples

Introduction

This chapter presents detailed examples that fully describes the procedures for 
performing design optimization and sensitivity in COSMOSM. The descriptions 
include: selection and definition of appropriate parameters required for geometry 
creation, generation of the finite element mesh parametrically or otherwise, 
applying loads and boundary conditions, optimization constraint definitions, 
defining the objective function, defining sensitivity response quantities, specifying 
the optimization and sensitivity options, performing the optimization and 
sensitivity loops, and postprocessing of optimization, sensitivity and analysis 
results.

Table  3-1. Examples

Shape Optimization of a Slotted Control Arm in Static Analysis 

(See page 3-17.)

Sensitivity Study of a Control Arm Bracket in Frequency 

(See page 3-37.)

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Overview of Process for Design Optimization 
and Sensitivity

The general process for design optimization and sensitivity displayed in Chapter 1 
is shown in the following figures in more detail.

Figure

3-1. Overview of Process for Design Optimization

Requirements

Achieved?

Yes

Perform Analysis

Approximate 

Objective Function 

and Constraints

Extract Critical 

Constraints

Update Geometry 

and Mesh (If Needed)

De fine  

O ptimiz ation 

P arame te rs

O ptimiz ation Loop

Improved Design

Design 
Parameters 
(Variables)

Design 
Objective 
(Objective 
Function)

Design 
Constraints
(Behavior 
Constraints)

P re proce ssing

Build Geometry and 

Mesh in Terms of 

Design Parameters

P e rform Analysis

P ostproce ssing

Deformed Shapes

Contour and 
Vector Plots

X-Y Plots

Mode Shapes

Animation

Final Design

Static
Frequency
Buckling
Thermal
Nonlinear
Post Dynamic
Dynamic Stress
Fatigue








 No

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Figure

3-2. Overview of Process for Sensitivity Study

Overview of Commands for Design Optimization 
and Sensitivity

The following figure provides an overview of commands required for defining 
design variables, objective function, constraints, response quantities, and 
optimization/sensitivity options in COSMOSM.

For more information on the commands, please refer to the COSMOSM Command 
Reference manual (Volume 2).

Is required 

number of runs 

executed?

Yes

Perform Analysis

Update Geometry and 

Mesh (If Needed)

De fine

S e nsitivity

 P arame te rs

S e nsitivity Loop

Design 
Parameters 
(Variables)

Response 
Quantities

Sensitivity 
Types

P re proce ssing

Build Geometry and 

Mesh in Terms of 

Design Parameters

P e rform Analysis

P ostproce ssing

Deformed Shapes

Contour and 
Vector Plots

X-Y Plots

Mode Shapes

Animation

Static
Frequency
Buckling
Thermal
Nonlinear
Post Dynamic
Dynamic Stress
Fatigue








 No

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Figure

3-3. Overview of Commands for Design Optimization and Sensitivity

DE S IGN O P TIMIZATIO N 

AND S E NS ITIV ITY

•  Design Variables

•  Optimization Objective

•  Optimization Constraints

•  Sensitivity Response  

•  Optimization Loops

•  Sensitivity Runs 

ANALY S I S  > O P TI MI ZE / S E NS I TI V I TY  ME NU TRE E

CONVERGENCE AND 

SENSITIVITY PLOTS

DI S P LAY   >  X Y _

  P LO TS

ME NU TRE E

INITXYPLOT

ACTXYPOST

SETXYPLOT

XYRANGE

XYREFLINE

XYIDENTIFY

XYLIST

XYPTLIST

XYPLOT

DVARDEF

DVARLIST

DVARVDEL

OP_DVMOVE

SN_SETDEF

SN_SETLIST

SN_SETDEL

OP_CONDEF

OP_CONLIST

OP_CONDEL

OP_CONTRIM

OP_OBJDEF

OP_OBJSET

OP_OBJLIST

OP_OBJDEL

SN_RESPDEF

SN_RESPLIST

SN_RESPDEL

A_SENSITIV

R_SENSITIV

OP_CONTROL

OP_RESTORE

A_OPTIMIZE

R_OPTIMIZE

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Procedures for Performing Design Optimization

The following steps are recommended to be followed for performing design 
optimization studies using OPTSTAR. These guidelines are not in any sense 
complete, and are intended to be complementary to your own optimization 
knowledge and expertise. 

Step 1. Build the model parametrically

For shape optimization problems, build the model geometry parametrically in 
places where it is necessary. For sizing optimization, the section constants (e.g., 
cross-sectional area of a truss) and design aspects to be optimized will be 
defined as parameters. These parameters should then be defined as design 
variables using the 

DVARDEF 

(Analysis > OPTIMIZE/SENSITIVITY > 

DESIGN VARIABLES > 

Define

) command. You may choose to use all or some 

of the defined parameters in the optimization process. Note that the 

DVARDEF

 

(Analysis > OPTIMIZE/SENSITIVITY > DESIGN VARIABLES > 

Define

command needs to be applied to each design variable separately.

For design optimization and sensitivity, you need to use the COSMOSM 
command language to parametrically model the design geometry and/or 
physical properties. The command language essentially facilitates you to 
describe the design variables in GEOSTAR for a fully automated design 
optimization and sensitivity processes. Some of the capabilities of this 
parametric language are:

- the use of single parameters, arrays and functions,

- construction of arithmetic expressions,

- generating macros,

- control structure commands, and 

- logical expressions.

In most cases only the 

PARASSIGN

 (Control > PARAMETER > 

Assign 

Parameter

) command needs to be used. Refer to COSMOSM User Guide, Vol-

ume 1, Appendix E for more details.

You must exercise caution when using parameters to describe the model 
geometry. The chosen parameters have to define the model completely so that 
when their values are modified during the optimization loops, the geometry 
creation and meshing will not fail.

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Step 2. Execute required initial analyses

Execute the initial analysis as usual in COSMOSM. The types of analyses 
currently supported for design optimization are: 

- linear static stress analysis (including multiple load cases),

- linearized buckling analysis,

- analysis of natural frequencies and mode shapes,

- heat transfer analysis, 

- nonlinear structural analysis,

- post dynamic analysis,

- dynamic stress analysis, and

- fatigue analysis.

For multidisciplinary design optimization, you can execute the analyses in any 
order before proceeding with optimization loops except the following cases.

It should be noted that natural frequency analysis and buckling analysis cannot 
be combined in a multidisciplinary optimization application since they share the 
same database locations in the program unless user-defined postprocessing 
functions are used for constraints and/or objective functions.

If you are performing design optimization on a heat transfer - linear static 
problem in which the temperatures are computed using either HSTAR or FFE 
Thermal, then you need to follow the procedure listed below in order to input 
the heat transfer results as thermal loads in static analysis:

- Use 

R_THERMAL

 (Analysis > HEAT TRANSFER > 

Run Thermal Analysis

command to execute heat transfer analysis.

- Use 

TEMPREAD

 (LoadsBC > LOAD OPTIONS > 

Read Temp as Load

command to read temperatures from heat transfer analysis.

- Use 

A_STATIC

 (Analysis > STATIC > 

Static Analysis Options

) command with 

flag T to include thermal loading in static analysis.

- Use 

R_STATIC

 (Analysis > STATIC > 

Run Static Analysis

) command to 

execute linear static analysis.

Post dynamic and fatigue analyses cannot be executed alone instead they must 
follow other types of analysis. You need to follow the procedures listed below to 
get correct results.

- Post dynamic analysis:

1. Use 

R_FREQUENCY

 (Analysis > FREQUENCY/BUCKLING > 

Run 

Frequency

) command to execute analysis of natural frequencies and mode 

shapes,

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2. Use 

R_DYNAMIC

 (Analysis > POST-DYNAMIC > 

Run Post Dynamic

command to execute post dynamic analysis,

3. Use 

R_STRESS

 (Analysis > STATIC > 

Run Stress Analysis

) command to 

execute dynamic stress analysis if desired.

- Fatigue analysis:

1. Use 

R_STATIC

 (Analysis > STATIC > 

Run Static Analysis

) or 

R_NONLINEAR

 (Analysis > NONLINEAR > 

Run NonL Analysis

command to execute linear or nonlinear structural analysis respectively or 

R_FREQUENCY 

(Analysis > FREQUENCY/BUCKLING > 

Run 

Frequency

),

 

R_DYNAMIC 

(Analysis > POST-DYNAMIC > 

Run Post 

Dynamic

),

 

and 

R_STRESS

 

(Analysis > STATIC > 

Run Stress Analysis

)

 

commands to execute frequency, post dynamic and dynamic stress analysis,

2. Use 

R_FATIGUE

 (Analysis > FATIGUE > 

Run Fatigue Analysis

command to execute fatigue analysis.

Step 3. Perform postprocessing of initial analysis results

Perform postprocessing of the initial executed analyses as usual. For multi-
disciplinary analysis, you need to first activate the required type of analysis. Users 
will have access to all existing GEOSTAR'S postprocessing features. Please refer to 
User Guide (Vol. 1) and Basic FEA System Manual (Vol. 3) for more information.

Step 4. Begin design optimization procedures by defining design 
variables

First, define the design variables using the command 

DVARDEF 

(Analysis > 

OPTIMIZE/SENSITIVITY > DESIGN VARIABLES > 

Define

). Note that each 

design variable, whether in shape or sizing optimization, must have already been 
defined as a parameter [using the 

PARASSIGN

 (Control > PARAMETER > 

Assign Parameter

) command]. The command controls the following 

information:

- Type of variable (shape or sizing) and its parametric name,

- Lower and upper bounds,

- Convergence tolerance (see Chapter 4),

Default values = 1/100 | upper bound- to lower bound |

- Method of choosing the pre-optimization design variable values (perturbation 

or random evaluation),

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- Sizing options and element type (only for linear static analysis) where a 

distinction has to be made between 2D and 3D beam elements and either 
membrane or bending dominant behavior has to be indicated for shell 
elements.

Use the commands 

DVARDEL

 (Analysis > OPTIMIZE/SENSITIVITY > 

DESIGN VARIABLES > 

Delete

) and 

DVARLIST

 (Analysis > OPTIMIZE/

SENSITIVITY > DESIGN VARIABLES > 

List

) ‘to delete and list the design 

variables respectively.

Use the commands 

OP_DVMOVE 

(Analysis > OPTIMIZE/SENSITIVITY > 

DESIGN VARIABLES > 

Move Limits

) to control the move limits of design 

variables during the optimization loops. This command is seldom necessary 
since its default options will suffice in most cases. Chapter 4, Numerical 
Aspects explains in more detail how the move limits of design variables 
function in each optimization loop.

Step 5. Define objective function 

Define the objective function using the 

OP_OBJDEF

 (Analysis > OPTIMIZE/

SENSITIVITY > OBJECTIVE FUNCTION > 

Define Function

) command. 

The command controls the following information:

- Types of objective functions,

- Layer and face numbers (for composite shells only),

- Analysis type (for multidisciplinary optimization), 

- Type of application (minimization or maximization),

- Criterion and approximation type (see Chapter 4),

- Convergence tolerance (see Chapter 4),

- Reference keypoint (relative displacement),

- Load case (multiple load cases only) or time step number (nonlinear or post 

dynamic only).

You can use the 

OP_OBJSET

 (Analysis > OPTIMIZE/SENSITIVITY > 

OBJECTIVE FUNCTION > 

Define Function Set

) command to declare 

portions (sets) of the model for objective function computations. It is also 
possible to assign weight factors to different parts of the model using the same 
command. This command is most useful for volume and weight objective 
functions (cost). However, it cannot be used with frequency and buckling 
functions.

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Use the 

OP_OBJDEL

 (Analysis > OPTIMIZE/SENSITIVITY > OBJECTIVE 

FUNCTION > 

Del Function Set

) command to delete sets defined by the 

OP_OBJSET

 (Analysis > OPTIMIZE/SENSITIVITY > OBJECTIVE 

FUNCTION > 

Define Function Set

) command.

To delete the objective function defined using the 

OP_OBJDEF

 (Analysis > 

OPTIMIZE/SENSITIVITY > OBJECTIVE FUNCTION > 

Define Function

command, you need to use the same command again to overwrite the old 
information.

Use the 

OP_OBJLIST

 (Analysis > OPTIMIZE/SENSITIVITY > OBJECTIVE 

FUNCTION > 

List Function

) command to list information defined by 

OP_OBJDEF

 (Analysis > OPTIMIZE/SENSITIVITY > OBJECTIVE 

FUNCTION > 

Define Function

) and 

OP_OBJSET

 (Analysis > OPTIMIZE/

SENSITIVITY > OBJECTIVE FUNCTION > 

Define Function Set

commands.

Step 6. Define constraints 

Define behavior constraints using the 

OP_CONDEF

 (Analysis > OPTIMIZE/

SENSITIVITY > BEHAVIOR CONSTRAINT > 

Define

) command. The 

command controls the following information:

- Types of behavior constraints,

- Layer and face numbers (for composite shells only),

- Analysis type (for multidisciplinary optimization),

- Geometry association,

- Lower and upper limits (bounds),

- Feasibility tolerance: 

Default values = 1/100 | upper bound- to lower bound |

- Reference keypoint (relative displacement),

- Criterion and approximation type (see Chapter 4),

- Load case (multiple load cases only) or time step number (nonlinear or post 

dynamic only).

Use 

OP_CONLIST

 (Analysis > OPTIMIZE/SENSITIVITY > BEHAVIOR 

CONSTRAINT > 

List Behavior Const

) and 

OP_CONDEL

 (Analysis > 

OPTIMIZE/SENSITIVITY > BEHAVIOR CONSTRAINT > 

Del Behavior 

Const

) commands to list and delete constraints, respectively.

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By default, OPTSTAR considers only the violated and potentially critical 
constraints during calculations. In order to control this step, use the command 

OP_CONTRIM

 (Analysis > OPTIMIZE/SENSITIVITY > BEHAVIOR 

CONSTRAINT > 

Truncate Constraint

) which allows you to input trimming 

(truncation) factors for the unviolated constraints. If the normalized value of a 
particular constraint is above the negative value of the truncation factor, then 
that constraint is appended to the critical list. For more detailed explanation, 
refer to Chapter 4, Numerical Aspects.

Step 7. Specify parameters for optimization 

Specify the parameters for the optimization loops using the 

A_OPTIMIZE

 

(Analysis > OPTIMIZE/SENSITIVITY > OPTIMIZE LOOP > 

Optimize 

Analysis Options

) command. The important input for this command are:

– Maximum number of optimization loops (nloops flag)

– Number of stages to check convergence (loop_conv flag)

– Type of analyses. It should be mentioned that an optimization loop will 

execute the analyses in the same sequence specified here. For heat transfer - 
linear static problems requiring data transfer from heat transfer to static 
analysis, you must specify THERMAL followed by STATIC.

– Number of consecutive infeasible design sets. You are recommended to 

always start with a feasible initial design. Otherwise, the program will prompt 
you with a choice to continue or stop. If you choose to continue, the 
optimization loops will be terminated if a feasible solution is not reached after 
five consecutive attempts. To change this number (five), use the 

A_OPTIMIZE

 

(Analysis > OPTIMIZE/SENSITIVITY > OPTIMIZE LOOP > 

Optimize 

Analysis Options

) command and specify the appropriate input for the infeas 

flag.

Start the optimization process using the 

R_OPTIMIZE

 (Analysis > OPTIMIZE/

SENSITIVITY > OPTIMIZE LOOP > 

Run Optimize Analysis

) command.

Step 8. Restart options prior to convergence

In cases where the maximum number of optimization loops are exceeded, you can 
restart the process by activating the restart flag under the 

A_OPTIMIZE

 (Analysis > 

OPTIMIZE/SENSITIVITY > OPTIMIZE LOOP > 

Optimize Analysis Options

command, followed by the 

R_OPTIMIZE

 (Analysis > OPTIMIZE/SENSITIVITY > 

OPTIMIZE LOOP > 

Run Optimize Analysis

) command. If you choose to use this 

option, only the following commands can be reissued (if needed): 

DVARLIST

OP_DVMOVE

OP_CONLIST

OP_CONTRIM

OP_OBJLIST

OP_CONTROL

.

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Step 9. Postprocess optimization results

You can display convergence plots of objective function (component name 
OP_OBJ), behavior constraints (component name OP_CON), and design 
variables (component name OP_DVAR) against number of loops using the 

ACTXYPOST

 (Display > XY PLOTS > 

Activate Post-Proc

) and 

XYPLOT

 

(Display > XY PLOTS > 

Plot Curves

) commands from the Display-XY Plots 

menu tree. It is also possible to list the activated result component on-line using 
the 

XYPTLIST

 (Display > XY PLOTS > 

List Points

) command. It should be 

mentioned that the 

ACTPOST

 (Results > SET UP > 

Set PostProcess Type

command has to be used prior to using the 

ACTXYPOST

 (Display > XY PLOTS 

Activate Post-Proc

) command.

The optimization results for each loop are summarized in the output file 
jobname.OPT.

Step 10. Postprocess converged analyses results

Perform postprocessing of the converged analyses as usual. Please refer to User 
Guide (Vol. 1) and Basic FEA System Manual (Vol. 3) for more information.

One of the good features of the optimization module is that you will have the 
optimum product in terms of its geometric dimensions (not giving only the final 
coordinates of the mesh) which is an aspect favored in the manufacturing 
process. Using the standard methods of transferring geometry (such as IGES 
and DXF formats), the users can transfer the final geometry to NC machines.

Step 11. Restore an interim design set

It is possible to examine the design configuration at an interim step even after 
the convergence of the optimization loops. The command 

OP_RESTORE 

(Analysis > OPTIMIZE/SENSITIVITY > OPTIMIZE LOOP > 

Restore 

Design Set

) can be used to restore a design set (corresponding to a specified 

loop number) so that the entire database can be reconstructed for the specified 
design set and the required analyses run automatically.

If you use the 

OP_RESTORE

 (Analysis > OPTIMIZE/SENSITIVITY > 

OPTIMIZE LOOP > 

Restore Design Set

) command, note that the converged 

solution obtained will be lost. You need to therefore save the database of the 
converged solution before applying this command.

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Procedures for Performing Sensitivity Studies

The following steps are recommended to be followed for performing sensitivity 
studies using OPTSTAR. These guidelines are not in any sense complete, and are 
intended to be complementary to your own knowledge and experience.

Step 1. Initial model and analysis

The first step is similar to steps 1 through 3 of the procedures recommended for 
performing design optimization:

 –

Build the model parametrically

 –

Execute required initial analyses

 –

Perform postprocessing of initial analysis results

Step 2. Begin sensitivity study by defining design variables

Define the design variables using the 

DVARDEF

 (Analysis > OPTIMIZE/

SENSITIVITY > DESIGN VARIABLES > 

Define

) command. Note that each 

design variable, whether of shape of sizing type, must have been already defined 
as a parameter (using the 

PARASSIGN

 (Control > PARAMETER > 

Assign 

Parameter

) command). It should be noted that the 

DVARDEF

 (Analysis > 

OPTIMIZE/SENSITIVITY > DESIGN VARIABLES > 

Define

) command is 

used for both optimization and sensitivity applications where some options of 
the command are needed only for optimization.

Use the commands 

DVARDEF

 (Analysis > OPTIMIZE/SENSITIVITY > 

DESIGN VARIABLES > 

Define

) and 

DVARLIST

 (Analysis > OPTIMIZE/

SENSITIVITY > DESIGN VARIABLES > 

List

) to delete and list the design 

variables respectively.

Step 3. Define the sensitivity response quantities 

Define the response quantity using the 

SN_RESPDEF 

(Analysis > OPTIMIZE/

SENSITIVITY > RESPONSE QUANTITY > 

Define

) command. The 

commands controls the following information:

- Type of response quantities,

- Layer and face numbers (for composite shells only),

- Analysis type (for multidisciplinary optimization),

- Geometry association,

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- Reference keypoint (relative displacement),

- Criterion type (see Chapter 4),

- Load case (multiple load cases only) or time step number (nonlinear or post 

dynamic only).

Use 

SN_RESPDEL

 (Analysis > OPTIMIZE/SENSITIVITY > RESPONSE 

QUANTITY > 

Delete

) and 

SN_RESPLIST

 (Analysis > OPTIMIZE/

SENSITIVITY > RESPONSE QUANTITY > 

List

) to delete and list response 

quantities respectively.

Step 4. Specify type of sensitivity 

Specify the type and parameters of the sensitivity study using the 

A_SENSITIV

 

(Analysis > OPTIMIZE/SENSITIVITY > SENSITIVITY RUN > 

Options

command. The important input for this command are:

– Type of sensitivity:

Global sensitivity, offset sensitivity, or local sensitivity. For offset and local 
sensitivity studies, the command 

SN_SETDEF

 (Analysis > OPTIMIZE/

SENSITIVITY > RESPONSE QUANTITY > 

Define

) should be used to 

define the user-specified design sets.

– Type of analyses:

It should be mentioned that a sensitivity run will execute the analyses in the 
same sequence specified here. For instance if you want to find the fundamental 
frequency of the model based on the deformed configuration calculated by the 
nonlinear program, you must specify NONLINEAR followed by 
FREQUENCY.

Start the sensitivity study by using the 

R_SENSITIV

 (Analysis > OPTIMIZE/

SENSITIVITY > SENSITIVITY RUN > 

Run Analysis

) command.

Step 5. Restart option

In cases where the sensitivity study is terminated by the user or due to an error, you 
can restart the process by activating the restart flag under the 

A_SENSITIV 

(Analysis > OPTIMIZE/SENSITIVITY > SENSITIVITY RUN > 

Options

command, followed by the 

R_SENSITIV

 (Analysis > OPTIMIZE/SENSITIVITY > 

SENSITIVITY RUN > 

Run Analysis

) command.

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Step 6. Postprocess sensitivity results

You can display plots of response quantities against value or label of design 
variables using the 

ACTXYPOST

 (Display > XY PLOTS > 

Activate Post-Proc

and 

XYPLOT

 (Display > XY PLOTS > 

Plot Curves

) commands from the 

Display-XY Plots menu tree. It is also possible to list the activated result 
component on-line using the 

XYPTLIST

 (Display > XY PLOTS > 

List Points

command. It should be mentioned that the 

ACTPOST

 (Results > SET UP > 

Set 

PostProcess Type

) command has to be used prior to using the 

ACTXYPOST

 

(Display > XY PLOTS > 

Activate Post-Proc

) command.

The sensitivity results are summarized in the output file jobname.OPT.

Special Features for Optimization and Sensitivity

Dynamic change of parameters

The user can specify the flags controlling the optimization and sensitivity features in 
terms of parametric expressions. For example, the upper and lower bounds of a 
design variable may not always be a constant value but depends on some boundary 
conditions and geometric features that change from one optimization or sensitivity 
run to another.

Restart option

For optimization, users can restart the process from the last successful design 
sets in the following cases:

– Iterations exceed the maximum allowed number.

– Number of trials to find a feasible solution exceeds the allowed number.

– Optimization process terminated by the user either during the optimization 

screen or during regenerating the model's geometry or mesh using the <Esc> 
key

– Optimization terminated because of failure to regenerate the model or crash of 

optimization procedure.

For sensitivity studies, you can restart the process from the last successful run in 
the following cases:

- Terminating the process during the sensitivity screen or generating the model's 

geometry or mesh using the <Esc> key.

- Failure to regenerate the model.

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It should be mentioned that you can restart the optimization process (as a fresh 
start) from the current design variable values as new initial values by choosing 
the OFF option in the restart flag. In this case, optimization will begin its first 
iteration all over again. For example, if your model converged to an optimum 
selection in eight iterations, and you chose to restore the fifth design set to 
inspect it. If you choose fresh start at this point, the optimizer will consider the 
design variables, constraints and objective function values of the fifth design set 
as initial values in a new optimization run.

User-defined constraints, objective function and sensitivity response 
quantities

Situations may arise where you need to customize your own objective function, 
behavior constraints, or sensitivity response quantities. A user-defined feature is 
included in the 

OP_OBJDEF

 

(Analysis > OPTIMIZE/SENSITIVITY > 

OBJECTIVE FUNCTION >

Define Function

), 

OP_CONDEF

 (Analysis > 

OPTIMIZE/SENSITIVITY > BEHAVIOR CONSTRAINT > 

Define Behavior 

Constraint

) and 

SN_RESPDEF

 (Analysis > OPTIMIZE/SENSITIVITY > 

RESPONSE QUANTITY > 

Define

) commands. The user-defined quantity has 

to be declared by a 

PARASSIGN

 (Control > PARAMETER > 

Assign 

Parameter

) command prior to issuing the 

OP_OBJDEF

 

(Analysis > 

OPTIMIZE/SENSITIVITY > OBJECTIVE FUNCTION > 

Define Function

), 

OP_CONDEF

 (Analysis > OPTIMIZE/SENSITIVITY > BEHAVIOR 

CONSTRAINTS > 

Define Behavior Constraint

) or 

SN_RESPDEF

 (Analysis > 

OPTIMIZE/SENSITIVITY > RESPONSE QUANTITY > 

Define

) commands. 

