SECTION 4 - MSC Softwarepages.mscsoftware.com/rs/mscsoftware/images/Sec4_Optimization_o… ·...

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Composites Technology Day, February 2012

Copyright 2012 MSC.Software Corporation



SECTION 4

Optimization of Composite Structures

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We are here

Time Agenda: Composites Technology Day with MSC Nastran

9:00-9:15 Welcome

9:15-9:45 Overview of MSC’s Composites Solution

9:45-10:30

Introduction to Analysis of Composites Structures

Hands-on Training

Workshop 1: Stress Analysis of a Composite Wing

10:30-10:45 Break

10:45-12:15

Solid Composite Elements

Hands-on Training

Workshop 2: Solid Shell Composites Modeling

12:15-12:45 Lunch

12:45-2:15

Progressive Ply Failure and Delamination Modeling

Hands-on Training

Workshop 3: Open-Hole-Tension Test Coupon

2:15-2:30 Break

2:30-4:00


Hands-on Training

Workshop 4: Minimizing the Weight of a Composite Wing

4:00-4:30 Curing, Draping, and Direct CAD Interface

4:30-4:45 Feedback/Wrap-up

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Time Agenda: Composites Technology Day with MSC Nastran

9:00-9:15 Welcome

9:15-9:45 Overview of MSC’s Composites Solution

9:45-10:30

Introduction to Analysis of Composites Structures

Hands-on Training

Workshop 1: Stress Analysis of a Composite Wing

10:30-10:45 Break

10:45-12:15

Solid Composite Elements