These quantities can be calculated using the extensive options provided by the 
COSMOSM command language (User Guide, Vol. 1, Appendix E).

Regenerating the model through GEOSTAR requires reading all the steps you 
followed as stored in the session file in every optimization or sensitivity loop. 
There are however some commands (action commands) in the session file that 
are ignored by GEOSTAR (e.g. “

R_

” or “

R...

” commands). The reason is that it 

would be very time consuming to follow the user's steps of running analysis 
modules since you might have executed these commands many times to check 
and modify the initial model. Instead, the control of this step is left to the 

A_OPTIMIZE

 (Analysis > OPTIMIZE/SENSITIVITY > OPTIMIZE LOOP > 

Optimize Analysis Options

) and 

A_SENSITIV

 (Analysis > OPTIMIZE/

SENSITIVITY > SENSITIVITY RUN > 

Options

) commands.

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User-defined objective function, behavior constraint or a response quantity may 
be a preprocessing or a postprocessing quantity. An example of a preprocessing 
quantity is the volume or weight of some elements. Once the mesh is generated 
you will be able to use its information to calculate these quantities (using 
VOLUME and WEIGHT functions explained in Appendix E of the User 
Guide.) If the user-defined feature is a postprocessing-function dependent 
quantity, it must be defined after running the analysis. For example, in order to 
use the frequency function (FREQ) you have to execute 

R_FREQUENCY

 

(Analysis > FREQUENCY/BUCKLING > 

Run Frequency

) first. Another 

example is the use of secondary load cases using the 

LCCOMB

 (Results > 

Combine Load Case

) command. You need to run 

R_STATIC

 (Analysis > 

STATIC > 

Run Static Analysis 

first followed by the 

LCCOMB

 (Results > 

Combine Load Case

) command.

In order to respect the sequence (or order) of issuing some of GEOSTAR 
commands which is essential in some user-defined cases, a separate option is 
included in the type of analysis flag defined by the 

A_OPTIMIZE

 (Analysis > 

OPTIMIZE/SENSITIVITY > OPTIMIZE LOOP > 

Optimize Analysis 

Options

) and 

A_SENSITIV

 

(Analysis > OPTIMIZE/SENSITIVITY > 

SENSITIVITY RUN > 

Options

) command. This option is called “FILE”, and it 

means that the type of analysis (“

R_

” commands.) and other GEOSTAR 

commands are included in a separate file prepared by the user. The file name 
should be GEOFILE.FIL and it has to be located in the local directory. This file 
include the “

R_

” 

commands and other action commands given in the sequence 

necessary for calculating the user-defined quantities.

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In this example, you are required to find the thickness of the two shafts (TR1 and 
TR2), and the size and location of the cutout (TW). The outer arm thickness is 20 

mm, modulus of elasticity is 2 x 10

5

 MPa, and Poisson’s ratio is 0.3. The control 

arm is subjected to a pressure loading of 4 MPa as shown in the following figure. 
The only constraint on the control arm is that the von Mises stress due to the 
applied loading should neither exceed 225 MPa nor fall below 10 MPa. The 
objective function for minimization is the volume of the control arm with a 
tolerance of 1%.

Figure

3-4. Initial Geometry, Boundary Conditions and Loads

The design variables for this problem as seen from the above figure are 
designated as TR1, TR2 and TW. Since their value will change with each 
optimization cycle, they will be defined as parameters using the 

PARASSIGN

 

(Control > PARAMETER > 

Assign Parameter

) command. The bounds, initial 

values and tolerances for the design variables are as shown below:

Shape Optimization of a Slotted 

Control Arm in Static Analysis

(See 

page 

3-1.)

5

5

5

tr

Fixed

 = 140

1

tr

2

20

20

10

10

tw

P

Y

6 - Node  TRI ANG

=  20 mm

=  2 x 10   N/mm

2

5

=  0.3

=  4 N/ mm

  

 (Y direction)

Thickness

E

Note:  All dimensions in millimeters.

ν

2

P

r   = 30

1

r    = 7

2

Y

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Using the design variables as well as other geometric dimensions, you will first 
build the initial geometry of the model parametrically. In the next step, the finite 
element mesh of the initial geometry will be subjected to loads and boundary 
conditions. The linear static stress analysis is performed as usual. After successful 
completion, you need to specify the input for design optimization, and solve for the 
optimal shape of the control arm. During the optimization cycle, the program will 
automatically change the design variable values as required and perform linear 
static stress analysis to satisfy the constraints. The following paragraphs describe 
all relevant steps in detail with illustrations.

1.

To start with, set a working plane by executing the following command:

Geo Panel:

 Geometry > GRID > 

Plane (PLANE)

Rotation/sweep axis > 

2

Offset on axis > 

0.0

Grid line style > 

Solid

2.

Initialize all parameters used to build the model using the 

PARASSIGN

 (Control 

> PARAMETER > 

Assign Parameter

) command. Let us start with the design 

variables (TR1, TR2 and TW):

Geo Panel:

 Control > PARAMETER > 

Assign Parameter (PARASSIGN)

Parameter name > 

TR1

Data type > 

REAL

Parametric real value > 

25

Geo Panel:

 Control > PARAMETER > 

Assign Parameter

 

(PARASSIGN)

Parameter name > 

TR2

Data type > 

Real

Parameter real value > 

20

In addition to the required design variables, you can define some other 
dimensions of the model as parameters. These dimensions include the length 
between the centers of the shafts and their radii (L, R1 and R2).

Bounds

Initial Value

Tolerance

 8 

≤ 

TR1 

 25

25

1

 TR2 

 20

20

1

 TW 

 

8

8

0.5

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Geo Panel:

 Control > PARAMETER > 

Assign Parameter

 

(PARASSIGN)

Parameter name > 

R1

Data type > 

Real

Parameter real value > 

30

Geo Panel:

 Control > PARAMETER > 

Assign Parameter (PARASSIGN)

Parameter name > 

R2

Data type > 

Real

Parameter real value > 

7

Geo Panel:

 Control > PARAMETER > 

Assign Parameter (PARASSIGN)

Parameter name > 

L

Data type > 

Real

Parameter real value > 

140

The parameters defined above can be listed on-screen using the 

PARLIST

 

(Control > PARAMETER > 

List Parameter

) command which provides a 

summary as shown below:

3.

For this problem, you need to increase the closure tolerances at keypoints. 
Establish keypoints for the centers of shafts as follows (note the parametric 
input for the center of the smaller shaft):

Geo Panel:

 Geometry > POINTS > 

Merge Tolerance (PTTOL)

Tolerance > 

0.001

Geo Panel:

 Geometry > POINTS > 

Define (PT)

Keypoint > 

1

XYZ-coordinate value > 

0.0, 0.0, 0.0

Geo Panel:

 Geometry > POINTS > 

Define (PT)

Keypoint > 

2

XYZ-coordinate value > 

L, 0, 0

Num

Name

Type

Value

1

TR1

REAL

25.000000

2

TR2

REAL

20.000000

3

TW

REAL

8.000000

4 R1

REAL

30.000000

5 R2 

REAL

7.000000

6 L

REAL

140.000000

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4.

Use the Auto scale icon to adjust the view on the screen. Next, draw circles at 
the points created above using the 

CRSCIRCLE

 (Geometry > CURVES > 

CIRCLES > 

By Center/Edge

) command to model the two shafts. The shafts 

have a radius of R1 and R2 with thickness of TR1 and TR2 (defined as 
parameters). The prompts and input for creating the shafts are as below 
[

ACTNUM

 (Control > ACTIVATE > 

Entity Label

) command is used to activate 

labels of curves]:

Geo Panel:

 Geometry > CURVES > CIRCLES > 

By Center/Edge 

(CRSCIRCLE)

Curve > 

1

XYZ-coordinate value of center of circle > 

0.0, 0.0, 0.0

XYZ-coordinate value of center of circle >

 R1, 0.0, 0.0

Number of segments > 

4

Geo Panel:

 Geometry > CURVES > CIRCLES > 

By Center/Edge 

(CRSCIRCLE)

Curve > 

5

XYZ-coordinate value of center of circle >

 L, 0.0, 0.0

XYZ-coordinate value of center of circle > 

L+R2, 0.0, 0.0

Number of segments > 

4

Geo Panel:

 Geometry > CURVES > CIRCLES > 

By Center/Edge 

(CRSCIRCLE)

Curve > 

9

XYZ-coordinate value of center of circle > 

0.0, 0.0, 0.0

XYZ-coordinate value of center of circle > 

R1+TR1, 0.0, 0.0

Number of segments > 

4

Geo Panel:

 Geometry > CURVES > CIRCLES > 

By Center/Edge 

(CRSCIRCLE)

Curve > 

13

XYZ-coordinate value of center of circle > 

L

XYZ-coordinate value of center of circle > 

L+R2+TR2

Number of segments > 

4

5.

Use the Auto scale icon to re-scale the screen view. The circles created above 
will be connected together by straight lines tangential to the inner circles of the 
shafts using the 

CRTANLIN

 (Geometry > CURVES > MANIPULATION 

MENU > 

Tangent btwn 2 Cr

) command as illustrated below.

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Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Tangent 

btwn 2 Cr (CRTANLIN)

Curve > 

17

Curve 1 > 

1

Curve 2 > 

5

Break flag > 

Do not break

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Tangent 

btwn 2 Cr (CRTANLIN)

Curve > 

18

Curve 1 > 

4

Curve 2 > 

8

Break flag > 

Do not break

The figure below shows a view of the two shafts connected together by tangential 
lines. Note that the lines protruding into the shaft thicknesses will be trimmed later.

Figure

3-5 Construction of Tangential Lines Connecting the Shafts

6.

Activate the display of point tables using the Status 1 icon. In the next step, you 
will construct two more lines parallel to the tangents created earlier representing 
the slotted portion of the model. In order to draw these lines, you can define a 
coordinate system along the tangential lines so that the new curves generated 
will be parallel to the tangential lines. Use the 

CSYS

 (Geometry > COORD 

SYS > 

By 3 Points

) command as shown below:

Geo Panel:

 Geometry > COORD SYS > 

By 3 Points (CSYS)

Coordinate system > 

3

Coordinate system type > 

Cartesian

Keypoint at origin > 

19

Keypoint on the X-axis > 

20

Keypoint on the X-Y plane > 

1

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Geo Panel:

 Geometry > COORD SYS > 

By 3 Points (CSYS)

Generation number > 

1

Beginning curve > 

18

Ending curve > 

18

Increment < 

1

Generation flag > 

Translation

X-displacement > 

0.0

Y-displacement > 

-TW

Z displacement > 

0.0

Next, apply the 

CRGEN

 (Geometry > CURVES > GENERATION MENU > 

Generate

) command at the top tangent line and input an offset of -TW (with 

respect to the new coordinate system) which represents the thickness of the 
slotted portion.

Geo Panel:

 Geometry > CURVES > GENERATION MENU > 

Generate 

(CRGEN)

Generation number > 

1

Beginning curve > 

17

Ending curve > 

17

Increment > 

1

Generation flag > 

Translation

X-displacement > 

0.0

Y-displacement > 

-TW

Z-displacement > 

0.0

Similarly apply the 

CSYS

 (Geometry > COORD SYS >

 By 3 Points

) and 

CRGEN

 (Geometry > CURVES > GENERATION MENU > 

Generate

commands at the bottom tangent line as shown below:

Geo Panel:

 Geometry > COORD SYS > 

By 3 Points (CSYS)

Coordinate system > 

4

Coordinate system type > 

Cartesian

Keypoint at origin > 

21

Keypoint on the X-axis > 

22

Keypoint on the X-Y plane > 

1

7.

You now need to remove the lines protruding into the shaft thicknesses. This can 
be achieved by finding the intersection of the straight lines with the outer circles 
of the shafts and then subdividing the lines at the points of intersection. The 
lines inside the shafts can be then easily removed. The commands below 
illustrate these tasks:

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Geo Panel:

 Geometry > POINTS > GENERATION MENU > 

Cr/Cr 

Intersect (PTINTCC)

Primary curve > 

17

Beginning curve > 

9

Ending curve > 

14

Increment > 

5

Tolerance > 

0.000050

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

Curve to be broken > 

17

Reference keypoint > 

27

Original curve keeping flag > 

Do not keep

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

Curve to be broken > 

21

Reference keypoint > 

28

Original curve keeping flag > 

Do not keep

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

Beginning curve > 

17

Ending curve > 

22

Increment > 

5

You need to repeat the above procedure for the remaining three lines of the 
slotted portion as outlined below: (Cryptic commands need to be typed in the 
command window; however, the command paths are also shown.)

Geo Panel:

 Geometry > POINTS > GENERATION MENU > 

Cr/Cr Intersect (PTINTCC)

PTINTCC,18,12,15,3;

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

CRPTBRK,18,29,0;
CRPTBRK,22,30,0;

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,18,18,1;
CRDEL,23,23,1;

Geo Panel:

 Geometry > POINTS > GENERATION MENU > 

Cr/Cr Intersect (PTINTCC)

PTINTCC,19,9,14,5;

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Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

CRPTBRK,19,31,0;
CRPTBRK,23,32,0;

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,19,19,1;
CRDEL,24,24,1;

Geo Panel:

 Geometry > POINTS > GENERATION MENU > 

Cr/Cr Intersect (PTINTCC)

PTINTCC,20,12,15,3;

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

CRPTBRK,20,33,0;
CRPTBRK,24,34,0;

Geo Panel:

 Edit > DELETE >

 Curves (CRDEL)

CRDEL,20,20,1;
CRDEL,25,25,1;

8.

Next, it is necessary to remove arcs of the outer circles at the connection with 
the slotted portion so that model domain is continuous. There are four such arcs 
and the 

CRPTBRK

 (Geometry > CURVES > MANIPULATION MENU > 

Break Near Pt

and 

CRDEL

 (Edit

 > 

DELETE

 > 

Curves

) commands are applied 

to remove them as illustrated below:

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

CRPTBRK,9,27,0;
CRPTBRK,25,31,0;

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,25,25,1;

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU >

 Break 

Near Pt (CRPTBRK)

CRPTBRK,12,29,0;
CRPTBRK,12,33,0;

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,28,28,1;

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Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

CRPTBRK,14,28,0;
CRPTBRK,14,32,0;

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,29,29,1;

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

CRPTBRK,15,30,0;
CRPTBRK,29,34,0;

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,29,29,1;

The figure below shows the geometry created so far, with curve labels activated. 
These labels will be helpful in defining fillets at sharp corners, described next.

Figure

3-6. Interim Model Geometry with Curve Labels

9.

It is necessary to smooth the sharp corners at the intersection points of straight 
lines with the shafts. Fillets at these points can be defined using the 

CRFILLET

 

(Geometry > CURVES > MANIPULATION MENU > 

Fillet

) command. The 

labels of adjacent curves can be seen from the above figure for this command.

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Fillet 

(CRFILLET)

Curve > 

31

Curve 1 > 

21

Curve 2 > 

9

Radius of fillet > 

5

Trim flag > 
Original curve keeping flag >
Tolerance > 

0.000001

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Repeat the above command at other locations as shown below (as before, the 
cryptic commands need to be typed in the command window; command paths 
on the menu are also shown):

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Fillet 

(CRFILLET)

CRFILLET,33,22,27,5,1,0;
CRFILLET,35,21,28,5,1,0;
CRFILLET,37,22,15,5,1,0;
CRFILLET,39,23,26,20,1,0;
CRFILLET,40,24,12,20,1,0;
CRFILLET,41,23,14,10,1,0;
CRFILLET,42,24,30,10,1,0;

The figure below shows the initial geometry of the control arm for finite element 
model development. In order to generate the finite element mesh, you need to 
convert the geometry to a region entity and use the automatic meshing feature for 
regions.

Figure

3-7. Initial Geometry of the Control Arm for Finite Element Modeling

10.

There are four contours constituting one region entity for this model. The outer 
contour will be designated as the first contour and the inner ones will be 
numbered 2 through 4. The design variables TR1, TR2, and TW will alter the 
profiles of the outer contour and the middle inner contour in the slotted portion. 
The average element size is specified as half of the value of TW, the thickness of 
the slotted part. You also need to switch to the global coordinate system at this 
point. The contour and region definitions are illustrated below:

Geo Panel:

 Control > ACTIVATE > 

Set Entity (ACTSET)

Set Label > 

CS

Coordinate system > 

0

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Geo Panel:

 Geometry > CONTOURS > 

Define (CT)

Contour > 

1

Mesh flag > 

Esize

Average element size >

TW/2

Number of reference boundary curves > 

1

Curve 1 > 

23

Use selection set > 

No

Geo Panel:

 Geometry > CONTOURS > 

Define (CT)

CT,2,0,TW/2,1,21,0;
CT,3,0,TW/2,1,1,0;
CT,4,0,TW/2,1,5,0;

Geo Panel:

 Geometry > REGIONS > 

Define (RG)

Region > 

1

Number of contours > 

1

Outer contour > 

1

Inner contour 1 > 

2

Inner contour 2 > 

3

Inner contour 3 > 

4

Underlying surface > 

0

11.

Generate the finite element mesh and define the element group, material 
properties, section constants, and higher order elements as illustrated below:

Geo Panel:

 Propsets > 

Element Group (EGROUP)

Element group > 

1

Element Category > 

Area

Element Type (for area) > 

TRIANG

Accept defaults ....

Geo Panel:

 Propsets > 

Real Constant (RCONST)

Associated element group > 

1

Real constant set > 

1

Start location of the real constants > 

1

No. of real constants to be entered > 

2

RC1: thickness > 

20

RC2: material angle (Beta) > 

0.0

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Geo Panel:

 Propsets > 

Material Property (MPROP)

Material property set > 

1

Material property name > 

EX

Property value > 

200000

Material property name 

NUXY

Property value > 

0.3

Geo Panel:

 Meshing > AUTO MESH > 

Regions (MA_RG)

Beginning region > 

1

Ending region > 

1

Increment > 

1

Number of smoothing iterations > 

0

Method of Sweeping

Geo Panel:

 Meshing > AUTO MESH > 

Region

 

Mesh Type (MARGCH)

Beginning region > 

1

Ending region > 

1

Increment > 

1

Element type > 

T

Total element nodes > 

6

Push flag > 

Yes

Associate element group > 

1

Define the boundary conditions and loads.

Geo Panel:

 LoadsBC > STRUCTURAL > DISPLACEMENT > 

Define 

Curves (DCR)

Beginning curve > 

1

Displacement label > 

All

Value > 

0.0

Ending curve > 

4

Increment > 

1

Geo Panel:

 LoadsBC > STRUCTURAL > PRESSURE > 

Define Curves 

(PCR)

Beginning curve > 

5

Pressure magnitude > 

4

Ending curve > 

6

Increment > 

1

Pressure at the end of direction 1 > 

4

Pressure direction > 

Normal direction

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12.

Proceed with linear static stress analysis by executing the 

R_STATIC

 (Analysis 

> STATIC > 

Run Static Analysis

) command.

13.

It is a good practice to postprocess the results from the preliminary design 
before starting the optimization loops due to several reasons. First, you can 
eliminate any modeling errors by inspecting the results. More importantly, you 
can make sure that the behavior constraints imposed on the model for 
optimization are realistic. For this example, the von Mises stress constraint has 
bounds of 10 and 225, whereas the computed von Mises stress for the 
preliminary design ranges from 0 to 90 (you can either use the 

STRMAX

 

(Results > EXTREMES > 

Min/Max Stress

) or 

STRPLOT

 (Results > PLOT > 

Stress

) commands to process the von Mises stress). Therefore, the constraints 

specified for this example are indeed realistic.

After the linear static analysis is successfully completed, you can proceed to define 
the input for shape optimization. The following commands for specifying 
optimization analysis options are found in the Analysis > OPTIMIZE/
SENSITIVITY menu tree.

14.

Define the design variables. There are three design variables (TR1, TR2, and 
TW) for this problem that will be applied in obtaining an optimal shape of the 
model under linear static analysis. Each of the design variable needs to be 
defined separately using the 

DVARDEF

 

(Analysis > OPTIMIZE/SENSITIVITY 

> DESIGN VARIABLES > 

Define

) command. You also need to specify the 

upper and lower bounds of the design variable under this command.

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY > DESIGN VARIABLES 

> 

Define (DVARDEF)

Design variable set number > 

1

Design variable type > 

Shape

Design variable parametric name > 

TR1

Design variable lower bound > 

8

Design variable upper bound > 

25

Design variable conv. tol. for optimization > 

1

Preopt process: zero=random nonzero=perturb_ratio > 

0.0

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY > DESIGN VARIABLES 

> 

Define (DVARDEF)

Design variable set number > 

2

Design variable type > 

Shape

Design variable parametric name > 

TR2

Design variable lower bound > 

8

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Design variable upper bound > 

20

Design variable conv. tol. for optimization > 

1

Preopt process: zero=random nonzero=perturb_ratio > 

0.0

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY > DESIGN VARIABLES 

> 

Define (DVARDEF)

Design variable set number > 

3

Design variable type > 

Shape

Design variable parametric name > 

TW

Design variable lower bound > 

3

Design variable upper bound > 

8

Design variable conv. tol. for optimization > 

0.5

Preopt process: zero=random nonzero=perturb_ratio > 

0.0

The 

DVARLIST

 (Analysis > OPTIMIZE/SENSITIVITY > DESIGN VARIABLES 

> 

List

) command can be used to obtain an on-screen listing of design variables 

defined above. The listing for this problem is as shown below:

15.

The objective function to be minimized (or maximized) and the associated 
parameters for nodal or elemental type functions is defined using the 

OP_OBJDEF

 (Analysis > OPTIMIZE/SENSITIVITY > OBJECTIVE 

FUNCTION > 

Define Function

) command. For this example, you will be 

minimizing volume as an elemental quantity using linear approximation to start 
with. Quadratic approximations with cross terms as well as cubic terms will be 
used for subsequent approximations of the objective function (approximation 
type 3).

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY> OBJECTIVE 

FUNCTION > 

Define Function (OP_OBJDEF)

Type > 

Elemental

Objective > 

Minimize

Elemental objective function name > 

Volume

Set

Type

DvName

Value

Lower/

Upper Bound

Tolerance/

Perturb Ratio

1

Shape

TR1

2.5000e+001

8.0000e+000

1.0000e+000

2.5000e+001

0.0000e+000

2

Shape

TR2

2.0000e+001

8.0000e+000

1.0000e+000

2.0000e+001

0.0000e+000

3

Shape

TW

8.0000e+000

3.0000e+000

5.0000e-001

8.0000e+000

0.0000e+000

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Analysis type > 

Linear

Unused option >
Unused option >
Objective function convergence tolerance (ratio) > 

0.01

Objective function approximation type > 

Linear + quadratic

The objective function input can be listed on-screen using the 

OP_OBJLIST

 

(Analysis > OPTIMIZE/SENSITIVITY > OBJECTIVE FUNCTION > 

List 

Function

) command which provides the following information:

16.

The remaining input for performing shape optimization of the control arm 
is the constraint definition. The 

OP_CONDEF

 (Analysis > OPTIMIZE/

SENSITIVITY > BEHAVIOR CONSTRAINT > 

Define

) command is used 

to define the constraints as illustrated below:

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY > BEHAVIOR 

CONSTRAINT > 

Define (OP_CONDEF)

Constraint set number > 

1

Type > 

Nodal

Nodal constraint name > 

VON

Analysis type > 

Linear

Criterion flag > 

Max Abs

Layer number > 

1

Face flag (shell) > 

Top

Load case/time step > 

1

Entity type assoc. with constraint > 

Nodes

Beginning node > 

1

Ending node > 

NDMAX

See paragraph below

Increment of nodes > 

1

Constraint lower bound > 

10

Constraint upper bound > 

225

Constraint feasibility tolerance > 

3

Constraint approximation type > 

Linear + Quad

Objtyp

= Elemental

Tolerance

= 1.000000e-002

Objname

= VOLUME

ApprxType

= 1

Objective

:  Minimize

Value

= 2.003479e+005

Layer

= 1

Face

=1

Analysis

= Static

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In the above, the second prompt seeks your input for the type of constraint, in 
this case, nodal. The criterion flag specifies whether the absolute maximum, or 
algebraic maximum, etc., is applied for evaluating the constraints. The entity 
type associated with the constraint are nodes for this example. Since the label of 
the ending node is not known in advance, and will keep changing for different 
optimization loops, you can input a parametric equivalent (NDMAX) for that 
prompt. The constraint upper and lower bounds as well as the tolerance are 
input for the next three prompts. The last prompt seeks your input for constraint 
approximation type. The default option of 1 for this prompt will use linear and 
quadratic terms for approximations of the constraint function.

The constraint input can be listed on-screen using the 

OP_CONLIST

 (Analysis 

> OPTIMIZE/SENSITIVITY > BEHAVIOR CONSTRAINT > 

List Behavior 

Const

) command.

17.

The last set of input you need to specify before beginning the optimization loops 
is furnished using the 

A_OPTIMIZE

 (Analysis > OPTIMIZE/SENSITIVITY > 

OPTIMIZE LOOP > 

Optimize Analysis Options

) command. The command 

and its input are shown below:

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY > OPTIMIZE LOOP > 

Optimize Analysis Options (A_OPTIMIZE)

Maximum number of optimization loops > 

10

Convergence check stages > 

To the previous loop

No. of consec. infeasible designs > 

5

Output print flag > 

On

Echo option flag > 

On

Restart flag > 

Off

Type of analysis > 

Static

In the above, the default option of 1 for the second prompt means that the 
convergence is achieved if the change in the objective function and design 
variables compared to the previous loop and the best design so far is less than 
the tolerance. If the initial design is infeasible and your model goes through five 
consecutive infeasible designs, the optimization process will be halted by 
default. The type of analysis to be run in the optimization loop is static stress 
analysis by default, and the program will prompt you further if you plan to run 
multidisciplinary analyses. The options you specified under the 

A_OPTIMIZE

 

(Analysis > OPTIMIZE/SENSITIVITY > OPTIMIZE LOOP > 

Optimize 

Analysis Options

) command can be listed on-screen using the 

A_LIST

 

(Analysis > 

List Analysis Option

) command (from the ANALYSIS submenu) 

as shown below:

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Geo Panel:

 Analysis > 

List Analysis Option (A_LIST)

Component > 

Optimization

18.

You can now proceed to perform the shape optimization analysis of the slotted 
control arm. Use the 

R_OPTIMIZE

 (Analysis > OPTIMIZE/SENSITIVITY > 

OPTIMIZE LOOP > 

Run Optimize Analysis

) command to start the 

optimization loops.

19.

The results of the static stress analysis performed will be written as usual to the 
jobname.OUT file. Note that this file will only contain results corresponding to 
the final design. If you want to store analysis results of all loops. you need to use 
the 

PRINT_OPS

 

(Analysis > OUTPUT OPTIONS > 

Set Print Options

command to append all subsequent results to this file. For optimization iteration 
summary of all loops, you can view the jobname.OPT file. Let’s create four 
windows using

 

the New Win icon. Move to the first window by clicking inside 

he window.

20.

In main window, we will plot the von Mises stresses using the 

ACTSTR

 and 

STRPLOT

 commands (Results > PLOT > 

Stress

).

21.

In window 1, we will study the variation of objective functions versus the 
optimization loops. Move to window 2 and execute the 

ACTXYPOST

 

(Display 

> XY PLOTS > 

Activate Post-Proc

)

 

and 

XYPLOT

 (Display > XY PLOTS > 

Plot Curves

) commands (Display > WINDOWS menu tree) as illustrated 

below:

Geo Panel:

 Results > SET UP > 

Set to Post-Proc (ACTPOST)

Select optimization

Geo Panel:

 Display > XY PLOTS > 

Activate Post-Proc (ACTXYPOST)

Graph number > 

1

Y_variable > 

OP_OBJ

Type of results > 

FEA

Graph color > 

12

Graph line style > 

Solid

Graph symbol style > 

1

Graph id > 

OP_OBJ

Adjust the X- and Y-axis intervals of the X-Y plot (for a clear display) by 
making use of the 

SETXYPLOT

 (Display > XY PLOTS > 

Set Plot Parameter

command as illustrated below:

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Geo Panel:

 Display > XY PLOTS > 

Set Plot Parameter (SETXYPLOT)

X logarithmic > 

No

Y logarithmic > 

No

Number of X intervals > 

7

Number of Y intervals > 

4

Accept Defaults

Geo Panel:

 Display > XY PLOTS > 

Plot Curves (XYPLOT)

Plot graph 1 > 

Yes

22.

In window 2, we will study the variation of the design variables versus the 
optimization loops. Since there are three design variables in this example, you 
will use set numbers 1, 2, and 3 for TR1 TR2 and TW respectively. Move to 
window 3 and execute the 

ACTXYPOST

 (Display > XY PLOTS > 

Activate 

Post-Proc

)

 

and 

XYPLOT

 (Display > XY PLOTS > 

Plot Curves

) commands as 

illustrated below (remember to use the 

SETXYPLOT

 (Display > XY PLOTS > 

Set Plot Parameter

) command to adjust the X-axis and Y-axis intervals):

Geo Panel:

 Display > XY PLOTS > 

Activate Post-Proc (ACTXYPOST)

Graph number > 

1

Y_variable > 

OP_DVAR

Set number > 

1

Graph color > 

12

Graph line style > 

Solid

Graph symbol style > 

1

Graph id > 

OP_DVAR-1

Geo Panel:

 Display > XY PLOTS > 

Activate Post-Proc (ACTXYPOST)

Graph number > 

2

Y_variable > 

OP_DVAR

Set number > 

2

Graph color > 

14

Graph line style > 

Solid

Graph symbol style > 

1

Graph id > 

OP_DVAR-2

Geo Panel:

 Display > XY PLOTS >

 Activate Post-Proc (ACTXYPOST)

Graph number > 

3

Y_variable > 

OP_DVAR

Set number > 

3

Graph color > 

8

Graph line style > 

Solid

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Graph symbol style > 

1

Graph id > 

OP_DVAR-3

Geo Panel:

 Display > XY PLOTS > 

Set Plot Parameter (SETXYPLOT)

...

Geo Panel:

 Display > XY PLOTS > 

Plot Curves (XYPLOT)

Plot graph 1 > 

Yes

Plot graph 2 > 

Yes

Plot graph 3 > 

Yes

23.

In window 3, we will study the variation of the behavior constraint versus the 
optimization loops. Move to window 3 and execute the 

ACTXYPOST

 (Display > 

XY PLOTS > 

Activate Post-Proc

) and 

XYPLOT

 (Display > XY PLOTS > 

Plot 

Curves

) commands as illustrated below:

Geo Panel:

 Display > XY PLOTS >

 Activate Post-Proc (ACTXYPOST)

Graph number > 

1

Y_variable > 

OP_CON

Set number > 

1

Type of results > 

FEA

Graph color > 

12

Graph line style > 

Solid

Graph symbol style > 

1

Graph id > 

OP_CON-1

Geo Panel:

 Display > XY PLOTS >

 Set Plot Parameter (SETXYPLOT)

...

Geo Panel:

 Display > XY PLOTS > 

Plot Curves (XYPLOT)

XYPLOT
Plot graph 1 > 

Yes

You will obtain a plot as shown in the following figure. Note that you can use the 

XYPTLIST

 (Display > SET UP > 

List Points

) command to list the values of the 

optimization results for each loop on-screen.

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Figure

3-8. Final Stress Distribution and Convergence Plots

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In this example, you are required to find the size and location of the cutout under 
the first (out-of-plane) mode of free vibration. The bracket thickness is 0.3 cm, 

modulus of elasticity is 2 x 10

7

 N/cm

2

, and Poisson’s ratio is 0.3. The material mass 

density is 0.0075 Kg/cm

3

The following figure shows the initial geometry of the 

bracket.

Figure

3-9. Initial Geometry of the Control Arm Bracket

The design variables for this problem as seen from the above figure are designated 
as T1 and T2. Since their value will change with each sensitivity run, they will be 
defined as parameters using the 

PARASSIGN

 (Control > PARAMETER > 

Assign 

Parameter

) command. The initial values and bounds for the design variables are as 

shown below:

Sensitivity Study of a Control Arm 

Bracket in Frequency

(See 

page 

3-1.)

Design Variable

Initial Value

Lower Bound

Upper Bound

T1

2.5

0.5

2.5

T2

3.5

1.5

3.5

15.

0

1.5

1.0

Y

X

r = 1.0
r = 

1.5

1.0

t

1

t

1

t

2

5.0

5.0

0.5

=  0.3 cm
=  2 x 10   N/cm
=  0.30
=  0.0075 Kg/cm

7

2

Thickness
E

Note:  All dimensions in centimeters.

2

ρ

ν

S

S

S

S

S h

h

h

h

h e

e

e

e

el

l

l

l

ll

l

l

l

l3

3

3

3

3

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Using the design variables as well as other geometric dimensions, you will first 
build the initial geometry of the model parametrically. In the next step, the finite 
element mesh of the initial geometry will be subjected to boundary conditions. The 
frequency analysis is then performed as usual. After successful completion, you 
need to specify the input for sensitivity study. During he sensitivity runs, the 
program will automatically change the design variable values as required and 
perform frequency analysis. The following steps describe all relevant procedures in 
detail with illustration.

1.

To start with, set the working plane and the view, and initialize the design 
variables T1 and T2 by executing the following commands:

Geo Panel:

 Geometry > GRID > 

Plane (PLANE)

PLANE;

Use the VIEW icon

VIEW;

Geo Panel:

 Control > PARAMETER >

 Assign Parameter (PARASSIGN)

PARASSIGN,T1,REAL,2.5,
PARASSIGN,T2,REAL,3.5,

2.

Establish the following keypoints for use in geometry creation:

Geo Panel:

 Geometry > POINTS > 

Define (PT)

PT,1,0,0,0,
PT,2,10,0,0,
PT,3,5,15,0,

Use Auto scaling icon

SCALE,0,

3.

Scale the view using the Auto scaling icon. Construct a triangle connecting the 
three keypoints created above using the 

CRLINE

 

(Geometry > CURVES > 

Line 

with 2 Pts

) command as shown below 

ACTNUM

 (Control > ACTIVATE > 

Entity Label

) command is used to activate labels of curves):

Geo Panel:

 Control > ACTIVATE > 

Entity Label (ACTNUM)

ACTNUM,CR,1;

Geo Panel:

 Geometry > CURVES > 

Line with 2 Pts (CRLINE)

CRLINE,1,1,3,
CRLINE,2,1,2,
CRLINE,3,2,3,

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4.

Next, we will generate a line parallel to the base of the triangle which aligns 
along the X-axis of the default Cartesian coordinate system (label 0). The 

CRGEN

 (Geometry > CURVES > GENERATION MENU > 

Generate

command will be used with a Y-axis offset of T2 as illustrated below. If you 
activate the SNP and PIC icons, you can select entities from the screen using the 
left button of the mouse. Note that you can still use the keyboard.

Geo Panel:

 Geometry > CURVES > GENERATION MENU > 

Generate 

(CRGEN)

Generation number [1] >
Pick/Input Beginning Curve > 

2

Pick/Input Ending Curve > 

2

Increment > 

1

Generation flag > 

Translation

X-Displacement > 

0.0

Y-Displacement > 

T2

Z-Displacement > 

0.0

5.

In order to create lines parallel to the inclined sides of the triangle, you need to 
make use of the local coordinate systems. First, define a local Cartesian 
coordinate system (label 3) with its X-axis aligned with the left inclined side and 
repeat the 

CRGEN

 (Geometry > CURVES > GENERATION MENU > 

Generate

) command as shown below:

Geo Panel:

 Geometry > COORD SYS > 

By 3 Points (CSYS)

CSYS,3,0,3,1,2,

Geo Panel:

 Geometry > CURVES > GENERATION MENU > 

Generate 

(CRGEN)

CRGEN,1,1,1,1,0,0,T1,0,

Next, define another local Cartesian coordinate system (label 4) with its X-axis 
aligned with the right inclined side and repeat the 

CRGEN

 (Geometry > 

CURVES > GENERATION MENU > 

Generate

) command as shown below:

Geo Panel:

 Geometry > COORD SYS > 

By 3 Points (CSYS)

CSYS,4,0,2,3,1,

Geo Panel:

 Geometry > CURVES > GENERATION MENU > 

Generate 

(CRGEN)

CRGEN,1,3,3,1,0,0,T1,0,

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The following figure shows a plot of keypoints and curves generated so far, along 
with the coordinate systems. In the next step, you will find the points of intersection 
of curves 4 through 6 and delete the unwanted segments.

6.

Find the points of intersection of the 
straight lines bounding the inner triangle 
using the 

CRINTCC

 (Geometry > 

CURVES > GENERATION MENU > 

Cr/Cr Intersect

) command and delete the 

unwanted segments using the 

CRDEL

 

(Edit > DELETE > 

Curves

) command:

Geo Panel:

 Geometry > CURVES > 

GENERATION MENU > 

Cr/Cr 

Intersect (CRINTCC)

CRINTCC,4,5,6,1,2,0.00005,
CRINTCC,7,8,8,1,2,0.00005,

Geo Panel:

 Edit > DELETE > 

Curves

CRDEL,5,6,1,
CRDEL,4,10,6,
CRDEL,11,12,1,

The geometry of the control arm is now as 
shown below. Note that the corners of the 
inner triangle will be rounded off using 
fillets. At the corners of the outer triangle, 
you will construct circles and connect them 
to the rest of the geometry using procedures 
similar to the above.

7.

Next, you need to create fillets at the 
sharp corners created by the intersection 
of straight lines with the circles. The 

CRFILLET

 (Geometry > CURVES > 

MANIPULATION MENU > 

Fillet

command is applied as shown below at 
the sharp corners:

Figure 3-10. Construction of the 

Control Arm Geometry

Figure 3-11. Construction of the 

Control Arm Geometry

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Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Fillet 

(CRFILLET)

CRFILLET,10,9,7,0.5,1,0,1E-006,
CRFILLET,12,7,8,0.5,1,0,1E-006,
CRFILLET,14,9,8,0.5,1,0,1E-006,

8.

Define concentric circles at the three corners as shown below:

Geo Panel:

 Geometry > CURVES > CIRCLES > 

Circle in Plane 

(CRPCIRCLE)

CRPCIRCLE,16,1,2,1,360,4,
CRPCIRCLE,20,2,1,1,360,4,
CRPCIRCLE,24,3,20,1,360,4,

Use Auto scale icon

SCALE,0,

Geo Panel:

 Geometry > CURVES > CIRCLES > 

Circle in Plane 

(CRPCIRCLE)

CRPCIRCLE,28,1,2,2,360,6,
CRPCIRCLE,34,2,1,2,360,6,

CRPCIRCLE,40,3,20,2,360,6,

Use Auto scale icon

SCALE,0,

The geometry of the slotted control arm you 
constructed up to this stage is as shown 
below. You need to find the intersection 
points of the straight lines with the circles 
and remove the unwanted segments.

9.

Find the points of intersection of the 
straight lines with the circles using the 

CRINTCC

 (Geometry > CURVES > 

GENERATION MENU 

Cr/Cr Intersect

command and delete the unwanted 
segments using the 

CRDEL

 (Edit > 

DELETE > 

Curves

) command:

Figure 3-12. Construction of the 

Con

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Geo Panel:

 Geometry > CURVES > GENERATION MENU > 

Cr/Cr Intersect (CRINTCC)

CRINTCC,1,29,45,16,2,0.00005,

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,1,49,48,

Geo Panel:

 Geometry > CURVES > GENERATION MENU > 

Cr/Cr Intersect (CRINTCC)

CRINTCC,3,38,40,2,2,0.00005,

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,3,52,49,

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Break 

Near Pt (CRPTBRK)

CRPTBRK,2,37,0,
CRPTBRK,52,43,0,

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,2,53,51,

10.

Smoothen the sharp apices of the control arm using fillets as illustrated below:

Geo Panel:

 Geometry > CURVES > MANIPULATION MENU > 

Fillet 

(CRFILLET)

CRFILLET,53,33,52,1.0,1,0,1E-006,
CRFILLET,54,34,52,1.0,1,0,1E-006,
CRFILLET,55,38,51,1.0,1,0,1E-006,
CRFILLET,56,46,48,1.0,1,0,1E-006,
CRFILLET,57,50,51,1.5,1,0,1E-006,
CRFILLET,58,45,48,1.5,1,0,1E-006,

11.

Delete the remaining unwanted segments as illustrated below:

Geo Panel:

 Edit > DELETE > 

Curves (CRDEL)

CRDEL,28,29,1,
CRDEL,39,49,10,
CRDEL,40,47,7,

With the steps executed so far, the initial geometry of the control arm is now fully 
constructed. The following figure shows a view of the initial geometry. You can 
next proceed to generate the finite element model.

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12.

In order to prepare the initial 
geometry for meshing, execute the 

CT

 (Geometry > CONTOURS > 

Define

) and 

RG

 (Geometry > 

CONTOURS > 

Regions

) commands 

as illustrated below:

Geo Panel:

 Geometry > 

CONTOURS > 

Define (CT)

CT,1,0,1,1,51,0,
CT,2,0,1,1,8,0,
CT,3,0,1,1,22,0,
CT,4,0,1,1,16,0,
CT,5,0,1,1,25,0,

Geo Panel:

 Geometry > 

REGIONS >

 Regions (RG)

RG,1,5,1,2,3,4,5,0,

13.

You will be using triangular 3-node shell elements with an average element size 
of 1 units. The control arm will be held in place at the two bottom openings 
against rotations and translations in all directions (we will also be switching 
back to the default Cartesian global coordinate system at this stage):

Geo Panel:

 Control > ACTIVATE > 

Set Entity (ACTSET)

ACTSET,CS,0,

Geo Panel:

 Propsets > 

Element Group (EGROUP)

EGROUP,1,SHELL3,0,0,0,0,0,0,0,

Geo Panel:

 Propsets > 

Real Constant (RCONST)

RCONST,1,1,1,6,0.3,0,0,0,0,0,

Geo Panel:

 Propsets > 

Material Property (MPROP)

MPROP,1,EX,20.E6,DENS,0.0075,

Geo Panel:

 Meshing > AUTO MESH > 

Regions (MA_RG)

MA_RG,1,1,1,0,1,

Geo Panel:

 LoadsBC > STRUCTURAL > DISPLACEMENT > 

Define Contours (DCT)

DCT,3,ALL,0,4,1,

Figure 3-13. Completed Initial Geometry 

of the Control Arm

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The following figure shows the completed 
finite element mesh of the initial design. 
You need to next execute the analysis to 
compute the first out-of-plane free vibration 
mode.

14.

Before starting the sensitivity study, you 
need to run the analysis once to make 
sure that you did not make any errors in 
modeling or in the required features of 
analysis. Execute the 

R_FREQUENCY

 

(Analysis > FREQUENCY/
BUCKLING > 

Run Frequency

command and use the default options 
from the 

A_FREQUENCY

 

(Analysis > 

FREQUENCY/BUCKLING > 

Frequency Options

) command which 

include the computation of the first mode of vibration using the subspace 
iteration algorithm. Note that it is possible to study the sensitivity of the model’s 
frequency of different modes.

15.

It is a good practice to postprocess 
the results from the preliminary 
design before starting the sensitivity 
study so that you can eliminate any 
modeling errors by inspecting the 
results. The figure below was 
obtained using the 

DEFPLOT

 

(Results > PLOT > 

Deformed 

Shape

) command illustrated as 

follows:

Use Viewing icon to set isometric 

view (XYZ)

Geo Panel:

 Results > PLOT > 

Deformed Shape (DEFPLOT)

Mode shape number > 

1

Figure 3-14. Finite Element Mesh 

of the Initial Design

Figure 3-15. Deformed Shape Plot of the 

Initial Design (First Mode)

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16.

With the successful completion of the initial model, you can now proceed to 
define the sensitivity data. As required, you will define frequency as the 
response quantity:

Geo Panel:

 Analysis> OPTIMIZE/SENSITIVITY> RESPONSE 

QUANTITY> 

Define (SN_RESPDEF)

Response set number > 

1

Type > 

Freq

Mode shape number > 

1

Define the design variables. There are two design variables (T1 and T2) for this 
problem. Each of the design variable needs to be defined separately using the 

DVARDEF

 (Analysis > OPTIMIZE/SENSITIVITY > DESIGN VARIABLES > 

Define

) command. You also need to specify the upper and lower bounds of the 

design variable under this command.

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY > DESIGN VARIABLES 

Define (DVARDEF)

Design variable set number > 

1

Design variable type > 

Shape

Design variable parametric name > 

T1

Design variable lower bound > 

0.5

Design variable upper bound > 

2.5

Accept defaults ...

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY > DESIGN VARIABLES 

Define (DVARDEF)

Design variable set number > 

2

Design variable type > 

Shape

Design variable parametric name > 

T2

Design variable lower bound > 

1.5

Design variable upper bound > 

3.5

Accept defaults ...

Lastly, the 

A_SENSITIV

 (Analysis > OPTIMIZE/SENSITIVITY > SENSITIVITY 

RUN > 

Options

) command is used to specify the sensitivity study options and the 

analysis type:

Geo Panel:

 Analysis > OPTIMIZE/SENSITIVITY > SENSITIVITY RUN > 

Options (A_SENSITIV)

Sensitivity type > 

1 by 1

Number of increment > 

5

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Output print flag > 

On

Echo option flag > 

On

Restart flag > 

Off

Type of analysis > 

Frequency

Now, you can use 

R_SENSITIV

 

(Analysis > OPTIMIZE/SENSITIVITY > 

SENSITIVITY RUN > 

Run Analysis

) command to start the sensitivity study. 

After ten runs, a message “sensitivity study completed” will be displayed.

17.

Use the 

ACTPOST

 

(Results > SET UP > 

Set to Post-Proc

)

,

 

ACTXYPOST

 

Display > XY PLOTS > 

Activate Post-Proc

) and 

XYPLOT

 (Display > XY 

PLOT > 

Plot Curves

) commands to view the variation of the fundamental 

frequency versus the design variable values.

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4-1

4

Numerical Aspects

Introduction

The basic features and procedures for design optimization and sensitivity were 
introduced in Chapter 1 to Chapter 3. These materials are sufficient in most 
situations to perform the design problems.

This chapter is intended for the users who wish to learn more about the 
implementation of the optimizer in OPTSTAR. Many of the methods used in the 
optimizer use numerical parameters to control the convergence, tolerance, and so 
on. Default values are provided for those parameters and in most situations they are 
working perfectly. Nevertheless, the users are allowed to override these constants 
by using appropriate commands.

The material covered in this chapter includes: basic statements of optimization 
problems, function approximation, singular value decomposition, the modified 
feasible direction method, the sequential linear programming method, move limits 
of design variables, constraint trimming, and convergence criteria.

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Basic Statements of Optimization Problems

The basic problem that we consider in OPTSTAR is the minimization of a function 
subject to inequality constraints.

Figure 4-1 shows the 
objective function and 
constraints in the design 
space with two design 
variables. 

It is noted that for a 
maximization problem 
we can always 
transform it to be a 
minimization one by 
multiplying the 
objective function by -1.

 

Function Approximation

The main idea of design optimization presented herein relies on finding a 
mathematical relationship between the objective function or constraints and design 
variables. Such a relationship is generally not known in advance.

OPTSTAR makes use of the existing response (objective function or constraints) at 
a number of points in the design space to construct a polynomial approximation to 
the response at other points. The optimization process is then applied to the 
approximate problem represented by the polynomial approximation. 

Minimize:

Objective function

Subject to:

Side constraints

Behavior constraints

where: X

i

 = i

th

 design variable

Figure 4-1.  Objective Function and Constraints in the 

Design Space with Two Design Variables

X

1

X

1

L

=

X

2

X

2

X

2

U

=

X

2

X

2

L

=

X

1

g

1

(X  ,X   )

g

2

F(X  ,X   ) = Constant

X

1

X

1

U

=

1

2

1

2

(X  ,X   )

1

2

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Linear, quadratic, cubic, or quadratic cross-terms may be selected for the 
polynomial approximation depending on the approximation type. They are as 
follows:

Table  2-1. Approximation Types

For example, if we want to fit the response by the approximation type +1, we need 
N

d

+2 (extra one for quality factor) design sets to start with a linear approximation. 

As the optimization loop number exceeds this value, new design sets are added to 
the linear approximation until it reaches 2N

d

+2. After then, a quadratic approxi-

mation is adopted. The coefficients of the polynomial function are determined by a 
least squares regression.

where:

N

d

= Number of design variables

X

i

 

= i

th

 design variable

a

i

, b

i

, c

ij

, d

i

= Coefficients to be determined

 Flag

Type

-1

Only linear terms 

-2

Only quadratic terms 

-3

Only cubic terms 

0

Automatic determination of approximation type

+1

Start with linear and add quadratic terms if needed 

+2

Start with linear and add quadratic and quadratic cross terms if needed 

+3

Start with linear and add quadratic, quadratic cross terms and cubic terms 

if needed 

1   

=          

2   

+          

3   

+          

4   

+          

5   

+          

OPTSTAR 
(Advanced Modules 
Manual, Part 2, 
page  4-3)

2   

)

(

1   ,

3   

)

(

1   ,

5   

)

(

1   ,

)

3   

(

1   , 2   ,

)

3   ,

4   

(

1   , 2   ,

)

3   , 4   , 5 

(

1   , 2   ,

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Singular Value Decomposition

Singular value decomposition (SVD) is used for regression analysis. It is 
advantageous to use SVD because it can handle:

the mathematical irony that least-squares problems are both overdetermined 
(number of data points greater than number of parameters) and underdetermined 
(ambiguous combinations of parameters exist),

sets of equations that are either singular or very close to singular.

The svd_thr of the 

OP_CONTROL

 command sets the threshold for singular values 

allowed to be non-zero. it is a ratio of the maximum singular value of the matrix. 
The svd_iter of the 

OP_CONTROL

 command controls the maximum number of 

iterations allowed to detect singular values.

The Modified Feasible Direction Method 

Overall Process

After the objective function and constraints are approximated and their gradients 
with respect to the design variables are calculated based on the approximation, we 
are able to solve the approximate optimization problem. One of the algorithms used 
in the optimizer is called the Modified Feasible Direction method (MFD). The 
solving process is iterated until convergence is achieved. 

It is important to distinguish the iteration inside the approximate optimization from 
the loop in the overall optimization process. Figure 4-2 shows the iterative process 
within each optimization loop.

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Figure 4-2. The Modified Feasible Direction Algorithm

Search Direction

In order to make any further improvement in an optimization loop, a new search 
direction must be found that continues to reduce the objective function but keeps 
the design feasible. We seek a usable-feasible search direction, in which:

A usable direction is the one that reduces the objective function, and

A feasible direction is the one that a small move in this direction will not violate 
the constraints. 

q = 0, X   = X

q = q + 1

Evaluate objective 
function F(X  ) and 
behavior constraints 
g  (X  )  

  0   

where  j = 1, 2, . . .,  N   

Identify critical and 
potentially critical 
constraints,  N

Calculate gradient of objective function 
—F(X ) and behavior constraints  

g   (X  ) 

where  k = 1, 2, . . .,  N 

Find a usable-feasible search direction S  

Perform a one-dimensional search 
X    = X       + 

α

 S

 
Check convergence.  If satisfied, go to 9.  
Otherwise, go to 2.

X          = X

1.

2.

3.

4.

5.

6.

7.

8.

9.

M F D 

q

m

m +1

q

i

j

i

c

c

i

k

i

c

q

q

q-1

q

Requirements

Achieved?

No

Yes

Update Geometry 
and Mesh
(if needed) X

(m)
 i

Initial 

Analysis

Postprocessing

Define

m = 1

Optimization Loop

Ge ne ra l Optimiza tion 

• Design Variables
• Objective Function
• Behavior Constraints

X

(1)
 i

Parametric 
Geometry 
and Mesh

Approximate 
Objective Function 
and Constraints

Perform 

Analysis

m = m +1

Improved 
Design

X

(m+1)
 i

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This situation is shown in 
Figure 4-3.

To find the search 
direction, active 
and violated 
constraints have 
to be identified. 
A constraint is 
active if its value 
lies between 
mfd_viol (+ve value) and 
mfd_active 
(-ve value) as defined 
by the command 

OP_CONTROL

. A 

small positive value, 
mfd_viol, is allowed 
before categorizing a 
constraint as violated. If a 
constraint is less than 
mfd_active, it 
is then inactive. 
These conditions 
are displayed in 
Figure 4-4.

Convergence to the Optimum 

The optimizer uses several criteria to decide when to end the iterative search process. 
The criteria are described as the following.

Maximum iterations - The maximum number of iterations (search directions) is 
defined by mfd_ifsrch in the command 

OP_CONTROL

. It is intended to avoid 

excessive computations and the default value, 100, is usually more than enough for 
finding an optimum. 

Changes of objective function - To measure the progress made in the successive 
iterations, one of the following criteria is to be satisfied:

Figure 4-3. Usable-Feasible Search Direction

Figure 4-4.  Tolerances for a Constraint in a 

Two Design Variable Space

X

1

g

j

(X) = mfd_    active

X

2

g

j

( X)   >  0

g

j

(X) = mfd_    viol

g

j

( X)   =  0

g

j

( X)   <  0

X

1

X

2

Usable 
Feasible 
Sector

F(X  , X   ) = Constant

g

2

(X  , X   )

 = 0

g

1

Feasible 
Sector

S

Usable
Sector

2

1

2

1

(X  , X   )

 = 0

2

1

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Part 2   OPSTAR / Optimization

or

where mfd_relobj and mdf_absobj are the specified tolerances defined in the 
command 

OP_CONTROL

. The first criterion, relative change, is an indication of 

convergence if the objective function is large. However, the convergence is 
controlled by the second criterion, absolute change, if the objective function is 
small. The number of successive iterations is defined by mfd_conv in the command 

OP_CONTROL

.

Satisfaction of Kuhn-Tucker Conditions

Besides the previously mentioned criteria, the Kuhn-Tucker conditions necessary 
for optimality must be satisfied. 

Unconstrained problems - The conditions degenerate to the case where the 
gradient of the objective function vanishes:

It is noted that this 
condition is 
necessary but not 
sufficient for 
optimality. To ensure 
a function to be a 
minimum, the 
Hessian matrix 
(second derivatives 
with respect to design 
variables) must be 
positive-definite. 
Also, the optimum is 
in a sense of relative 
optimum rather than global one. In general, the conditions to ensure a global 
minimum can rarely be demonstrated. If a global minimum is intended, the 
designers must restart the optimization process from different initial points to check 
if other solutions are possible. Figure 4-5 shows the relative and global minima in 
the design space.

Figure 4-5. Relative and Global Minima in the Design Space

X

F(X)

1

*

2

*

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Constrained problems - The conditions of optimality are more complex. By using 
the Lagrangian multiplier method, we define the Lagrangian function as the 
following:

where t

j

 is a slack variable which measures how far the j

th

 constraint is from being 

critical. Differentiating the Lagrangian function with respect to all variables we 
obtain the Kuhn-Tucker conditions which are summarized as follows: 

1.

2.

The corresponding 

λ

j

 is zero if a constraint is not active.

The physical interpretation of these conditions is that the sum of the gradient of the 
objective function and the scalars 

λ

j

 times the associated gradients of the active 

constraints must vectorally add to zero as shown in Figure 4-6.

Figure 4-6. Kuhn-Tucker Conditions at a Constrained Optimum

The Kuhn-Tucker conditions are also sufficient for optimality when the number of 
active constraints is equal to the number of design variables. Otherwise, sufficient 
conditions require the second derivatives of the objective function and constraints 
(Hessian matrix) similar to the unconstrained one. If the objective function and all 
of the constraints are convex, the Kuhn-Tucker conditions are also sufficient for 
global optimality. 

(X)

g   (X)

2

X

2

X

1

g

2

(X) = 0

g   (X)

F (X)

g

1

(X) = 0

F (X)

λ

g   (X)

1

1

λ

g   (X)

2

2

1

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Part 2   OPSTAR / Optimization

The Sequential Linear Programming Method

In OPTSTAR, the other algorithm for solving the approximate optimization 
problem is called the Sequential Linear Programming method (SLP). The iterative 
process within each optimization loop is shown in Figure 4-7. In Figure 4-8, linear 
approximations to the objective function and constraints are displayed.

Figure 4-7. The Sequential Linear Programming Method

p = 0, X   = X

p = p + 1

Linearize the problem 
at X       by creating a 
first order Taylor 
Series expansion of the 
objective function and 
retained constraints:

F(X)   = F(X      ) + 

F(X      ) (X - X      )

g  (X) = g  (X      ) + 

g  (X      ) (X - X      )

Use this approximation of optimization instead of the 
original nonlinear functions:

Minimize:    F(X)
Subject to: g  (X) 

 0    and    X     

 X   

 X   

Find an improved design  X   (using the MFD algorithm)

Check feasibility and convergence.  If both of them are 
satisfied, go to 7.  Otherwise, go to step 2.

X         = X

1.

2.

3.

4.

5.

6.

7.

SLP 

p

m

m +1

p

p-1

j

p-1

p-1

p-1

j

p-1

p-1

j

p-1

p

L
 i

j

U
 i

Requirements

Achieved?

No

Yes

Update Geometry 
and Mesh
(if needed) X

(m)
 i

Initial 

Analysis

Postprocessing

Define

m = 1

Optimization Loop

Ge ne ra l Optimiza tion 

• Design Variables
• Objective Function
• Behavior Constraints

X

(1)
 i

Parametric 
Geometry 
and Mesh

Approximate 
Objective Function 
and Constraints

Improved 
Design

X

(m+1)
 i

Perform 

Analysis

m = m +1

i

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Figure 4-8. Linear Approximation to Objective Function and Constraints

The flag slp_iter controls the maximum number of iterations (repeated 
linearization process) and slp_conv controls the number of successive iterations for 
convergence check. Both flags are specified in the command 

OP_CONTROL

.

Move Limits of Design Variables

During the optimization process, each design variable is bounded by its global 
lower and upper limits as shown below:

Within each optimization loop, a percentage change, move limit M

L

, is temporarily 

applied to the current value of design variable such that local bounds are created as:

The physical interpretation of move limits is that the optimizer creates a temporary 
box around the current value of design variable as shown in Figure 4-9.

X

2

X

1

True
Oprimum

Approximate
Optimum

Linear

to  g   (X   )

1

p

Approximation

X

p

g

1

(X)

F(X)

g

2

(X)

Linear

to  g   (X   )

2

p

Approximation

Linear

to  F (X   )

p

Approximation

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Part 2   OPSTAR / Optimization

Figure 4-9. Move Limits of Two Design Variables

The command 

OP_DVMOVE

 controls the initial move limit, its lower and upper 

bounds, M

l

L

 and M

u

L

, and multiplier,

 µ. With these parameters, the move limit for 

a subsequent optimization loop is computed by the following formula:

Constraint Trimming

Most structural optimization problems contain more constraints than what are 
necessary to adequately guide the design. The constraints are filtered such that only 
violated and potentially critical ones are considered in the optimizer to increase the 
computational efficiency. 

To identify what is meant by potentially critical, a trimming (truncation) factor is 
applied to the non-violated constraints by using the command 

OP_CONTRIM

. If the 

normalized value of a particular constraint is below the negative value of the 
trimming factor, then this constraint is temporarily deleted from the critical list. It is 

Behavior 

Constraint

Objective 
Function

X

L

1

X

1

X

U

1

X

U

1

X

1

X

L

1

X

2

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noted that those constraints which are temporarily deleted may become active 
during the subsequent optimization loop, thus may be retained in the critical list 
later. 

Constraints are normalized by using their lower and upper bounds specified by the 
command 

OP_CONDEF

. The original constraint is bounded by:

A pair of normalized constraints with respect to upper and lower bounds are 
bounded by: 

This normalization provides a clear indication for the trimming. For example, a 
normalized constraint with a value +0.4 has violated its bound by 40%; another 
constraint with a value -0.3 is within its bound 30%. If the trimming factor is 0.2, 
then the first constraint will be retained in the critical list, however the second one 
will be deleted. 

Convergence Criteria

Convergence or termination checks are performed at the end of each optimization 
loop. The optimization process continues until either convergence or termination 
occurs. 

The process may be terminated before convergence in two cases:

The number of design sets so far exceeds the maximum number of optimization 
loops specified in the command 

A_OPTIMIZE

,

If the initial design is infeasible and the allowed number of consecutive 
infeasible designs has been exceeded.

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Part 2   OPSTAR / Optimization

The optimization problem is considered converged if all of the following conditions 
are satisfied:

The current design is feasible,

Changes in the objective function F:

- The difference between the current value and the best design so far is less than 

the tolerance 

τF specified in the command 

OP_OBJDEF

,

- The difference between the current value and the previous design is less than 

the tolerance,

- (Optional) The differences between the current value and two previous designs 

are less than the tolerance,

and

Changes in the design variables X

i

:

- The difference between the current value of each design variable and the best 

design so far is less than the respective tolerance 

τ

i

 specified in the command 

DVARDEF

,

- The difference between the current value of each design variable and the 

previous design is less than the respective tolerance,

- (Optional) The differences between the current value of each design variable 

and two previous designs are less than the respective tolerance,

and

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Figure 4-10 shows the convergence plots. 

Figure 4-10. Convergence Plots

References

1.

R. T. Haftka and Z. Gürdal “Elements of Structural Optimization,” Third 
Edition, Kluwer Academic Publishers, 1992.

2.

W. H. Press, B. P. Flannery, S. A. Teukolsky and W. T. Vetterling, “Numerical 
Recipes,” Cambridge University Press, 1986.

3.

G. N. Vanderplaats, “Numerical Optimization techniques for Engineering 
Design with Applications,” McGraw Hill, Inc., 1984.

Objective
Function
(F)

Design 
Set

1

2

3

4

5

6

7

8

9

10

Constraint
Value

Design 
Set

1

2

3

4

5

6

7

8

9

10

Infeasible

F easible

Infeasible

be st

F

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5

Additional Problems

Introduction

This chapter presents additional examples for performing shape and sizing 
optimization and sensitivity in COSMOSM. The input files for these problems 
are available in the “...\Vprobs\Optimization” folder. Where “...” denotes the 
COSMOSM directory. The prefix alphabets for the shape optimization problems 
are OPS, whereas for sizing, they are OPZ. The prefix alphabets for the shape 
sensitivity problems are SNS, whereas for sizing, they are SNZ. Static stress 
analysis is denoted by letters ST, natural frequency analysis by FQ, buckling 
analysis by BK, heat transfer analysis by HT, nonlinear by the letter N, post 
dynamic analysis by D, and fatigue analysis by FT. Multidisciplinary analysis 
examples use a combination of the first alphabets from the above. Note that post 
dynamic and fatigue analyses are categorized to multidisciplinary since they cannot 
run alone. For example, the problem OPSST5 discusses shape optimization 
analysis of a beam under linear static stress analysis; OPZBK2 discusses minimum 
weight of a cantilever subject to buckling constraints; OPSTSB1 addresses thermal, 
static and buckling analysis of a fixed channel for the optimal shape. The following 
tables provide a listing of shape and sizing optimization examples and sensitivity 
with respect to the type of analysis. It is noted that the results may vary in a certain 
range from one platform to another.

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Table  3-1. Dominantly Shape Optimization Problems

Static

OPSST1

Stress analysis of a cantilever bracket 

(see page 5-6).

OPSST2

Stress analysis of a Steering Control Arm 

(see page 5-8).

OPSST3

Stress analysis of a slotted control arm 

(see page 5-9).

OPSST4

Stress analysis of a simply supported beam - line curves 

(see page 5-11).

OPSST5

Stress analysis of a simply supported beam - Bezier curves 

(see page 5-12).

OPSST6

Stress analysis for an engine bearing cap under multiple load cases 

(see page 5-13).

Natural 

Frequency

OPSFQ1

Frequency analysis of a control arm bracket 

(see page 5-14).

Linearized 

Buckling

OPSBK1

Buckling analysis of a C-shape column 

(see page 5-15).

Heat 

Transfer

OPSHT1

Thermal analysis of a circular disk 

(see page 5-17).

OPSHT2

Thermal analysis of a pipe cooling system 

(see page 5-19).

OPSHT3

Thermal analysis of a simplified mechanical part 

(see page 5-21).

OPSHT4

Transient temperature - dependent heat conduction of a slab 

(see page 5-22).

Nonlinear 

Structural

OPSN1

Nonlinear analysis of a thick-walled pipe 

(see page 5-23).

OPSN2

Nonlinear analysis of a rubber circular ring 

(see page 5-24).

Multi-

disciplinary

OPSFS1

Stress and frequency analysis of a bracket 

(see page 5-26).

OPSBS1

Stress and buckling analysis of a C-shape column 

(see page 5-28).

OPSTS1

Stress and thermal analysis of a mechanical part 

(see page 5-30).

OPSTSF1

Thermal, static and frequency analysis of a circular disk 

(see page 5-31).

OPSTSB1

Thermal, Static and buckling analysis of a fixed channel 

(see page 5-33).

OPSTN1

Transient thermal and nonlinear analysis of a cylinder 

(see page 5-35).

OPSFDS1

Harmonic response analysis of a culvert 

(see page 5-37).

OPSFDS2

Random vibration analysis of a lever arm 

(see page 5-39).

OPSFDS3

Response spectrum analysis of a trophy setting on a table 

(see page 5-42).

OPSTNFT1

Fatigue analysis of a nozzle under a cyclic temperature loading 

(see page 5-45).

OPSFDSFT1

Fatigue analysis of a curved pipe under a cyclic pressure loading 

(see page 5-48).

Table  3-2. Sizing Optimization Problems

Static

OPZST1

Minimum volume of a 1-bar truss subject to stress constraint 

(see page 5-52).

OPZST2

Minimum volume of a 1-bar truss subject to displacement constraint 

(see page 5-53).

OPZST3

Minimum volume of a 3-bar statically determinate truss subject to stress constraints 

(see page 5-54).

OPZST4

Minimum weight of a 3-bar statically indeterminate truss - multiple load cases 

(see page 5-55).

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Table  3-2. Sizing Optimization Problems (Continued)

Static

OPZST5

Minimum weight of a 4-bar statically indeterminate truss subject to stress constraints 

(see page 5-56).

OPZST6

Minimum displacement of a cantilever subject to weight constraint - beam elements 

(see page 5-57).

OPZST7

Minimum weight of a cantilever subject to stress constraint - beam elements 

(see page 5-58).

OPZST8

Minimum weight of a cantilever subject to stress constraint - beam elements 

(see page 5-59).

OPZST9

Minimum weight of a cantilever subject to displacement constraint - beam elements 

(see page 5-60).

OPZST10

Minimum stress of a simply supported rectangular plate subject to weight constraint - 
shell elements 

(see page 5-61).

OPZST11

Minimum stress of a simply supported rectangular plate subject to stress constraint - 
shell elements 

(see page 5-62).

OPZST12

Minimum stress of a simply supported rectangular plate subject to displ.t constraint - 
shell elements 

(see page 5-63).

OPZST13

Minimum weight of a cantilever plate subject to stress constraint - quad. continuum 
elements 

(see page 5-64).

OPZST14

Minimum volume of a plate subject to displacement constraint - triangular continuum 
elements 

(see page 5-65).

OPZST15

Minimum volume of a plate subject to stress constraint - triangular continuum elements 

(see page 5-66).

OPZST16

Minimum volume of a plate subject to stress constraint - quadrilateral continuum elements 

(see page 5-67).

OPZST17

Minimum volume of a plate subject to stress constraint - quadrilateral continuum elements 

(see page 5-68).

OPZST18

Minimum weight of a simply supported rectangular plate subject to effective strain 
constraint - shell elements 

(see page 5-69).

OPZST19

Minimum weight of a simply supported rectangular plate subject to strain energy density 
constraint - shell elements 

(see page 5-70).

OPZST20

Minimum volume of a cantilever pipe subject to a stress constraint - pipe radius 

(see page 5-71).

OPZST21

Minimum volume of a cantilever pipe subject to a stress constraint - pipe thickness 

(see page 5-71).

Natural 

Frequency

OPZFQ1

Minimum weight of a cantilever subject to frequency constraint - beam elements 

(see page 5-72).

OPZFQ2

Minimum weight of a cantilever subject to frequency constraint - shell elements 

(see page 5-73).

OPZFQ3

Minimum weight of a pipe cantilever subject to frequency constraint - pipe elements 

(see page 5-74).

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Table  3-2. Sizing Optimization Problems (continued)

Linearized 

Buckling

OPZBK1

Minimum weight of a cantilever subject to buckling load factor constraint - beam elements 

(see page 5-76).

OPZBK2

Minimum weight of a cantilever subject to buckling constraint - shell elements 

(see page 5-77).

OPZBK3

Minimum weight of a cantilever plate subject to buckling constraint - quadrilateral continuum 
elements 

(see page 5-78).

OPZBK4

Minimum weight of a pipe cantilever subject to buckling load factor - pipe elements 

(see page 5-79).

OPZBK5

Maximum buckling load design of a graphite-epoxy laminate 

(see page 5-80).

Multi-

disciplinary

OPZNB1

Snap buckling of a thin hinged cylindrical shell under a central point load 

(see page 5-82).

OPZFDS1

Modal time history analysis of a simply supported shell structure 

(see page 5-83).

Table  3-3. Dominantly Shape Sensitivity Problems

Static

SNSST1

Sensitivity study of a steering control arm in stress analysis 

(see page 5-86).

SNSST2

Sensitivity study of an engine bearing cap in stress analysis under multiple load cases 

(see page 5-87).

Natural 

Frequency

SNSFQ1

Sensitivity study of a control arm bracket in frequency analysis 

(see page 5-88).

Linearized 

Buckling

SNSBK1

Sensitivity study of a C-shape column in buckling analysis 

(see page 5-89).

Heat 

Transfer

SNSHT1

Sensitivity study of a circular disk in heat transfer analysis 

(see page 5-91).

Nonlinear

SNSN1

Sensitivity study of a thick-walled pipe in nonlinear analysis 

(see page 5-93).

Multi-

disciplinary

SNSTSF1

Sensitivity study of a circular disk in thermal, stress and frequency analysis 

(see page 5-94).

SNSTSB1

Sensitivity study of C-shape column in thermal, stress and buckling analysis 

(see page 5-96).

SNSTN1

Sensitivity study of a cylinder in transient thermal and nonlinear analyses 

(see page 5-98).

SNSFDS1

Sensitivity study of a culvert in harmonic response analysis 

(see page 5-98).

SNSFDS2

Sensitivity study of a lever arm in random vibration analysis 

(see page 5-102).

SNSFDS3

Sensitivity study of a trophy in response spectrum analysis 

(see page 5-105).

Table  3-4. Sizing Sensitivity Problems

Static

SNZST1

Global sensitivity of a 2-bar truss: (incremented simultaneously) 

(see page 5-108).

SNZST2

Global sensitivity of a 2-bar truss: design variables incremented one at a time 

(see page 5-109).

SNZST3

Offset sensitivity of a 2-bar truss 

(see page 5-110).

SNZST4

Local sensitivity of a 5-bar truss 

(see page 5-111).

SNZST5

Sensitivity study of a graphite-epoxy laminate 

(see page 5-112).

Nonlinear SNZN1

Sensitivity of a rubber ring to coefficient of friction in nonlinear analysis 

(see page 5-114).

Multi-

disciplinary

SNZNF1A 
SNZNF1B

Sensitivity study of a cantilever beam in linear, nonlinear and frequency analyses 

(see page 5-116).

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Dominantly Shape 
Optimization Problems

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KEYWORDS:

Shape, static analysis, 8-node PLANE2D, minimum volume, and stress constraint.

OPSST1: Stress Analysis 

of a Cantilever Bracket

(see 

page 

5-2).

Note:  All dimensions in milimeters.

ν

100.

0

175.0

dv3

12.

5

25

dv2

dv1

Pressure

12.5

25

12.

5

Y

X

r = 5

r = 5

8 - Node  P LANE 2 D

E le me nt s   ( S iz e   =  4 )

I nit ia l P roble m G e ome t ry

I nit ia l Finit e  E le me nt  Me s h

6

6

6

Thickness
Pressure
E

= 10 mm
= 5 N/mm
= 200,000 N/mm
= 0.3

2

2

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PROBLEM:

Find size and location of the cutout. The bracket thickness is 10 mm, modulus of 
elasticity is 200,000 N/mm

2

 and Poisson's ratio is 0.3. A pressure of 5 N/mm

2

 is 

applied to the top edge of the bracket. The initial values and bounds of design 
variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

DV1
DV2
DV3

10 

 25 

 25

10 

 25 

 25

20 

 50 

 50

19.814
10.0
20.0

2.0
2.0
2.0

Objective Function

Volume

106,794

67,600

0.05 (Ratio)

Constraints

von Mises stress

 94 

 300

311.08

15.0

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KEYWORDS:

Shape, static analysis, TETRA4, minimum volume, and stress constraint.

PROBLEM:

Find thickness of the two shafts and size and location of the cutout. The arm outer 
thickness is 20 mm, modulus of elasticity is 200,000 N/mm

2

, and Poisson's ratio is 

0.3. The initial values and bounds of design variables, constraints and the objective 
function are shown below.

SUMMARY OF RESULTS:

OPSST2: Stress Analysis 

of a Steering Control Arm

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

TR1
TR2
TW
DINT

 24 

 25

 19 

 20

 8 

 8

 6 

 17

8.0
8.0
4.6981
17.00

1.0
1.0
1.0
1.0

Objective Function

Volume

218,870

76,046

0.01 (Ratio)

Constraints

von Mises stress 

 105.35 

 225

218.11

3.0

tr

tw

=  31 N/mm

Y

TE TRA4   E LE ME NTS

X

Z

20

140

20

Internal surfaces 
fixed in all directions

30

tr

1

7

I nit ia l P roble m 

G e ome t ry

I nit ia l Finit e

E le me nt   Me s h

dint

=  2 x 10   N/mm

=  0.3

E

Note:  All dimensions 
in milimeters.

ν

2

2

P

y

2

Y

P

y

5

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-9

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, static analysis, 6-node TRIANG, minimum volume, and stress constraint.

OPSST3: Stress Analysis 

of a Slotted Control Arm

(see 

page 

5-2).

I nit ia l Finit e  E le me nt  Me s h

5

5

5

tr

Fixed

  =  140

1

20

20

10

10

r   = 7

P

Y

6 - Node

Tria ngula r Me s h

=  20 mm

=  2 x 10   N/mm

2

5

=  0.3
=  4 N/mm   
    (Y direction)

Thickness

E

Note:  All dimensions in milimeters.

ν

2

P

I nit ia l P roble m G e ome t ry

2

r  = 30

1

y

Y

y

tr

2

X

t w

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-10

COSMOSM Advanced Modules

PROBLEM:

Find thickness of the two shafts and size and location of the cutout. The arm outer 
thickness is 20 mm, modulus of elasticity is 200,000 N/mm

2

, and Poisson's ratio is 

0.3. The initial values and bounds of design variables, constraints and the objective 
function are shown below.

SUMMARY OF RESULTS:

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

TR1
TR2
TW

 25 

 25

 20 

 20

3.5 

 8 

 8

8.0
8.0
5.8192

1.0
1.0
0.5

Objective Function

Volume

200,347.9

72,047.13

0.00125 (Ratio)

Constraints

von Mises stress 

10 

 90.64 

 225

227.70 

3.0

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-11

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, static analysis, 8-node SOLID, minimum volume, and stress constraint.

PROBLEM:

Find height of the beam at support and middle part. The beam width is 4 in, modulus 
of elasticity is 1E7 psi, and Poisson's ratio is 0.3. Nodal forces of 100 lb are applied 
to the middle part of the beam. The initial values and bounds of design variables, 
constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPSST4: Stress Analysis of a Simply 

Supported Beam – Line Curves

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

D1
D2

0.2 

 6 

 10

0.2 

 6 

 10

1.4442
3.4309

0.098
0.098

Objective Function

Volume

2400

1014.8

0.03 (Ratio)

Constraints

von Mises 1
von Mises 2

 1575.6 

 5000

 1648.2 

 5000 

4949.7
5033.3

49.99
49.99

45"

Cros s  

S e c t ion

45"

10"

D

1

100 lbs/Node

D

2

4"

I nit ia l P roble m G e ome t ry

I nit ia l Finit e  E le me nt  Me s h

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-12

COSMOSM Advanced Modules

KEYWORDS:

Shape, static analysis, 8-node SOLID, minimum volume, and stress constraint.

PROBLEM:

Find heights along the beam span. The beam width is 4 in, modulus of elasticity is 
1E7 psi, and Poisson's ratio is 0.3. Nodal forces of 1000 lb are applied at the mid-
section of the beam. The initial values and bounds of design variables, constraints 
and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPSST5: Stress Analysis of a Simply 

Supported Beam – Bezier Curves

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

D1
D2
D3
D4

0.1 

 6 

 10

0.1 

 6 

 10

0.1 

 6 

 10

0.1 

 6 

 10

4.2882
4.1135
1.8693
1.8858

0.099
0.099
0.099
0.099

Objective Function

Volume

1,440.0

729.42

0.03125 (Ratio)

Constraints

von Mises 1
von Mises 2
von Mises 3
von Mises 4
von Mises 5

 7401.2 

 15000 

 5255.1 

 15000

 2759.7 

 15000

 3409.7

 15000

 7378.1 

 15000

15,124
14,035
15,052
2681.5
15,110

149.99
149.99
149.99
149.99
149.99

4"

20"

20"

D

1

D

2

Cros s  

S e c t ion

D

3

D

4

20"

1,000 lbs/node 

init ia l P roble m G e ome t ry

init ia l Finit e  E le me nt  Me s h

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-13

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, static analysis, TETRA10, multiple load cases, minimum volume, and stress 
constraint.

PROBLEM:

Find size and geometric dimensions of the bearing cap. The bearing cap modulus of 
elasticity is 200,000 N/mm

2

 and Poisson's ratio is 0.30. A horizontal pressure (as 

load case 1) and a vertical pressure (as load case 2) are applied to the internal 
surfaces of the cylindrical hole. The initial values and bounds of design variables, 
constraints and objective function are shown below.

SUMMARY OF RESULTS:

 

OPSST6: Stress Analysis of an Engine 

Bearing Cap Under Multiple Load Cases

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final Value(s)

Tolerance

STAR

FFE

Design Variables

ECCENT
TWEB
HEIGHT
HUMP

50 

 75 

 75

 10 

 10

40 

 70

 70

 15 

 15

50
6.6044
40
6.7424

50
6
40
9.7574

0.25
0.04
0.30
0.14

Objective Function

Volume

69,844.78

21,767

21,450

0.05 (Ratio)

Constraints

von Mises 
stress 

STAR: 0 

 117.4 

FFE: 113.6 

 250 

259.21

261.02

12.50

Fixed

ECCENT

Height

Initial 

P roble m 

Ge ome try

TWEB

Symmetry
Boundary
Conditions

HUMP

1 0 -Node  Te tra Me sh

E

ν

= 2 x 10     N/mm
= 0.30

5

2

Initial Finite

E le me nt  Me sh

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-14

COSMOSM Advanced Modules

KEYWORDS:

Shape, frequency analysis, SHELL3, minimum volume, and frequency constraint.

PROBLEM:

Find size and location of the cutout. The bracket thickness is 0.3 cm, modulus of 
elasticity is 2E7 N/cm

2

, and Poisson's ratio is 0.3. The material mass density is 

0.0075 Kg/cm

3

. T

he initial values and bounds of design variables, constraints and the 

objective function are shown below.

SUMMARY OF RESULTS:

 

OPSFQ1: Frequency Analysis 

of a Control Arm Bracket

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T1
T2

0.5 

 2.5 

 2.5 

1.5 

 3.5 

 3.5

0.6256
1.5

0.02
0.02

Objective Function

Volume

28.473

16.491

0.008 (Ratio)

Constraints

Fundamental frequency

 13.65 

 14

7.9992

0.06

15.

0

1.5

1.0

Y

X

r = 1.0
r = 2.0

1.5

1.0

t

1

t

1

t

2

5.0

5.0

0.5

3 - Node  Tria ngula r

Me s h  ( S iz e   =  1 )

=  0.3 cm
=  2 x 10   N/cm
=  0.30
=  0.0075 Kg/cm

7

2

Thickness
E

Note:  All dimensions in centimeters.

3

ρ

ν

I nit ia l P roble m G e ome t ry

I nit ia l Finit e  E le me nt  Me s h

Fixed

Fixed

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-15

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, buckling analysis, SHELL3, minimum volume, and buckling load factor 
constraint.

OPSBK1: Buckling Analysis 

of a C-shape Column

(see 

page 

5-2).

I nit ia l Finit e  

E le me nt   Me s h

B = 20"

T

2

T

1

A = 6"

C = 3"

Fixed

T

2

T

1

T

2

T

1

h = 120"

0.18h

0.32h

0.32h

0.18h

p = 

5,000 psi

(T   /4)

2

Fillet

I nit ia l P roble m 

G e ome t ry

=  3 in

=  0. 25 in

=  A_ Steel

Element Size

Thickness

Material

S HE LL3

E

=  0.28

ν

=  3 x 10   psi

7

ρ

=  0.73 x 10   lbf sec  /in

-3

2

4

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-16

COSMOSM Advanced Modules

PROBLEM:

Find size of the column cutouts. The cross section thickness is 0.25 in., modulus of 
elasticity is 3E7 psi, and Poisson's ratio is 0.28. A pressure of 5000 psi is applied to 
the column's face. The initial values and bounds of design variables, constraints and 
the objective function are shown below.

Summary of Results:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T1
T2

 5 

 35 

 5 

 12

35.0
11.261

0.34
0.11

Objective Function

Volume

1018.15

745.91

0.01 (Ratio)

Constraints

Buckling load 
factor

1.6 

 2.87 

 10

1.5843

0.02

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-17

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, thermal analysis, SHELL3, minimum volume, and temperature constraint.

OPSHT1: Thermal Analysis 

of a Circular Disk

(see 

page 

5-2).

Initial Finite  E le me nt Me sh

25

10

5

=  2 mm

Thickness

3 - Node   S he ll

Me s h  ( S iz e   =  2 )

10

5

5

5

2

Heat Flux
0.1 W/mm

Heat Flux
0.1 W/mm

2

Convection 0.0005 W/mm   -

°

C

Ambient Temperature 50

°

C

2

Convection 0.0 W/mm   -

°

C

Ambient Temperature 50

°

C

2

10

25

Radius

5

Initial P roble m Ge ome try

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-18

COSMOSM Advanced Modules

PROBLEM:

Find radius of the disk. The disk thickness is 2 mm, and conductivity is 0.57 
W/mm-

°C. A convection of 0.0005 W/mm-°C with an ambient temperature of 50 °C 

is applied to the entire model except for the heat sources. The heat source regions 
(heat flux of 0.1 W/mm

2

) is assumed to have a convection of 0 W/mm

2

-

°C with an 

ambient temperature of 50

°C. The initial values and bounds of design variables, 

constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

Radius

30 

 70 

 70

30.849

1.0

Objective Function

Volume

33,375.56

8566.86

0.0015 (Ratio)

Constraints

Temperature

50 

 77.63 

 140

140.15

1.0

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-19

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, thermal analysis, 8-node SOLID, SHELL4, minimum volume, and 
temperature constraint.

OPSHT2: Thermal Analysis 

of a Pipe Cooling System

(see 

page 

5-2).

T

3

T

3

T

3

T

3

T

3

R4 (thickness of
pipes = 0.2 mm)

T

3

RADD

2

R  = 5

T

1

T

2

T

2

T

2

T

2

H     = 5

1

H     = 7

2

H     = 5

1

H     = 7

2

H     = 7

3

H     = 7

3

H     = 7

3

I nit ia l P roble m G e ome t ry

I nit ia l Finit e  E le me nt  Me s h

1

Cros s   S e c t ion

R

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-20

COSMOSM Advanced Modules

PROBLEM:

Find radii and thicknesses of plates and pipes of the cooling system. The material 
conductivity is 0.57 W/mm-

°C. A convection of 0.0015 W/mm

2

-

°C with an ambient 

temperature of 50

°C is applied to the entire model except for the heat source. The 

heat source region (heat flux of 0.1 W/mm

2

) is assumed to have a convection of 

0 W/mm

2

-

°C with an ambient temperature of 50°C The initial values and bounds of 

design variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

Optimization 

Parameters

Initial Value(s) and Bounds

Final Value(s) 

Toler-

ance

HSTAR

FFE

Design 
Variables

R2 
RADD
R4
T1
T2
T3

13 

 25 

 25

 50 

 50

 3 

 3

 2 

 2

 2 

 2

 2 

 2

13.0
8.0
1.0
1.3246
1.0
1.0

13.0
8.0
1.0
1.3671
1.0
1.0

1.0
1.0
0.1
0.1
0.1
0.1

Optimization 

Parameters

 HSTAR 

FFE

HSTAR

FFE

Toler-

ance

Objective 
Function

Weight

196.436

196.436 37.0046

37.588

0.001 
(Ratio)

Constraints

Temp 1
Temp 2
Temp 3

50 

 77.33 

 100

50 

 76.36 

 100

50 

 50.55 

 100

50 

 77.34 

 100

50 

 76.36 

 100

50 

 50.56 

 70

100.18
98.995
68.317

99.754
98.602
68.264

1.0
1.0
1.0

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-21

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, thermal analysis, TETRA10, minimum volume, and temperature constraint.

PROBLEM:

Find dimensions and thicknesses of the mechanical part. The material conductivity 
is 0.57 W/mm-

°C. A convection of 0.0003 W/mm

2

-

°C with an ambient temperature 

of 50 

°C and a volume heat of 0.02 W/mm

3

 are applied for the entire model. The 

initial values and bounds of design variables, constraints and the objective function 
are shown below.

SUMMARY OF RESULTS:

 

OPSHT3: Thermal Analysis of a 

Simplified Mechanical Part

(see 

page 

5-2).

Optimization 

Parameters

Initial Value(s) and Bounds

Final Value(s) 

Toler-

ance

HSTAR

FFE

Design 
Variables

TW 
H
T

 6 

 6

55 

 100 

 100

 15 

 15

2.434
55.0
3.0

2.4367
55.0
3.0

0.04
0.45
0.12

Optimization 

Parameters

 HSTAR 

FFE

HSTAR

FFE

Toler-

ance

Objective 
Function

Volume

69405.3

69405.3

17030.75 17046.7

0.001 
(Ratio)

Constraints

Temp 125 

 222.5 

 250 125 

 222.27 

 250 123.57

123.44

1.0

TW

H

TW

P la n

T

I nit ia l P roble m 

G e ome t ry

I nit ia l Finit e

E le me nt   Mode l

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-22

COSMOSM Advanced Modules

KEYWORDS:

Shape, transient thermal analysis, temperature-dependent conductivity, PLANE2D, 
minimum volume, and temperature constraint.

PROBLEM:

Find the thickness of an infinitely large slab. The thermal conductivity K is assumed 
to vary linearly with temperature, T

, (K = 2 + 0.01 T BTU/in-s °F). The specific heat 

is constant (C = 8 BTU in/lb-s

2

 

°F). The temperature of the left side is suddenly 

raised to 200 

°F and returns to the initial temperature of 100 °F after 10 seconds. The 

initial values and bounds of design variables, constraints and objective function are 
shown below.

SUMMARY OF RESULTS:

 

OPSHT4: Transient Temperature – 

Dependent Heat Conduction of a Slab

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

H

 20

 20

5.6253

0.15

Objective Function

Volume

20

5.62531

0.01 (Ratio)

Constraints

Temp

 104.71 

 150

151.47

1.50

H

Initial P roble m Ge ome try

Initial Finite  E le me nt Me sh

1.0"

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-23

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, nonlinear analysis, von Mises plasticity, automatic time stepping, 
PLANE2D, minimum volume, and stress constraint.

PROBLEM:

Find the pipe's outer diameter. The modulus of elasticity is 86,666 psi, Poisson's 
ration is 0.3, yield stress is 17.32 psi and tangential modulus is 866 psi. The initial 
values and bounds of design variables, constraints and objective function are shown 
below.

SUMMARY OF RESULTS:

 

OPSN1: Nonlinear Analysis 

of a Thick-walled Pipe

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

ROUT

1.5 

 2

 ≤

 2.5

1.5427

0.01

Objective Function

Volume

2.34716

1.0795

0.01 (Ratio)

Constraints

von Mises stress

 17.396 

 23

23.007

0.23

Rout

Initial P roble m Ge ome try

Rint

Initial Finite  E le me nt Me sh

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-24

COSMOSM Advanced Modules

KEYWORDS:

Shape, nonlinear analysis, rubber, Mooney model, contact, prescribed displacement, 
automatic time stepping, axisymmetric PLANE2D, minimum volume, and stress 
constraint.

OPSN2: Nonlinear Analysis 

of a Rubber Circular Ring

(see 

page 

5-2).

Initial Finite  E le me nt Me sh

0.5615"

0.5615"

0.3475"

Top Steel Plate

Bottom Steel Plate

Initial P roble m Ge ome try

2 R Cross

0.3"

0.3"

0.278"

Rubber Ring

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-25

Part 2   OPSTAR / Optimization

PROBLEM:

Find the cross-section radius of a circular rubber ring squeezed between two parallel 
steel plates. For rubber, the Mooney's constants are 175 and 10 psi and Poisson's 
ratio is 0.49. For steal plates, the Young's modulus is 30 x 10

6

 psi, and Poisson's ratio 

is 0.30. The coefficient of friction is 0.01. The initial values and bounds of design 
variables, constraints and objective function are shown below.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

RCROSS

0.05 

 0.139 

 0.15

0.069462

0.001

Objective Function

Volume (rubber)

0.03

0.00749278

0.01 (Ratio)

Constraints

von Mises stress

 209.218 

 450

453.37

4.5

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-26

COSMOSM Advanced Modules

KEYWORDS:

Shape, static analysis, frequency analysis, multidisciplinary optimization, 8-node 
PLANE2D, minimum volume, stress constraint, and frequency constraint.

OPSFS1: Stress and Frequency 

Analysis of a Bracket

(see 

page 

5-2).

Note:  All dimensions in milimeters.

100.

0

8 - Node  P LANE 2 D

Me s h  ( S iz e   =  4 )

= 10 mm
=  5 N/mm
=  200,000 N/mm

2

2

=  0.3
=  0.00785 gm/mm

Thickness
Pressure
E

175.0

dv3

12.

5

25

dv2

dv1

Pressure

12.5

25

12.

5

Y

X

r = 5

r = 5

I nit ia l P roble m G e ome t ry

I nit ia l Finit e  E le me nt  Me s h

ν

Density

6

6

6

3

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-27

Part 2   OPSTAR / Optimization

PROBLEM:

Find size and location of the cutout. The bracket thickness is 10 mm, modulus of 
elasticity is 200,000 N/mm

2

 and Poisson's ratio is 0.3. A pressure of 5 N/mm

2

 is 

applied to the top edge of the bracket. The material density is 0.00785 gm/mm

3

The 

initial values and bounds of design variables, constraints and the objective function 
are shown below.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

DV1
DV2
DV3

10 

 25 

 25

10 

 25 

 25

20 

 50 

 50

25.0
10.0
22.0

2.0
2.0
2.0

Objective Function

Volume

106,794

76,063.64

0.05 (Ratio)

Constraints

von Mises stress
Fundamental frequency

 94.12 

 300

1.8 

 2.8613 

 3

241.52
1.7978

15.0
0.012

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-28

COSMOSM Advanced Modules

KEYWORDS:

Shape, stress analysis, buckling analysis, multidisciplinary optimization, SHELL3, 
minimum volume, buckling load factor constraint, and stress constraint.

OPSBS1: Stress and Buckling 

Analysis of a C-shape Column

(see 

page 

5-2).

I nit ia l Finit e  

E le me nt   Me s h

B = 20"

T

2

T

1

A = 6"

C = 3"

Fixed

T

2

T

1

T

2

T

1

h = 20"

0.18h

0.32h

0.32h

0.18h

p = 

5,000 psi

(T   /4)

2

Fillet

I nit ia l P roble m 

G e ome t ry

=  3 in

=  0. 25 in

=  A_ Steel

Element Size

Thickness

Material

S HE LL3

E

=  0.28

ν

=  3 x 10   psi

7

ρ

=  0.73 x 10   lbf sec  /in

-3

2

4

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-29

Part 2   OPSTAR / Optimization

PROBLEM:

Find size of the column cutouts. The cross section thickness is 0.25 in., modulus of 
elasticity is 3E7 psi, and Poisson's ratio is 0.28. A pressure of 5000 psi is applied to 
the column's face. The initial values and bounds of design variables, constraints and 
the objective function are shown below.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T1
T2

 5 

 35

 5 

 12

35.0
9.8635

0.34
0.11

Objective Function

Volume

1018.15

780.98

0.01 (Ratio)

Constraints

von Mises stress
Buckling load factor

 8,729 

 22,000

1.8 

 2.87 

 10

19,125
1.8012

220
0.02

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-30

COSMOSM Advanced Modules

KEYWORDS:

Shape, static analysis, thermal analysis, multidisciplinary optimization, TETRA4R, 
minimum volume, temperature constraint, and stress constraint.

PROBLEM:

Find dimensions and thicknesses of the mechanical part. The material conductivity 
is 0.57 W/mm-

°C. A convection of 0.0003 W/mm

2

-

°C with an ambient temperature 

of 50 

°C and a volume heat of 0.02 W/mm

3

-

°C are applied for the entire model. The 

modulus of elasticity is 1E07 N/mm

2

 

and Poisson's ratio is 0.30. The initial values 

and bounds of design variables, constraints and the objective function are shown 
below.

SUMMARY OF RESULTS:

 

OPSTS1: Stress and Thermal 

Analysis of a Mechanical Part

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

TW
H
T

 6 

 6

55 

 100 

 100

 15 

 15

2.4053
55.0
3.0

0.04
0.45
0.12

Objective Function

Volume

69,599.5

17,017.8

0.001 (Ratio)

Constraints

von Mises stress
Temperature

 8752.45 

 9000

125 

 222.658 

 250

6133.8
123.18

20.0
2.0

TW

H

TW

P la n

T

Initial Finite  E le me nt Me sh

Initial P roble m Ge ome try

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-31

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, thermal analysis, static analysis, frequency analysis, multidisciplinary 
optimization, SHELL3, 

TEMPREAD

 command, minimum volume, temperature 

constraint, displacement constraint, and frequency constraint.

OPSTSF1: Thermal, Static and Frequency 

Analysis of a Circular Disk

(see 

page 

5-2).

Initial Finite  E le me nt Me sh

25

10

5

=  2 mm

Thickness

3 - Node   S he ll

Me s h  ( S iz e   =  2 )

10

5

5

5

2

Heat Flux
0.1 W/mm

Heat Flux
0.1 W/mm

2

Convection 0.0005 W/mm   -

°

C

Ambient Temperature 50

°

C

2

Convection 0.0 W/mm   -

°

C

Ambient Temperature 50

°

C

2

10

25

Radius

5

Initial P roble m Ge ome try

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-32

COSMOSM Advanced Modules

PROBLEM:

Find radius of the disk. The disk thickness is 2 mm, and conductivity is 0.57 
W/mm

°C. A convection of 0.0005 W/mm

2

-

°C with an ambient temperature of 50 °C 

is applied to the entire model except for the heat sources. The heat source regions 
(heat flux of 0.1 W/mm

2

) is assumed to have a convection of 0 W/mm

2

-

°C with an 

ambient temperature of 50 

°C. The modulus of elasticity is 200000 N/mm

2

Poisson's ratio is 0.30, coefficient of thermal expansion is 0.13E-4/

°C and material 

density is 0.00785 gm/mm

3

. The initial values and bounds of design variables, 

constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

Radius

30 

 70 

 70

38.859

1.0

Objective Function

Volume

33,251.96

11,955.40

 0.0015 (Ratio)

Constraints

Temperature
Displ. frequency
Displ. frequency

50 

 76.46 

 140

0.09 

 0.166 

 0.17

1.0 

 1.139 

 8

107.39
0.08974
5.28985

1.0
0.0008
0.07

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-33

Part 2   OPSTAR / Optimization

KEYWORDS: 

Shape, thermal analysis, static analysis, buckling analysis, multidisciplinary 
optimization, SHELL3, 

TEMPREAD

 command, minimum volume, buckling load 

factor constraint, and displacement constraint.

OPSTSB1: Thermal, Static and Buckling 

Analysis of a Fixed Channel

(see 

page 

5-2).

I nit ia l Finit e  

E le me nt   Me s h

B = 20"

T

2

T

1

A = 6"

C = 3"

Fixed

T

2

T

1

T

2

T

1

h = 120"

0.18h

0.32h

0.32h

0.18h

(T   /4)

2

Fillet

I nit ia l P roble m 

G e ome t ry

=  3 in

=  0. 25 in

=  A_ Steel

Element Size

Thickness

Material

S HE LL3

E

=  0.28

ν

=  3 x 10   psi

7

ρ

=  0.73 x 10   lbf sec  /in

-3

2

4

Fixed

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-34

COSMOSM Advanced Modules

PROBLEM:

Find size of the channel cutouts. The cross section thickness is 0.25 in, modulus of 
elasticity is 3E7 psi, and Poisson's ratio is 0.28. 

The material conductivity is 6.7E-4 BTU/in/s/

°F. A convection of 0.0001 BTU/sec 

in

2

-

°F with an ambient temperature of 50 °F and a volume heat of 0.005 BTU/sec in

3

 

are applied for the entire model. The material's coefficient of thermal expansion is 
7.4E-6/

°F The initial values and bounds of design variables, constraints and the 

objective function are shown below.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T1
T2

 5 

 35

 5 

 12

17.257
12.00

0.34
0.11

Objective Function

Volume

1018.15

887.157

0.01 (Ratio)

Constraints

Buckling factor
Displacement

1.6 

 1.8432 

 10

0.0 

 0.01102 

 0.018

3.981
0.018179

0.02
0.00018

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-35

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, transient thermal, nonlinear analysis, radiation, convection, heat flux; 
element heat, prescribed temperature, multi-disciplinary optimization, von Mises 
plasticity, Axisymmetric PLANE2D, minimum volume, stress, strain and 
temperature constraints.

PROBLEM:

Find the radius and thickness of a cylinder subject to thermal loads and boundary 
conditions. Steel alloy and Aluminum materials are used. The initial values and 
bounds of design variables, constraints and objective function are shown below.

OPSTN1: Transient Thermal – 

Nonlinear Analysis of a Cylinder

(see 

page 

5-2).

Thick

Initia l Finite  Ele me nt Me sh

Initia l Ge ome try, Loa ds 

a nd Bounda ry C onditions

Thick

ROUT

Temperature = 70

°

 F

Radiation Source 
Emissivity 
View Factor

= 500

°

 F

= 0.9
= 0.8

Ambient
Temperature = 200

°

 F

Firm Coefficient
 = 0.1 BTU /
     (sec in in

°

F)

_

Convection 

Element
Heat
= 0.140625 BTU / 
   (sec in in in)

Heat Flux 
= 0.0125 BTU /
   (sec in in)

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-36

COSMOSM Advanced Modules

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

ROUT
THICK

 12 

 12

0.5 

 2 

 2

5
0.66144

0.07
0.015

Objective Function

Volume

39.999

9.4841

0.01 (Ratio)

Constraints

von Mises 1
von Mises 2
Temp
Effective Strain 1
Effective Strain 2

 44,045 

 50,000

 30,213 

 30,000

350. 

 413.63 

 450

 0.003896 

 0.01

0.0021032 

0.01

38954.81
30152.49
381.429
0.003445
0.001796

500
300
1.0
1 x 10

-4

1 x 10

-4

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-37

Part 2   OPSTAR / Optimization

KEYWORDS:

Frequency analysis, post-dynamic analysis (harmonic response), dynamic stress 
analysis, 4-noded PLANE2D elements, shape optimization, multidisciplinary 
optimization, minimum volume design, frequency, displacement, and stress 
constraints.

Initial Problem Geometry

Initial Finite Element Mesh

OPSFDS1: Harmonic Response 

Analysis of a Culvert

(see 

page 

5-2).

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-38

COSMOSM Advanced Modules

PROBLEM:

Find the radius R and slope s of a culvert. The material constants of the culvert are 
given as: Young’s modulus E = 30E6 psi, Poisson’s ratio 

υ = 0.3, and Density ρ = 1 

lb*sec

2

/in

4

. A harmonic pressure loading with constant amplitude 500 psi within the 

desired range of frequency (1 rad/sec - 400 rad/sec) is applied to the top of the 
culvert. A modal damping 0.015 is assumed for the first 10 modes. The input data 
regarding optimization as well as the converged results are listed in the following 
table. Note that the displacement and stress constraints are defined as the extreme 
values within the desired range of frequency.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

DV1
DV2

20 

 20 

 35

1.3333 

 2 

 2

23.268
1.3333

0.15
6.6667E-3

Objective Function

Volume

2575.5

1954.8

0.01 (ratio)

Constraints

Frequency (1st)
Displacement (Uy)
Stress (von Mises)

 16.179 

 20

 0.0429 

 0.05

 4.6893E4 

 5E4

15.470
0.05021
4.7637E4

0.15
5.E-4
500.

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-39

Part 2   OPSTAR / Optimization

KEYWORDS:

Frequency analysis, post-dynamic analysis (random vibration), dynamic stress 
analysis, 6-noded TRIANG elements, shape optimization, multidisciplinary 
optimization, minimum volume design, frequency, displacement, and stress 
constraints.

OPSFDS2: Random Vibration 

Analysis of a Lever Arm

(see 

page 

5-2).

Initial Problem Geometry

Initial Finite

Element Mesh

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-40

COSMOSM Advanced Modules

Base Excitation versus Frequency Curve

Pressure Loading versus Frequency Curve

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-41

Part 2   OPSTAR / Optimization

PROBLEM:

Find the hyperbolic arc parameter RATIO and thickness T2 of a lever arm. The arm 
is made of A_STEEL and has a uniform thickness 1.0 in. Both harmonic pressure 
loading and base excitation (acceleration) in the y-direction are applied to the 
structure as shown in the figure. A modal damping 3% is assumed for the first 5 
modes. The input data regarding optimization as well as the converged results are 
listed in the following table. Note that the displacement constraint is defined as the 
extreme value of PSD within the desired range of frequency and the stress constraint 
is the extreme value of RMS.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

DV1
DV2

0.5 

 0.5 

 0.75

15 

 40 

 50

0.6325
29.782

2.5E-3
0.35

Objective Function

Volume

2.008E4

1.6078

0.01 (ratio)

Constraints

Frequency (1st)
Displacement (Uy)
Stress (von Mises)

75 

 92.377 

 100

 3.1874E-5 

 3.5E-5

 1.1893E4 

 1.25E4

82.089
2.1262E-5
1.2624E4

0.25
3.5.E-7
125.

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-42

COSMOSM Advanced Modules

KEYWORDS:

Frequency analysis, post-dynamic analysis (time history analysis, response 
spectrum generation, and response spectrum analysis), dynamic stress analysis, 
SHELL4 elements, shape optimization, multidisciplinary optimization, maximum 
volume design, frequency, displacement, and stress constraints.

OPSFDS3: Response Spectrum 

Analysis of a Trophy Setting on a Table

(see 

page 

5-2).

Initial Problem Geometry

Initial Finite Element Mesh

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-43

Part 2   OPSTAR / Optimization

Geometry of a Table

Impulsive Base Excitation (for Table)

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-44

COSMOSM Advanced Modules

PROBLEM:

Find the radii (R2 
and R3) and heights 
(H3 and H4) of a 
trophy which is 
setting on the top 
level of a table at the 
point P. Both 
structures are made 
of A_STEEP. The 
trophy has a 5% 
critical damping. 
This problem is 
solved in three 
steps:

1.

A time history 
analysis of the 
table is performed where an impulsive displacement base excitation in the x-
direction is applied.

2.

A maximum acceleration response spectrum is generated from the previous 
results.

3.

A design optimization of the trophy in the response spectrum analysis is per-
formed where the spectrum generated previously is used to excite the trophy in 
the form of acceleration base excitation. 

The input data regarding optimization as well as the converged results are listed in 
the following table. Note that the displacement and stress constraints are defined as 
the extreme values by using the SRSS mode combination method.

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

DV1
DV2
DV3
DV4

 5 

 8

 10 

 20

 10 

 15

15 

 20 

 25

4.994
20
8
25

0.04
0.12
0.07
0.1

Objective Function

Volume

377.49

1229.75

0.01 (ratio)

Constraints

Frequency (1st)
Displacement (Ux)
Stress (von Mises)

10 

 27.043 

 40

 0.3549 

 0.5

 1.849E4 

 2.5E4

10.935
0.5019
1.9645E4

0.3
0.005
250

Maximum Response Spectrum Generation (for Trophy)

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-45

Part 2   OPSTAR / Optimization

KEYWORDS:

Transient thermal analysis, nonlinear elastoplastic analysis, fatigue analysis, 4-
noded PLANE2D elements, shape optimization, multidisciplinary optimization, 
minimum volume design, fatigue usage factor, displacement, and stress constraints.

OPSTNFT1: Fatigue Analysis of a Nozzle 

Under a Cyclic Temperature Loading

(see 

page 

5-2).

Initial Problem Geometry

Initial Finite Element Mesh

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-46

COSMOSM Advanced Modules

Temperature Variation Cycle

Fatigue Design Curve (S-N Curve)

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-47

Part 2   OPSTAR / Optimization

PROBLEM:

Find the thickness parameters T1, T2, and T3 of a circular nozzle. The material 
constants of the nozzle are given as: Young’s modulus E = 3E7 psi, Poisson’s ratio 

υ =0.3, density ρ = 3E-4 lb*hr

2

/in

4

, yield stress 

σ

y

 = 1E4 psi, tangent modulus E

T

 = 

3E6 psi, coefficient of thermal expansion 

α = 8E-6 1/°F, thermal conductivity K

x

 = 

0.1 BTU/(in*hr*

°F), and specific heat C = 40 BTU*in/(lb*hr

2

*

°F). The convection 

coefficient h and the adjacent ambient temperature T

a

 for the exterior and interior 

surfaces of the nozzle are 1 and 5 BTU/(in

2

*hr*

°F) and 60 and 1 °F, respectively. 

Assuming that the nozzle is exposed to a fluid heat-up condition which is expected 
to occur 5000 times during its service life. One complete cycle of this heat-up 
condition is shown in the figure. The problem is solved in three steps:

1.

A transient thermal analysis is performed with the initial temperature T

0

 equal 

to 60 

°F. The nodal temperatures of the structure are evaluated at each time 

interval 0.01 hours for a total time 0.2 hours.

2.

Applying the nodal temperatures obtained from the transient thermal analysis to 
the structure, a nonlinear elastoplastic analysis is performed. The reference tem-
perature Tref is 60 

°F.

3.

With the stresses obtained from the nonlinear analysis, a fatigue analysis is per-
formed. A specified fatigue design curve (S-N curve) is shown in the figure.

The input data regarding optimization as well as the converged results are listed in 
the following table. Note that the constraints, fatigue usage factor and von Mises 
stress, are estimated at node N on the exterior surface of the nozzle and the resultant 
displacement is defined as the extreme value within the desired range of time (0 - 0.2 
hours).

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s) and 

Bounds

Final 

Value(s)

Tolerance

Design Variable

DV1
DV2
DV3

3 < 5 < 5
1 < 2 < 2
0.25 < 1 < 1

3.0
1.1708
0.25

0.02
0.01
7.5E-3

Objective 
Function

Volume

23.219

12.824

0.01 (ratio)

Constraints

Fatigue Usage Factor
Displacement (Ures)
Stress (von Mises)

0 < 0.1030 < 0.15
0 < 0.01057 < 0.012
0 < 1.1523E4 < 1.5E4

0.1491
0.01144
1.5116E4

1.5E-3
1.2E-4
150

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-48

COSMOSM Advanced Modules

KEYWORDS:

Frequency analysis, post-dynamic analysis (modal time history), dynamic stress 
analysis, fatigue analysis, SHELL4 elements, shape/sizing optimization, 
multidisciplinary optimization, minimum volume design, frequency, fatigue usage 
factor, displacement, and stress constraints.

OPSFDSFT1: Fatigue Analysis of a Curved 

Pipe Under a Cyclic Pressure Loading

(see 

page 

5-2).

Initial Problem Geometry

Initial Finite Element Mesh

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-49

Part 2   OPSTAR / Optimization

Pressure Variation Cycle

Fatigue Design Curve (S-N Curve)

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-50

COSMOSM Advanced Modules

PROBLEM:

Find the dimension parameters CURL, RADIUS, and thickness THICK of a curved 
pipe. The pipe is made of A_STEEL. A varying internal pressure loading is applied 
to the pipe which is expected to occur 10000 and 2000 times during its service life. 
One complete cycle of this loading is shown in the figure. The problem is solved in 
two steps:

1.

A modal time history analysis of the pipe is performed with the prescribed pres-
sure loading. A modal damping 0.05 is assumed for the first 5 modes. The 
responses during a total range of time 0.05 sec are recorded.

2.

With the stresses obtained from the dynamic stress analysis, a fatigue analysis is 
performed. A specified fatigue design curve (S-N curve) is shown in the figure.

The input data regarding optimization as well as the converged results are listed in 
the following table. Note that the constraint, fatigue usage factor, is the extreme 
value among all the nodes and the resultant displacement and von Mises stress are 
defined as the extreme value within the desired range of time (0 - 0.05 sec).

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s) and 

Bounds

Final 

Value(s)

Tolerance

Design Variable

DV1
DV2
DV3

1.5 

 2.5 

 2.5

0.25 

 1 

 1

0.05 

 0.1 

 0.1

1.5
0.25
0.0739

0.01
7.5E-3
5.E-4

Objective Function

Volume

14.930

2.5789

0.01 (ratio)

Constraints

Frequency (1st)
Fatigue Usage Factor
Displacement (U

res

)

Stress (von Mises)

50 

 146.28 

 150

 0.07713 

 0.15

 0.1122 

 0.3

 2.7786E4 

 5E4

50.882
0.1085
0.3012
2.8889E4

1
1.5E-3
3.E-3
500

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-51

Sizing Optimization 
Problems

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-52

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, TRUSS2D, minimum volume, and stress constraint.

PROBLEM:

Find the minimum volume of a 1-bar truss subject to a concentrated force of 10 lb. 
The length of the bar is 1 in. and modulus of elasticity is 5 psi. The initial values and 
bounds of design variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZST1: Minimum Volume of a 1-bar 

Truss Subject to Stress Constraint

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

A1

0.25 

 1.0 

 1.0

0.50005

0.0075

Objective Function

Volume

1.0

0.50005

0.001 (Ratio)

Constraints

Max stress

0.5 

 10 

 20

19.998

0.00001

E = 5 psi

F = 10 lbs

1"

A

1

Finit e   E le me nt   Me s h

P roble m G e ome t ry

Area =

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-53

Part 2   OPSTAR / Optimization

KEYWORDS: 

Sizing, static analysis, TRUSS2D, minimum volume, and displacement constraint.

PROBLEM: 

Find the minimum volume of a 1-truss element subject to a concentrated force of 10 
lb. The length of the bar is 1 in. and modulus of elasticity is 5 psi. The initial values 
and bounds of design variables, constraints and the objective function are shown 
below.

SUMMARY OF RESULTS:

 

OPZST2: Minimum Volume of a 1-bar 

Truss Subject to Displacement Constraint

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

A1

0.25 

 1.0 

 1.0

0.49776

0.0075

Objective Function

Volume

1.0

0.49776

0.001 (Ratio)

Constraints

Max displacement

 2 

 4 

4.018 

0.03

E = 5 psi

F = 10 lbs

1"

A

1

Finit e   E le me nt   Me s h

P roble m G e ome t ry

Area =

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-54

COSMOSM Advanced Modules

KEYWORDS: 

Sizing, static analysis, TRUSS2D, 
minimum volume, and stress 
constraint.

PROBLEM:

Find the minimum volume of a 3-
bar truss subject to a concentrated 
force of 20,000 lb. The modulus of 
elasticity is 1E7 psi. The initial 
values and bounds of design 
variables, constraints and the 
objective function are shown 
below.

SUMMARY OF RESULTS:

 

OPZST3: Minimum Volume of a 3-bar Statically 

Determinate Truss Subject to Stress Constraints

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

A1 = A2
A3

0.50 

 2.0 

 4.0

0.50 

 1.0 

 4.0

0.70394
0.66342

0.001
0.001

Objective Function

Volume

76.5685

33.179 

0.025 (Ratio)

Constraints

σ

x

 1, 2

σ

x

 

3

-15,000 

 7,071 

 20,000

-15,000 

 -10,000 

 20,000

20,090
-15,073

150
150

20,000 lbs

20"

A

3

A

1

A

2

P roble m G e ome t ry

10"

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-55

Part 2   OPSTAR / Optimization

KEYWORDS: 

Sizing, static analysis, TRUSS2D, 
minimum weight, and stress 
constraint, and multiple load cases.

PROBLEM: 

Find the minimum weight of a 3-bar 
truss subject to concentrated forces of 
20,000 lb applied in two distinct load 
cases. The modulus of elasticity is 
1E7 psi. The initial values and bounds 
of design variables, constraints and 
the objective function are shown 
below.

SUMMARY OF RESULTS:

 

OPZST4: Minimum Weight of a 3-bar Statically 

Indeterminate Truss Subject to Stress 

Constraints – Multiple Load Cases

(see 

page 

5-2).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

A1
A2

0.10 

 1.0 

 100

0.10 

 2.0 

 100

0.7147
0.6665

0.01
0.01

Objective Function

Weight

4.8284

2.6881

0.001 (Ratio)

Constraints

σ

x

 

σ

x

 

2

σ

x

 

3

-15000 

 12,612 

 20000

-15000 

 5,224 

 20000

-15000 

 12,612 

 20000

20,025
12,068
20,025

150
150
150

20,000 lbs

(Load Case 1)

10"

A

2

A

1

A

3

10"

P roble m G e ome t ry

20,000 lbs

(Load Case 2)

10"

A

1

=

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-56

COSMOSM Advanced Modules

KEYWORDS: 

Sizing, static analysis, 
TRUSS3D, minimum 
weight, and stress constraint.

PROBLEM: 

Find the minimum weight of 
a 4-bar truss subject to 
concentrated forces in X, Y, 
and Z directions. The 
modulus of elasticity is 1E4 
ksi and the material density 
is 0.10 lb/in

3

. The initial 

values and bounds of design 
variables, constraints and the 
objective function are shown 
below.

SUMMARY OF RESULTS:

 

OPZST5: Minimum Weight of a 

4-bar Statically Indeterminate Truss 

Subject To Stress Constraints

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

A1
A2
A3
A4

0.001 

 1.0 

 2

0.001 

 2.0 

 2

0.001 

 2.0 

 2

0.001 

 1.0 

 2

0.4708
1.7078
1.2976
0.4873

0.001
0.001
0.001
0.001

Objective Function

Weight

101.879

65.2703 

0.001 (Ratio)

Constraints

σ

x

 

1

σ

x

 

2

σ

x

 

3

σ

x

 

4

-25 

 -12.165 

 25

-25 

 -21.360 

 25

-25 

 -16.530 

 25

-25 

 -11.89 

 25

-25.18
-25.163
-25.205
-25.207

0.25
0.25
0.25
0.25

A

1

120"

72"

Y

X

Z

A

2

A

3

A

4

96"

60 K

20 K

10 K

144"

60"

P roble m G e ome t ry

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-57

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static analysis, BEAM2D, minimum displacement, and weight constraint.

PROBLEM:

A cantilever beam is subject to a concentrated load at the tip. Find the beam widths 
(in each half) maintaining a uniform height of the beam. The beam length is 100 in., 
height is 5 in., modulus of elasticity is 1E07 psi, and material density is 0.1 lb/in

3

The initial values and bounds of design variables, constraints and the objective 
function are shown below.

SUMMARY OF RESULTS:

 

OPZST6: Minimum Displacement of a Cantilever 

Subject to Weight Constraint – Beam Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

B1
B2

0.01 

 1.0 

 5

0.01 

 0.25 

 5 

1.4614
0.55234

0.001
0.001

Objective Function

Displacement UY

0.44 

0.2640145

0.001 (Ratio)

Constraints

Weight

 31.25 

 50 

50.344 

0.5

B

1

50"

50"

100

5"

B

2

5"

Finit e  E le me nt  

Me s h

P roble m G e ome t ry

Y

X

Z

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-58

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, BEAM2D, beam width, minimum weight, and stress 
constraint.

PROBLEM:

A cantilever beam is subject to a concentrated load at the tip. Find the beam widths 
(in each half) maintaining a uniform height of the beam. The beam length is 100 in., 
height is 5 in., modulus of elasticity is 1E07 psi, and material density is 0.1 lb/in

3

The initial values and bounds of design variables, constraints and the objective 
function are shown below.

SUMMARY OF RESULTS:

 

OPZST7: Minimum Weight of a Cantilever 

Subject to Stress Constraint – Beam Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

B1
B2

0.01 

 3 

 5 

0.01 

 3 

 5

0.23833 
0.11917

0.001
0.001

Objective Function

Weight

150

8.93745 

0.01 (Ratio)

Constraints

σ

x

 

1

σ

x

 

2

-10000 

 800 

 10000

-10000 

 400 

 10000

10,070
10,070

100
100

1

50"

50"

100

B

5"

B

2

5"

Finit e  E le me nt  

Me s h

P roble m G e ome t ry

Y

X

Z

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-59

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static analysis, BEAM2D, beam height, minimum weight, and stress 
constraint. 

PROBLEM:

A cantilever beam is subject to a concentrated load at the tip. Find the beam heights 
(in each half) maintaining a uniform width of the beam. The beam length is 100 in., 
width is 5 in, modulus of elasticity is 1E07 psi, and material density is 0.1 lb/in

3

. The 

initial values and bounds of design variables, constraints and the objective function 
are shown below.

SUMMARY OF RESULTS:

 

OPZST8: Minimum Weight of a Cantilever 

Subject to Stress Constraint – Beam Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

H1
H2

0.01 

 2 

 10

0.01 

 2 

 10

1.0916
0.7719

0.01
0.01

Objective Function

Weight

 100

46.588

0.001 (Ratio)

Constraints

σ

x

 

1

σ

x

 

2

-10000 

 3000 

 10000

-10000 

 1500 

 10000

10,070
10,070

100
100

5"

5"

H

50"

50"

2

100

1

2

Finit e  E le me nt  

Me s h

P roble m G e ome t ry

Y

X

Z

H

1

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-60

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, BEAM3D, minimum weight, and displacement constraint.

PROBLEM:

A 3D frame is subject to a concentrated load at the tip. Find the frame height and 
width given that width-to-height ratio is equal to the initial ratio. The modulus of 
elasticity is 1E07 psi, and material density is 0.1 lb/in

3

. The initial values and bounds 

of design variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZST9: Minimum Weight of a Frame Subject 

to Displacement Constraint – Beam Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

B
H = 2B

0.1 

 6 

 10 

3.7370
7.4740

0.01

Objective Function

Weight

1080 

418.96

0.001 (Ratio)

Constraints

UY

-0.10 

 -0.01536 

 0.10

-0.1018

0.002

100"

50"

H = 2B

B

Finit e  E le me nt  

Me s h

P roble m G e ome t ry

Y

X

Z

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-61

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static 
analysis, SHELL3, 
bending, minimum 
stress, and weight 
constraint.

PROBLEM:

Find the thickness of 
a 100 x 50 inch plate 
subject to pressure of 
1 psi. The modulus of 
elasticity is 1E07 psi, 
Poisson's ratio is 0.3, 
and material density 
is 0.1 lb/in

3

. The 

initial values and 
bounds of design 
variables, constraints 
and the objective 
function are shown 
below.

SUMMARY OF RESULTS:

 

OPZST10: Minimum Stress of a Simply 

Supported Rectangular Plate Subject 

to Weight Constraint – Shell Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

 0.01 

 0.1 

 1

0.2014

0.001

Objective Function

von Mises stress

132,432 

32,649 

0.001 (Ratio)

Constraints

Weight 0.01 

 50 

 100

100.7

1.0

50"

100"

P = 1 psi

T = Thickness

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-62

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static 
analysis, SHELL3,  
minimum weight, 
and stress constraint.

PROBLEM:

Find the thickness of 
a 100 x 50 inch plate 
subject to pressure of 
1 psi. The modulus 
of elasticity is 1E07 
psi, Poisson's ratio is 
0.3, and material 
density is 0.1 lb/in

3

The initial values 
and bounds of design 
variables, constraints 
and the objective 
function are shown 
below.

SUMMARY OF 
RESULTS:

 

OPZST11: Minimum Weight of a Simply 

Supported Rectangular Plate Subject 

to Stress Constraint – Shell Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

 0.01 

 2 

 2 

0.87877 

0.02

Objective Function

Weight 

1000 

439.388

0.001 (Ratio)

Constraints

von Mises stress

10 

 331.08 

 1700

1714.9 

20.0

50"

100"

P = 1 psi

T = Thickness

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-63

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static analysis, 
SHELL3, bending, 
minimum weight, and 
displacement 
constraint. 

PROBLEM:

Find the thickness of a 
100 x 50 inch plate 
subject to pressure of 
1 psi. The modulus of 
elasticity is 1E07 psi, 
Poisson's ratio is 0.3, 
and material density is 
0.1 lb/in

3

. The initial 

values and bounds of 
design variables, 
constraints and the 
objective function are 
shown below.

SUMMARY OF RESULTS:

 

OPZST12: Minimum Weight of a Simply 

Supported Rectangular Plate Subject to 

Displacement Constraint – Shell Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

 0.01 

 2 

 5 

0.87757

0.01

Objective Function

Weight 

1000 

438.78

0.001 (Ratio)

Constraints

Displacement UZ

-0.10 

 -0.0086 

 0.10

-0.1017

0.002

50"

100"

P = 1 psi

T = Thickness

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-64

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, 8-node PLANE2D, minimum weight, and stress constraint.

PROBLEM:

Find the cantilever plate thickness for each half. The cantilever length is 100 in., 
height is 5 in., modulus of elasticity is 1E07 psi, Poisson's ratio is 0, and material 
density is 0.1 lb/in

3

. The initial values and bounds of design variables, constraints 

and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZST13: Minimum Weight of a Cantilever 

Plate Subject to Stress Constraint – 

Quadrilateral Continuum Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

B1
B2

0.01 

 2 

 2

0.01 

 2 

 2

0.23850
0.11628

0.001
0.001

Objective Function

Weight

100 

8.86944 

0.001 (Ratio)

Constraints

von Mises 1
von Mises 2

-10000 

 1200 

 10,000

-10000 

 600 

 10,000

10,070
10,069

100
100

100 lbs

50"

5"

50"

P roble m G e ome t ry

Finit e   E le me nt   Me s h

1

2

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-65

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static analysis, 3-node TRIANG, minimum weight, and displacement 
constraint.

PROBLEM:

Find the plate thickness. The plate length is 1 inch, height is 1 inch, modulus of 
elasticity is 5 psi, and Poisson's ratio is 0. The initial values and bounds of design 
variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

OPZST14: Minimum Volume of a Plate 

Subject to Displacement Constraint – 

Triangular Continuum Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

0.1 

 1 

 2

0.50025 

0.01

Objective Function

Volume 

1.0

0.50025

0.001 (Ratio)

Constraints

Displacement UX

0.01 

 0.2 

 0.4 

0.3998

0.001

1"

1"

1 ps

i

P roble m G e ome t ry

Finit e   E le me nt   Me s h

T = Thickness

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-66

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, 3-node TRIANG, minimum weight, and stress constraint.

PROBLEM:

Find the plate thickness. The plate length is 1 inch, height is 1 inch, modulus of 
elasticity is 5 psi, and Poisson's ratio is 0. The initial values and bounds of design 
variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZST15: Minimum Volume of a Plate 

Subject to Stress Constraint – 

Triangular Continuum Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

0.1 

 1 

 2

0.499 

0.01

Objective Function

Volume

1.0 

0.499 

0.001 (Ratio)

Constraints

Stress 

σx 

0.1 

 1.0 

 2.0 

2.004 

0.01

1"

1"

1 ps

i

P roble m G e ome t ry

Finit e   E le me nt   Me s h

T = Thickness

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-67

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static analysis, 8-node PLANE2D, minimum volume, and stress constraint.

PROBLEM:

Find the plate thickness for each half. The plate length is 1 inch, height is 1 inch, 
modulus of elasticity is 5 psi, and Poisson's ratio is 0. The initial values and bounds 
of design variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZST16: Minimum Volume of a Plate 

Subject to Stress Constraint – 

Quadrilateral Continuum Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T1 (Thickness)
T2 (Thickness)

0.1 

 2 

 2

0.1 

 1 

 2

1.0034
0.499

0.01
0.01

Objective Function

Volume

1.5

0.7512 

0.001 (Ratio)

Constraints

Stress 

σ

x

 

1

Stress 

σ

x

 

2

-2 

 1.0 

 2

-2 

 1.0 

 2

1.9932
2.004

0.01
0.01

1"

0.5"

1 ps

i

0.5"

Thickness 

T

1

Thickness 

T

2

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-68

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, 4-node PLANE2D, minimum volume, and stress constraint.

PROBLEM:

Find the plate thickness. The plate length is 1 inch, height is 1 inch, modulus of 
elasticity is 5 psi, and Poisson's ratio is 0. The initial values and bounds of design 
variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZST17: Minimum Volume of a Plate 

Subject to Stress Constraint – 

Quadrilateral Continuum Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

0.1 

 1 

 1

0.50126

0.01

Objective Function

Volume

1.0

0.50126 

0.001 (Ratio)

Constraints

von Mises stress

 1.0 

 2.0 

1.995

0.001

1"

1"

1 ps

i

P roble m G e ome t ry

Finit e   E le me nt   Me s h

T = Thickness

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-69

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static analysis, 
SHELL3, bending, 
minimum weight, and 
effective strain 
constraint. 

PROBLEM:

Find the thickness of a 
100 x 50 inch plate 
subject to pressure of 
1 psi. The modulus of 
elasticity is 1E07 psi, 
Poisson's ratio is 0.3, 
and material density is 
0.1 lb/in

3

. The initial 

values and bounds of 
design variables, 
constraints and the 
objective function are 
shown below.

SUMMARY OF RESULTS:

 

OPZST18: Minimum Weight of a Simply 

Supported Rectangular Plate Subject to 

Effective Strain Constraint – Shell Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

0.01 

 2 

 5 

 0.87699

0.01

Objective Function

Weight

1000 

438.495

0.001 (Ratio)

Constraints

Effective Strain

2.0E-5 

 2.47E-5 

 1.28E-4

1.287E-4

1.08E-6

50"

100"

P = 1 psi

T = Thickness

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-70

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, 
SHELL3, bending, 
minimum weight, and 
strain energy density 
constraint.

PROBLEM:

Find the thickness of a 
100 x 50 inch plate 
subject to pressure of 
1 psi. The modulus of 
elasticity is 1E07 psi, 
Poisson's ratio is 0.3, 
and material density 
is 0.1 lb/in

3

. The 

initial values and 
bounds of design 
variables, constraints 
and the objective 
function are shown 
below.

SUMMARY OF RESULTS:

 

OPZST19: Minimum Weight of a Simply 

Supported Rectangular Plate Subject to Strain 

Energy Density Constraint – Shell Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

 0.01 

 2 

 5

0.8771 

0.01

Objective Function

Weight 

1000

438.550 

0.001 (Ratio)

Constraints

Strain Energy Density

 0.0022 

 0.059

0.05941 

0.00059

50"

100"

P = 1 psi

T = Thickness

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-71

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static analysis, PIPE, radius of cross-section, minimum volume, and stress 
constraint.

PROBLEM:

A cantilever pipe is subject to a concentrated load at the tip. Find the pipe radii (in 
each half). The cantilever length is 100 inches, modules of elasticity is 1 x 10

7

 psi, 

and Poisson's ratio is 0.30. The initial values and bounds of design variables, 
objectives function and constraints are shown below.

SUMMARY OF RESULTS:

 

OPZST20: Minimum Volume of a Cantilever Pipe 

Subject to Stress Constraint – Pipe Radius

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

RAVE1
RAVE2

0.5 

 1.6 

 2

0.5 

 1.6 

 2

1.2994
0.9650

0.015
0.015

Objective Function

Volume

231.6925

158.21

0.01 (Ratio)

Constraints

σ

x

1

σ

x

2

-10,000 

 6,302 

 10,000

-10,000 

 3,151 

 10,000

10,100
10,140

200
200

100 

Radius

P roble m Ge ome try

Finite  E le me nt Me sh

Thickness

50"

Average Radius 1

Average Radius 2

50"

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-72

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, PIPE, thickness of cross section, minimum volume, and stress 
constraint.

PROBLEM: 

A cantilever pipe is subject to a concentrated load at the tip. Find the pipe thickness 
(in each half). The cantilever length is 100 inches, modules of elasticity is 1 x 10

7

 

psi, and Poisson's ratio is 0.30. The initial values and bounds of design variables, 
objectives function and constraints are shown below.

SUMMARY OF RESULTS:

 

OPZST21: Minimum Volume of a Cantilever Pipe 

Subject to Stress Constraint – Pipe Thickness

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T1
T2

0.01 

 0.50 

 0.5

0.01 

 0.25 

 0.5

0.1644
0.07497

0.005
0.005

Objective Function

Volume

304.3418

107.68

0.01 (Ratio)

Constraints

σ

x

1

σ

x

2

-10,000 

 4,701 

 10,000

-10,000 

 3,643 

 10,000

10,149
10,170

200
200

50"

T

T

50"

100 

Thickness

P roble m Ge ome try

Finite  E le me nt Me sh

2

1

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-73

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, frequency analysis, BEAM2D, minimum weight, and fundamental 
frequency constraint.

PROBLEM:

Find the height of a cantilever. The beam's length is 100 inches, width is 1 inch, 
modulus of elasticity is 1 x 10

7

 psi and material density is 0.10 lb/in

3

. The initial 

values and bounds of design variables, constraints and the objective function are 
shown below.

SUMMARY OF RESULTS:

 

OPZFQ1: Minimum Weight of a Cantilever Subject 

to Frequency Constraint – Beam Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

H (Height)

0.1 

 10 

 20

4.9109

0.01

Objective Function

Weight 

100

49.109 

0.01 (Ratio)

Constraints

Fundamental 
frequency

0.8 

 1.6135 

 4

0.7924 

0.01

E = 10    psi

100"

7

Cros s

S e c t ion

1"

H

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-74

COSMOSM Advanced Modules

KEYWORDS:

Sizing, frequency analysis, SHELL4, minimum weight, and frequency constraint.

PROBLEM:

Find the cantilever plate thickness. The cantilever length is 100 in, height is 5 in, 
modulus of elasticity is 1 x 10

7

 psi, and material density is 0.1 lb/in

3

. The initial 

values and bounds of design variables, constraints and the objective function are 
shown below.

SUMMARY OF RESULTS:

 

OPZFQ2: Minimum Weight of a Cantilever Subject 

to Frequency Constraint – Shell Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

DV1

0.1 

 2 

 3

0.18494

0.001

Objective Function

Weight 

100

9.24676 

0.01 (Ratio)

Constraints

Fundamental 
frequency

0.03 

 0.3243 

 1 

0.029989

0.0001

100"

5"

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-75

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, frequency analysis, PIPE, radius of cross-section, minimum weight, and 
frequency constraint.

PROBLEM:

Find the pipe radius. The cantilever length is 100 in., modulus of elasticity is 1 x 10

7

 

psi, and material density is 0.1 lb/in

3

. The initial values and bounds of design 

variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZFQ3: Minimum Weight of a Pipe Cantilever 

Subject to Frequency Constraint – Pipe Elements

(see 

page 

5-3).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

R

0.1 

 1.5 

 2

0.57467

0.019

Objective Function

Weight 

21.59846

7.063443

0.01 (Ratio)

Constraints

Fundamental 
frequency 

0.2 

 0.5432 

 2 

0.18381

0.018

100"

P roble m Ge ome try

Finite  E le me nt Me sh

R

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-76

COSMOSM Advanced Modules

KEYWORDS:

Sizing, buckling analysis, BEAM2D, minimum weight, and buckling load factor 
constraint.

PROBLEM:

Find the height of a cantilever beam subject to a concentrated compressive force of 
1000 lb The beam's length is 100 in, width is 5 in, modulus of elasticity is 1 x 10

7

 

psi and material density is 0.10 lb/in

3

. The initial values and bounds of design 

variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZBK1: Minimum Weight of a Cantilever 

Subject to Buckling Load Factor 

Constraint – Beam Elements

(see 

page 

5-4).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

H (Height)

0.1 

 5 

 10 

2.101

 0.001

Objective Function

Weight

50

21.007

0.01 (Ratio)

Constraints

Buckling load factor

 2 

 25.702 

 50

1.9060

0.1

E = 10    psi

F = 1,000 lb

100"

7

P roble m Ge ome try

Finite  E le me nt Me sh

Cros s

S e c t ion

1"

H

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-77

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, buckling analysis, SHELL4, and minimum weight, buckling constraint.

PROBLEM:

Find the cantilever plate thickness. The cantilever length is 100 in, height is 5 in, 
modulus of elasticity is 1 x 10

7

 psi, and material density is 0.1 lb/in

3

. The initial 

values and bounds of design variables, constraints and the objective function are 
shown below.

SUMMARY OF RESULTS:

 

OPZBK2: Minimum Weight of a Cantilever 

Subject to Buckling Constraint – Shell Elements

(see 

page 

5-4).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

0.1 

 2 

 3 

1.2279 

0.001

Objective Function

Weight

100

61.393 

0.01 (Ratio)

Constraints

Buckling load factor

 2 

 8.2604 

 50

1.9115 

0.01

250 
lbs/
Node

100"

5"

P roble m G e ome t ry

Finit e   E le me nt   Me s h

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-78

COSMOSM Advanced Modules

KEYWORDS:

Sizing, buckling analysis, 8-node PLANE2D, minimum weight, and buckling 
constraint. 

PROBLEM:

Find the cantilever plate thickness. The cantilever length is 100 inches, height is 5 
inches, modulus of elasticity is 1 x 10

7

 psi, and material density is 0.1 psi. The initial 

values and bounds of design variables, constraints and the objective function are 
shown below.

SUMMARY OF RESULTS:

 

OPZBK3: Minimum Weight of a Cantilever 

Plate Subject to Buckling Constraint – 

Quadrilateral Continuum Elements

(see 

page 

5-4).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

T (Thickness)

0.1 

 1 

 2

0.13

0.001

Objective Function

Weight

50

6.50

0.001 (Ratio)

Constraints

Buckling load factor

 14.66 

 50

1.906

0.1

250 
lbs/
Node

100"

5"

P roble m Ge ome try

Finite  E le me nt Me sh

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-79

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, buckling analysis, PIPE, radius of cross-section, minimum weight, and 
linearized buckling constraint.

PROBLEM:

Find the pipe radius. The cantilever length is 100 in, modulus of elasticity is 1 x 10

7

 

psi, and material density is 0.1 lb/in

3

. The initial values and bounds of design 

variables, constraints and the objective function are shown below.

SUMMARY OF RESULTS:

 

OPZBK4: Minimum Weight of a Pipe 
Cantilever Subject to Buckling Load 

Constraint – Pipe Elements

(see 

page 

5-4).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

R

0.1 

 1.5 

 2

1.1242

0.019

Objective Function

Weight

21.598

15.696

0.01 (Ratio)

Constraints

Buckling load factor

 5.0732 

 6

1.9624

0.04

100"

1,000 lbs

R

P roble m Ge ome try

Finite  E le me nt Me sh

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-80

COSMOSM Advanced Modules

KEYWORDS:

Buckling analysis, SHELL4L elements, sizing optimization (ply orientation), 
maximum buckling load factor 

λ

cr

.

PROBLEM:

Find the ply orientation 

θ of a 

8-layer [

θ / -θ / θ / - θ]

s

 

Graphite-Epoxy laminated 
composite plate which is 
subject to a uniaxial edge 
pressure loading 1 psi. The 
total thickness of 8 plies is 1 
inch. The material constants 
are given as: modulus of 
elasticity in the first material 
direction E

x

 = 26.27E6 psi, 

modulus of elasticity in the 
second material direction E

y

 = 

1.49E6 psi, Poisson’s ratio 

υ = 

0.28, shear modulus in the 
material first and second plane G

xy

 = 1.04E6 psi, tensile and compressive strengths 

in the first material direction F

1T

 = F

1C

 = 2.17E5 psi, tensile and compressive 

strengths in the second material direction F

2T

 = 5.81E3 psi and F

2C

 = 3.57E4 psi, 

shear strength in the material first and second plane F

12

 = 9.87E3 psi. Four cases are 

studied in which the aspect ratios of the dimension A to B are equal to 1, 2, 3, and 4. 
The input data regarding optimization as well as the converged results are listed in 
the following table. Note that the optimum design is achieved without applying any 
constraint.

OPZBK5: Maximum Buckling Load 

Design of a Graphite-epoxy Laminate

(see 

page 

5-4).

Initial Problem Geometry and Finite Element Mesh

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-81

Part 2   OPSTAR / Optimization

SUMMARY OF RESULTS:

 

A/B

Optimization Parameters

Design Variable, 

θ − 

Objective Function, 

λ

cr

Tolerance

Initial Value(s) and Bounds

Final Value(s)

1

1.E-16 < 30 < 90

45.146

0.9

860.96

948.96

0.01 (ratio)

2

1.E-16 < 30 < 90

41.986

0.9

846.81

1193.0

0.01 (ratio)

3

1.E-16 < 30 < 90

44.985

0.9

965.58

1062.6

0.01 (ratio)

4

1.E-16 < 30 < 90

46.768

0.9

888.42

1126.1

0.01 (ratio)

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-82

COSMOSM Advanced Modules

KEYWORDS: 

Sizing, nonlinear 
analysis, 
linearized 
buckling, snap-
through/snap-
back, arc-length, 
limit point, 
SHELL4, 
minimum 
volume, and 
user-defined 
constraint.

PROBLEM: 

Find the thickness 
of a thin 
cylindrical shell. 
The curved edges of the shell are free while the straight edges are hinged and 
immovable. The modulus of elasticity is 3102.75 N/mm

2

 and Poisson's ratio is 0.3. 

The initial values and bounds of design variables, constraints and objective function 
are shown below.

SUMMARY OF RESULTS:

 

OPZNB1: Snap Buckling of a Thin Hinged 

Cylindrical Shell Under a Central Point Load

(see 

page 

5-4).

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

Thickness

 10 

 10

5.7611

0.10

Objective Function

Volume

6.451412 x 10

5

3.7167E5

0.01 (Ratio)

Constraints

Limit Point Load 
Factor or Linearized 
Buckling Load 
Factor (user-
defined)

50 

 588.39 

 

10,000

49.151

1.0

E

ν

R

b

θ

= 3102.75 N/mm

= 0.30

= 2540 mm

= 254 mm

= 0.10 Rad

2

P = 1.0

Thickness

b

b

R

θ

θ

Finite  Ele me nt 

Me sh

In

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x

In

de

x

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COSMOSM Advanced Modules

5-83

Part 2   OPSTAR / Optimization

KEYWORDS:

Frequency analysis, post-dynamic analysis (time history analysis), dynamic stress 
analysis, SHELL4 elements, sizing optimization, multidisciplinary optimization, 
minimum strain design, frequency and mass constraints.

Initial Problem Geometry

Initial Finite Element Mesh

OPZFDS1: Modal Time History Analysis 

of a Simply Supported Shell Structure

(see 

page 

5-4).

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-84

COSMOSM Advanced Modules

Pressure Loading versus Time Curve

PROBLEM:

Find the thickness t of a simply supported shell structure which is subject to an 
impulsive pressure loading 1 psi. The material constants of the shell are given as: 
Young’s modulus E = 1E7 psi, Poisson’s ratio 

υ = 0.3, and Density ρ = 0.1 lb*sec

2

/

in

4

. The input data regarding optimization as well as the converged results are listed 

in the following table. Note that the objective function, effective strain, is defined as 
the extreme value within the desired range of time (0.0 - 0.6 sec).

SUMMARY OF RESULTS:

 

Optimization Parameters

Initial Value(s)

and Bounds

Final

Value(s)

Tolerance

Design Variables

DV1

0.01 

 0.1 

 1

0.1927

0.001

Objective Function

Effective Strain

5.6057E-4

2.7323E-4

0.01 (Ratio)

Constraints

Frequency (1st)
Mass

 31560 

 10

0.01 

 52.255 

 100.

3.9598
100.70

0.09
1.0

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-85

Dominantly Shape 
Sensitivity Problems

In

de

x

In

de

x

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Chapter 5   Additional Problems

5-86

COSMOSM Advanced Modules

KEYWORDS:

Shape, static analysis, TETRA4, local sensitivity, stress response quantity.

PROBLEM:

Study the sensitivity of the steering control arm to changes in the thickness of the 
shafts, size and location of the cutout. Perform a local sensitivity study by perturbing 
the design variables by a ratio of 0.10. The arm outer thickness is 20 mm, modulus 
of elasticity is 200,000 N/mm

2

 and Poisson's ratio is 0.30

SUMMARY OF RESULTS: 

SNSST1: Sensitivity Study of a Steering 

Control Arm in Linear Stress Analysis

(see 

page 

5-4).

Design 

Variables

Name

Initial
Value

Perturbation

Ratio

Gradient of Maximum

von Mises Stress

1

TR1

24

-0.10

-1.131

2

TR2

19

-0.10

1.1946

3

TW

8

-0.10

-11.324

4

DINT

6

+0.10

4.3820

tr

tw

=  31 N/mm

Y

TE TRA4   E LE ME NTS

X

Z

20

140

20

Internal surfaces 
fixed in all directions

30

tr

1

7

I nit ia l P roble m 

G e ome t ry

I nit ia l Finit e

E le me nt   Me s h

dint

=  2 x 10   N/mm

=  0.3

E

Note:  All dimensions 
in milimeters.

ν

2

2

P

y

2

Y

P

y

5

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-87

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, static analysis, TETRA10, primary and secondary load cases, local 
sensitivity analysis, and stress response quantity.

PROBLEM:

Study the sensitivity of the bearing cap to changes in its dimensions. Perform a local 
sensitivity study by perturbing the design variables by a ratio of 0.10. The bearing 
cap modulus of elasticity is 200,000 N/mm

2

 and Poisson's ratio is 0.30.

SUMMARY OF RESULTS

SNSST2: Sensitivity Study of an Engine 

Bearing Cap in Stress Analysis Under 

Multiple Load Cases

(see 

page 

5-4).

Design Variables

Gradient of Max von Mises Stress

Set 
No.

Name

Initial 
Value

Perturbation

Ratio

Load Case

 1

2

51

1

ECCENT

75

-0.10

0.6238

 1.4428

 1.7547

2

TWEB

10

-0.10

1.7975

-12.318

-14.555

3

HEIGHT

70

-0.10

0.0633

-1.7607

-2.1395

4

HUMP

15

-0.10

0.03275

 0.4751

 1.6491

Fixed

ECCENT

Height

Initial 

P roble m 

Ge ome try

TWEB

Symmetry
Boundary
Conditions

HUMP

1 0 -Node  Te tra Me sh

E

ν

= 2 x 10     N/mm
= 0.30

5

2

Initial Finite

E le me nt  Me sh

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-88

COSMOSM Advanced Modules

KEYWORDS:

Shape, 
frequency 
analysis, 
SHELL3, 
global 
sensitivity, 
frequency 
response 
quantity.

PROB-

LEM:

 

Study the 
sensitivity 
of the 
fundamental
frequency of 
the control arm bracket to changes in design variables. Use the global sensitivity 
option by changing only one design variable at a time in 5 increments. The bracket 
thickness is 0.3 cm, modulus of elasticity is 2 x 10

7

 N/cm

2

 Poisson's ratio is 0.3, and 

mass density is 0.0075 Kg/cm

3

.

SUMMARY OR RESULTS:

SNSFQ1: Sensitivity Study of a Control 

Arm Bracket in Frequency Analysis

(see 

page 

5-4).

Design 

Variables 

Fundamental

 Frequency (Hz)

Design 

Variables 

Fundamental

 Frequency (Hz)

T

1

T

2

T

1

T

2

0.5

3.5

8.6495

2.5

1.5

13.035

1.0

10.798

2.0

13.170

1.5

12.119

2.5

13.329

2.0

13.029

3.0

13.491

2.5

13.662

3.5

13.662

15.

0

1.5

1.0

Y

X

r = 1.0
r = 2.0

1.5

1.0

t

1

t

1

t

2

5.0

5.0

0.5

3 - Node  Tria ngula r

Me s h  ( S iz e   =  1 )

=  0.3 cm
=  2 x 10   N/cm
=  0.30
=  0.0075 Kg/cm

7

2

Thickness
E

Note:  All dimensions in centimeters.

3

ρ

ν

I nit ia l P roble m G e ome t ry

I nit ia l Finit e  E le me nt  Me s h

Fixed

Fixed

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-89

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, linearized buckling analysis, SHELL3, global sensitivity, buckling response 
quantity.

PROBLEM:

Study the sensitivity of the column's buckling load factor to changes in design 
variables. Change the design variables one at a time in 5 increments. The column 
thickness is 0.25 inches, modulus of elasticity is 3 x 10

7

 psi, Poisson's ratio is 0.28, 

and material density is 0.73 x 10

-3

 lb. sec

2

/in

4

.

SNSBK1: Sensitivity Study of a C-shape 
Column in Linearized Buckling Analysis

(see 

page 

5-4).

I nit ia l Finit e  

E le me nt   Me s h

B = 20"

T

2

T

1

A = 6"

C = 3"

Fixed

T

2

T

1

T

2

T

1

h = 120"

0.18h

0.32h

0.32h

0.18h

p = 

5,000 psi

(T   /4)

2

Fillet

I nit ia l P roble m 

G e ome t ry

=  3 in

=  0. 25 in

=  A_ Steel

Element Size

Thickness

Material

S HE LL3

E

=  0.28

ν

=  3 x 10   psi

7

ρ

=  0.73 x 10   lbf sec  /in

-3

2

4

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-90

COSMOSM Advanced Modules

SUMMARY OR RESULTS:

Design Variables 

Linearized Buckling

Load Factor

T

1

T

2

10.00

5

2.8069

16.25

2.7425

22.50

2.6475

28.75

2.5432

35.00

2.4502

10

5.00

2.8069

6.75

2.7630

8.50

2.6785

10.25

2.5992

12.00

2.5103

In

de

x

In

de

x

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COSMOSM Advanced Modules

5-91

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape and sizing, thermal analysis, SHELL3, global sensitivity, temperature 
response quantity.

SNSHT1: Sensitivity Study of a Circular 

Disk in Heat Transfer Analysis

(see 

page 

5-4).

Initial Finite  E le me nt Me sh

25

10

5

=  2 mm

Thickness

3 - Node   S he ll

Me s h  ( S iz e   =  2 )

10

5

5

5

2

Heat Flux
0.1 W/mm

Heat Flux
0.1 W/mm

2

Convection 0.0005 W/mm   -

°

C

Ambient Temperature 50

°

C

2

Convection 0.0 W/mm   -

°

C

Ambient Temperature 50

°

C

2

10

25

Radius

5

Initial P roble m Ge ome try

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-92

COSMOSM Advanced Modules

PROBLEM:

Study the sensitivity of the circular disk temperature to changes in thickness and 
radius of the model. Use the global sensitivity feature and change one design 
variable at a time. The disk conductivity is 0.57 W/mm-

°C. A convection of 0.0005 

W/mm

2

 - 

°C with an ambient temperature of 50°C is applied to the entire model 

except for the heat sources. The heat source regions (heat flux of 0.1 W/mm

2

) is 

assumed to have a convection of 0 W/mm

2

-

°C with an ambient temperature of 50° C.

SUMMARY OR RESULTS:

Design Variables

Temperature

 Radius

Thickness

30

2

144.6651

40

108.324

50

91.6635

60

82.8095

70

77.6308

70

0.500

111.055

0.875

92.2412

1.250

84.5067

1.625

80.2878

2.000

77.6308

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-93

Part 2   OPSTAR / Optimization

KEYWORDS:

Shape, nonlinear analysis, von Mises plasticity, automatic time stepping, 
PLANE2D, global sensitivity, and stress response quantity.

PROBLEM:

Study the sensitivity of the pipe to changes in the outer radius. The modulus of 
elasticity is 86,666 psi, Poisson's ratio is 0.3, yield stress is 17.32 psi and tangential 
modulus is 866 psi. Use the global sensitivity feature for 5 increments.

SUMMARY OF RESULTS:

SNSN1: Sensitivity Study of a Thick 

Walled Pipe in Nonlinear Analysis

(see 

page 

5-4).

Design Variable: 

ROUT

von Mises 

Stress

1.50

25.0516

1.75

17.4911

2.0

17.3962

2.25

17.3580

2.50

17.3420

Rout

Initial P roble m Ge ome try

Rint

Initial Finite  E le me nt Me sh

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-94

COSMOSM Advanced Modules

KEYWORDS:

Shape, thermal analysis, static analysis, frequency analysis, SHELL3, 

TEMPREAD

local sensitivity, temperature, displacement and frequency response quantities.

SNSTSF1: Sensitivity Study of a Circular Disk in 

Thermal, Stress and Frequency Analyses

(see 

page 

5-4).

Initial Finite  E le me nt Me sh

25

10

5

=  2 mm

Thickness

3 - Node   S he ll

Me s h  ( S iz e   =  2 )

10

5

5

5

2

Heat Flux
0.1 W/mm

Heat Flux
0.1 W/mm

2

Convection 0.0005 W/mm   -

°

C

Ambient Temperature 50

°

C

2

Convection 0.0 W/mm   -

°

C

Ambient Temperature 50

°

C

2

10

25

Radius

5

Initial P roble m Ge ome try

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-95

Part 2   OPSTAR / Optimization

PROBLEM:

Study the sensitivity of the circular disk response to changes is its thickness and 
radius. Perform a local sensitivity study by perturbing the design variables by a ratio 
of 0.1. The disk conductivity is 0.57 W/mm-

°C. A convection of 0.0005 W/mm

2

-

°C 

with an ambient temperature of 50

°C is applied to the entire model except for the 

heat sources. The heat source regions (heat flux of 0.1 W/mm-

°C) is assumed to have 

a convection of 0 W/mm

2

-

°C with an ambient temperature of 50°C.

SUMMARY OF RESULTS

Design Variables

Gradient of Response Quantities

Set 
No.

Name

Initial 
Value

Perturbation 

Ratio

Temperature

Resultant 

Displacement

Fundamental 

Frequency

1

Radius

70

-0.10

-0.4415

+0.003120

-0.04806

2

Thickness

1.8

-0.10

-6.3049

-0.01540

+0.5076

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-96

COSMOSM Advanced Modules

KEYWORDS:

Shape, thermal analysis, static analysis, buckling analysis, SHELL3, 

TEMPREAD

global sensitivity, buckling load factor, displacement and temperature response 
quantities.

SNSTSB1: Sensitivity Study of a 

C-shape Column in Thermal, 

Stress and Buckling Analyses

(see 

page 

5-4).

I nit ia l Finit e  

E le me nt   Me s h

B = 20"

T

2

T

1

A = 6"

C = 3"

Fixed

T

2

T

1

T

2

T

1

h = 120"

0.18h

0.32h

0.32h

0.18h

(T   /4)

2

Fillet

I nit ia l P roble m 

G e ome t ry

=  3 in

=  0. 25 in

=  A_ Steel

Element Size

Thickness

Material

S HE LL3

E

=  0.28

ν

=  3 x 10   psi

7

ρ

=  0.73 x 10   lbf sec  /in

-3

2

4

Fixed

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-97

Part 2   OPSTAR / Optimization

PROBLEM:

Study the sensitivity of the C-Shape column to changes in the cutouts sizes. Change 
design variables one at a time in 5 increments. The cross section thickness is 0.25 
inch, modulus of elasticity is 3 x 10

7

 psi, and Poisson's ratio is 0.28. The material 

conductivity is 6.7E-4 BTU/in/s 

°F. A convection of 0.0001 BTU/sec in

2

-

°F with an 

ambient temperature of 50

°F and a volume heat of 0.005 BTU/sec in

3

 are applied for 

the entire model. The material's coefficient of thermal expansion is 7.4E-6/

°F.

SUMMARY OR RESULTS:

Design Variables

Response Quantities

T1

T2

Max Temp

Max Resultant 

Displ.

Buckling 

Load Factor

10.00

5

88.316

0.01299

1.8271

16.25

5

89.275

0.01739

1.7903

22.50

5

90.325

0.02204

1.7771

28.75

5

90.713

0.02327

1.8015

35.00

5

90.939

0.01941

1.8406

10.00

5.00

88.316

0.01299

1.8271

10.00

6.75

89.402

0.01294

2.1557

10.00

8.50

89.321

0.01232

2.5762

10.00

10.25

88.905

0.01235

2.9213

10.00

12.00

89.674

0.01306

3.1636

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-98

COSMOSM Advanced Modules

KEYWORDS:

Shape, transient thermal, nonlinear analysis, radiation, convection, heat flux, 
element heat, prescribed temperatures, multi-disciplinary global sensitivity study, 
von Mises plasticity, Axisymmetric PLANE2D, stress, strain and temperature 
response quantities.

PROBLEM:

Study the sensitivity of a cylinder to changes in its outer diameters and thickness. 
Change the design variables one at a time in 5 increments. Steel alloy and aluminum 
materials are used.

SNSTN1: Sensitivity Study of a Cylinder in 

Intransient Thermal and Nonlinear Analyses

(see 

page 

5-4).

Thick

Initia l Finite  Ele me nt Me sh

Initia l Ge ome try, Loa ds 

a nd Bounda ry C onditions

Thic
k

ROUT

Temperature = 70

°

 F

Radiation Source 
Emissivity 
View Factor

= 500

°

 F

= 0.9
= 0.8

Ambient
Temperature = 200

°

 F

Firm Coefficient
 = 0.1 BTU /
     (sec in in 

°

F)

_

Convection 

Element
Heat
= 0.140625 BTU / 
    (sec in in in)

Heat Flux 
= 0.0125 BTU /
    (sec in in)

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-99

Part 2   OPSTAR / Optimization

SUMMARY OF RESULTS:

Design Variables

Response Quantities

ROUT

Thick

von Mises

Temperature

Eff. Strain 

1

2

1

 2

 5.00

2.000

57,563

31,415

570.292

0.5043E-2

0.4254E-2

 6.75

57,911

30,495

509.935

0.5094E-2

0.3051E-2

 8.50

52,877

30,283

470.377

0.4670E-2

0.2569E-2

10.25

47,987

30,315

439.297

0.4247E-2

0.2536E-2

12.00

44,040

30,217

413.634

0.3896E-2

0.2109E-2

12.00

0.500

22,894

22,724

260.386

0.2025E-2

0.0839E-2

0.875

28,577

27,551

304.249

0.2525E-2

0.1085E-2

1.250

34,039

29,361

345.801

0.3012E-2

0.1371E-2

1.625

39,259

30,130

382.817

0.3472E-2

0.1782E-2

2.000

44,040

30,217

413.634

0.3896E-2

0.2109E-2

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-100

COSMOSM Advanced Modules

KEYWORDS:

Frequency analysis, post-dynamic analysis (harmonic response), dynamic stress 
analysis, 4-noded PLANE2D elements, shape, offset sensitivity, frequency, 
displacement, and stress response quantities.

Initial Problem Geometry

Initial Finite Element Mesh

SNSFDS1: Sensitivity Study of a Culvert 

in Harmonic Response Analysis

(see 

page 

5-4).

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-101

Part 2   OPSTAR / Optimization

PROBLEM:

Study the sensitivity of a culvert due to changes in the design variables, radius R and 
slope s. The material constants of the culvert are given as: Young’s modulus E = 
30E6 psi, Poisson’s ratio 

υ = 0.3, and Density ρ = 1. lb*sec

2

/in

4

. A harmonic 

pressure loading with constant amplitude 500 psi within the desired range of 
frequency (1 rad/sec - 400 rad/sec) is applied to the top of the culvert. A modal 
damping 0.015 is assumed for the first 10 modes. Six sets of design variables and 
their respective results are listed in the following table. Note that the response 
quantities, displacement and stress, are defined as the extreme values within the 
desired range of frequency.

SUMMARY OF RESULTS:

 

Design Variables

Response Quantities

Set 

Number

DV1 

(R)

DV2 

(s)

Frequency 

(1st)

Displacement 

(Uy)

Stress

(von Mises) 

1

20

2.0

16.181

0.0429

4.7188E4

2

23

1.86

14.851

0.0575

5.3807E4

3

26

1.7

13.354

0.0803

6.2323E4

4

29

1.55

11.684

0.1177

8.0398E4

5

32

1.4

9.5110

0.1948

1.2790E5

6

35

1.3333

6.8929

0.4574

2.3871E5

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-102

COSMOSM Advanced Modules

KEYWORDS:

Frequency analysis, post-dynamic analysis (random vibration), dynamic stress 
analysis, 6-noded TRIANG elements, shape, global sensitivity (one-by-one), 
frequency, displacement, and stress response quantities.

SNSFDS2: Sensitivity Study of a Lever 

Arm in Random Vibration Analysis

(see 

page 

5-4).

Initial Problem Geometry

Initial Finite 

Element Mesh

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-103

Part 2   OPSTAR / Optimization

Base Excitation versus Frequency Curve

Pressure Loading versus Frequency Curve

PROBLEM:

Study the sensitivity of a lever arm due to changes in the design variables, hyperbolic 
arc parameter RATIO and thickness T2. The arm is made of A_STEEL and has a 
uniform thickness 1.0 in. Both harmonic pressure loading and base excitation 
(acceleration) in the y-direction are applied to the structure as shown in the figure. 
A modal damping 3% is assumed for the first 5 modes. Changing one design variable 

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-104

COSMOSM Advanced Modules

at a time in 5 increments, their values and the respective results are listed in the 
following table. Note that the response quantity, displacement, is defined as the 
extreme value of PSD within the desired range of frequency and the stress is the 
extreme value of RMS.

SUMMARY OF RESULTS:

 

Design Variables

Response Quantities

DV1

(RATIO)

DV2

(T2)

Frequency

(1st)

Displacement

(U

y

)

Stress

(von Mises) 

0.5

40.0

92.563

3.1740E-4

1.1834E4

0.5625

-

87.351

3.2949E-4

1.2498E4

0.625

-

81.806

3.4710E-4

1.3734E4

0.6875

-

75.813

3.7408E-4

1.5190E4

0.75

-

69.242

4.1664E-4

1.7617E4

0.5

15.0

85.956

2.3235E-4

7710.6 

-

23.75

89.917

1.6545E-4

9111.7

-

32.5

92.059

2.1621E-4

1.1198E4

-

41.25

92.524

3.1188E-4

1.1832E4

-

50.0

91.206

2.2683E-4

1.1321E4

In

de

x

In

de

x

background image

COSMOSM Advanced Modules

5-105

Part 2   OPSTAR / Optimization

KEYWORDS:

Frequency analysis, post-dynamic analysis (response spectrum analysis), dynamic 
stress analysis, SHELL4 elements, shape, local sensitivity, frequency, displacement, 
and stress response quantities.

SNSFDS3: Sensitivity Study of a Trophy 

in Response Spectrum Analysis

(see 

page 

5-4).

Initial Problem Geometry

Initial Finite 

Element Mesh

In

de

x

In

de

x

background image

Chapter 5   Additional Problems

5-106

COSMOSM Advanced Modules

Acceleration Spectrum Excitation

PROBLEM:

Study the sensitivity of a trophy due to changes in its dimensions, R2, R3, H3, and 
H4. The trophy is made of A_STEEL and has a 5% critical damping. The base of the 
trophy is experiencing an acceleration spectrum excitation as shown in the figure. 
Performing a local sensitivity study by perturbing all the design variables by a ratio 
+0.05, the gradients of the response quantities are listed in the following table. Note 
that the response quantities, displacement and stress, are defined as the extreme 
values by using the SRSS mode combination method.

SUMMARY OF RESULTS:

 

Design Variables

Gradients of Response Quantities

Set 
No.

Name

Initial 
Value

Perturbation 

Ratio

Frequency

(1st)

Displacement

(U

x

)

Stress

(von Mises) 

1

R2

5

+0.05

9.8388

-0.0393

-1241.5

2

R3

10

+0.05

-2.4151

9.0626E-3

475.12

3

H3

10

+0.05

-0.4585

4.3791E-4

116.50

4

H4

21

+0.05

-1.1676

8.1406E-3

219.92

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COSMOSM Advanced Modules

5-107

Sizing Sensitivity Problems

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Chapter 5   Additional Problems

5-108

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static analysis, TRUSS2D, global sensitivity.

PROBLEM:

Study the behavior of the 2-bar truss for different values of cross sectional areas A

1

and A

2

. The length of each bar is 30 inches and modulus of elasticity is 5 psi. The 

design variables are to be changed simultaneously in 5 increments.

SUMMARY OF RESULTS:

SNZST1: Global Sensitivity of a 2-bar Truss: All 

Design Variables Incremented Simultaneously

(see 

page 

5-4).

Run 

Number

Design Variables

Response Quantities

A

1

A

2

U

2

U

3

1

1.000

1.000

60.000

120.000

2

3.250

3.250

18.462

36.923

3

5.500

5.500

10.909

21.818

4

7.750

7.750

7.7419

15.484

5

10.000

10.000

6.000

12.000

F = 10 lbs

P roble m Ge ome try

Finite  E le me nt Me sh

30"

A

A

30"

1

2

1

2

3

U

2

U

3

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COSMOSM Advanced Modules

5-109

Part 2   OPSTAR / Optimization

KEYWORDS:

Sizing, static analysis, 
TRUSS2D, global 
sensitivity.

PROBLEM:

Study the behavior of the 
2-bar truss for different 
values of cross sectional 
areas A

1

, and A

2

. The 

length of each bar is 30 
inches and modulus of 
elasticity is 5 psi. The 
design variables are to be 
changed one at a time in 
5 increments.

SUMMARY OF RESULTS:

SNZST2: Global Sensitivity of a 2-bar Truss: 

Design Variables Incremented One at a Time

(see 

page 

5-4).

Run 

Number

Design Variables

Response Quantities

A

1

A

2

U

2

U

3

1

1.0

1.0

60.000

120.000

2

3.25

1.0

18.462

78.462

3

5.50

1.0

10.909

70.909

4

7.75

1.0

7.7419

67.742

5

10.00

1.0

6.000

66.000

6

1.0

1.0

60.000

120.000

7

1.0

3.25

60.000

78.462

8

1.0

5.50

60.000

70.909

9

1.0

7.75

60.000

67.742

10

1.0

10.00

60.000

66.000

F = 10 lbs

P roble m Ge ome try

Finite  E le me nt Me sh

30"

A

A

30"

1

2

1

2

3

U

2

U

3

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Chapter 5   Additional Problems

5-110

COSMOSM Advanced Modules

KEYWORDS:

Sizing, static, TRUSS2D, 
offset sensitivity.

PROBLEM:

Study the behavior of the 
2-bar truss for specified 
values of cross sectional 
areas A

1

, and A

2

. The 

length of each bar is 30 in 
and modulus of elasticity 
is 5 psi. Four different sets 
are used to specify design 
variables.

SUMMARY OF RESULTS:

SNZST3: Offset Sensitivity of a 2-bar Truss

(see 

page 

Set 

Number

Design Variables

Response Quantities

A

1

A

2

U

2

U

3

1

1.0

10.0

60.0

66.0

2

10.0

1.0

6.0

66.0

3

10.0

10.0

6.0

12.0

4

5.0

5.0

12.0

24.0

F = 10 lbs

P roble m Ge ome try

Finite  E le me nt Me sh

30"

A

A

30"

1

2

1

2

3

U

2

U

3

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COSMOSM Advanced Modules

5-111

Part 2   OPSTAR / Optimization

KEYWORDS: 

Sizing, static, 
TRUSS2D, local 
sensitivity.

PROBLEM:

Study the effect of 
changing (perturbing) 
design variables on the 
response of a 5-bar truss. 
The cross-sectional area 
of each bar is 1.0 in, 
length is 10 in (each) and 
modulus of elasticity is 5 
psi. Each design variable 
is perturbed by 10%.

SUMMARY OF RESULTS:

SNZST4: Local Sensitivity of a 5-bar Truss

(see 

page 

Design 

Variable

U

1

*

U

2

*

U

3

*

U

4

*

U

5

*

A1

-18.1818

-18.1818

-18.1818

-18.1818

-18.1818

A2

0.0

-18.1818

-18.1818

-18.1818

-18.1818

A3

0.0

0.0

-18.1818

-18.1818

-18.1818

A4

0.0

0.0

0.0

-18.1818

-18.1818

A5

0.0

0.0

0.0

0.0

-18.1818

*Derivative of Response Quantity with Respect to Design Variables

3

10"

10"

10"

10"

10"

F = 10 lbs

P roble m Ge ome try

Finite  E le me nt Me sh

A

1

1

6

U

2

A

2

A

3

A

A

5

4

2

U

3

U

4

U

5

U

6

4

5

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Chapter 5   Additional Problems

5-112

COSMOSM Advanced Modules

KEYWORDS:

Linear static analysis, SHELL4L elements, size (ply orientation), global sensitivity, 
maximum failure index response quantity.

PROBLEM:

Study the sensitivity of a 6-layer [-

θ / 0 / θ]

s

 Graphite-Epoxy laminate due to changes 

in the ply orientation 

θ. The total thickness of 6 plies is 1 inch. The material 

constants are given as: modulus of elasticity in the first material direction E

x

 = 

26.27E6 psi, modulus of elasticity in the second material direction E

y

 = 1.49E6 psi, 

Poisson’s ratio 

υ = 0.28, shear modulus in the material first-second plane G

xy

 = 

1.04E6 psi, tensile and compressive strengths in the 1st material direction F

1T

 = F

1C

 

= 2.17E5 psi, tensile and compressive strengths in the second material direction F

2T

 

= 5.81E3 psi and F

2C

 = 3.57E4 psi, shear strength in the material first-second plane 

F

12

 = 9.87E3 psi. A biaxial tensile loading is applied to the edges of the structure 

with the ratios of the transverse load (N

y

) to the longitudinal load (N

x

) equal to 0, 

0.5, and 1.0 where N

x

 = 100 psi. Changing the ply orientation in 10 increments, their 

values and the respective maximum failure indexes are listed in the following table.

SNZST5: Sensitivity Study of a 

Graphite-epoxy Laminate

(see 

page 

5-4).

Initial Problem Geometry and Finite Element Mesh

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COSMOSM Advanced Modules

5-113

Part 2   OPSTAR / Optimization

SUMMARY OF RESULTS:

 

Design

Variable, 

q

Response Quantity, 

Maximum Failure Index

N

y

/N

x

 = 0

N

y

/N

x

 = 0.5

N

y

/N

x

 = 1

   1E-16 (=0)

2.1236E-7

7.2160E-3

0.01446

10

-2.3987E-4

6.7899E-3

0.01384

20

-8.2275E-4

5.4160E-3

0.01167

30

-1.2468E-3

3.3621E-3

7.9831E-3

40

-1.0689E-3

1.7210E-3

4.5160E-3

50

7.8222E-4

1.3938E-3

2.6199E-3

60

1.4606E-3

1.6914E-3

1.9231E-3

70

1.8906E-3

2.0304E-3

2.1705E-3

80

2.1198E-3

2.2559E-3

2.3923E-3

90

2.1912E-3

2.3327E-3

2.4743E-3

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Chapter 5   Additional Problems

5-114

COSMOSM Advanced Modules

KEYWORDS:

Shape, nonlinear analysis, rubber, Mooney model, contact, prescribed displacement, 
automatic time stepping, axisymmetric PLANE2D, friction, and stress response 
quantity.

SNZN1: Sensitivity of a Rubber Circular Ring to 

Coefficient of Friction in Nonlinear Analysis

(see 

page 

5-4).

0.5615"

Initial Finite  E le me nt Me sh

0.5615"

0.3475"

Top Steel Plate

Bottom Steel Plate

Initial P roble m Ge ome try

2 R Cross

0.3"

0.3"

0.278"

Rubber Ring

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COSMOSM Advanced Modules

5-115

Part 2   OPSTAR / Optimization

PROBLEM: 

Study the sensitivity of circular ring response to the friction coefficient value. Use 
the global sensitivity option. For rubber, the Mooney's constants are 175 and 10 psi, 
and the Poisson's ratio is 0.49. For steel plates, the Young's modulus is 30 x 10

6

 psi, 

and Poisson's ratio is 0.3.

SUMMARY OF RESULTS:

Design Variable:

FRICTION

von Mises Stress

in Rubber Ring

0.01

209.218

0.05

217.170

0.09

226.550

0.13

233.667

0.17

232.391

0.21

229.952

0.25

230.037

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5-116

COSMOSM Advanced Modules

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COSMOSM Advanced Modules

I-1

Index

A

analysis

1-4

approximations

1-7

arc-length

5-82

automatic time stepping

5-23, 5-

24, 5-93, 5-114

B

beam height

5-59

beam width

5-58

BEAM2D

5-57, 5-58, 5-59, 5-73, 5-

76

BEAM3D

5-60

behavior constraints

1-2, 1-5

bending

5-61, 5-63, 5-69, 5-70

buckling

5-1

buckling response quantity

5-89

C

contact

5-24, 5-114

convection

5-35, 5-98

converged

3-11

convergence

1-7, 3-10, 3-11, 3-32

curves

3-20

D

design optimization

2-1

design variables

1-2, 1-5, 1-8, 2-2–

2-11

displacement constraint

5-31, 5-

33, 5-37, 5-39, 5-42, 5-45, 5-48, 5-
53, 5-57, 
5-60, 5-63, 5-65

displacement response 

quantity

5-94, 5-96, 5-100, 5-102

5-105

E

effective strain constraint

5-69

element heat

5-98

F

failure index response quantity

5-

112

frequency analysis

2-8

frequency constraint

5-14, 5-265-

31, 5-37, 5-39, 5-42, 5-48, 5-73, 5-

74, 5-75, 5-83

frequency response quantity

5-88, 

5-94, 5-100, 5-102, 5-105

friction

5-114

G

global sensitivity

2-8, 5-88, 5-89, 

5-91, 5-93, 5-96, 5-98, 5-102, 5-108, 
5-109, 5-112

H

heat transfer

5-1

L

limit point

5-82

limits

1-8

linearized buckling

5-79, 5-825-

89

local sensitivity

5-86, 5-875-94, 

5-105, 5-111

M

mass constraint

5-83

modified feasible directions

1-7

Mooney model

5-24, 5-114

multidisciplinary design 

optimization

3-6

multidisciplinary optimization

5-

26, 5-28, 5-31, 5-33, 5-37, 5-39, 5-

42, 5-45, 5-48, 5-83

multiple load cases

5-13, 5-55

N

natural frequency

5-1

nonlinear

5-1, 5-23, 5-24, 5-35, 5-

45, 5-82, 5-93, 5-98, 5-114

numerical techniques

1-7

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Index   

I-2

COSMOSM Advanced Modules

O

objective function

1-2, 1-6, 1-8, 2-5

optimization loops

3-5, 3-6, 3-8, 3-

10, 3-11, 3-29, 3-32–3-35

P

PLANE2D

5-6

prescribed displacement

5-24, 5-

114

R

restart

1-7

restore

1-7

S

sensitivity

1-7

shape optimization

5-1

shape sensitivity

5-1

singular value decomposition

1-7

sizing

5-1

static

5-1

stress constraint

5-37, 5-39, 5-42, 5-

61

stress response quantity

5-86, 5-87, 

5-93, 5-100, 5-102, 5-105, 5-114

T

temperature response quantity

5-

91, 5-96

trimming factors

3-10

truncation

3-10

types of sensitivity

2-8

W

weight factors

3-8

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Document Outline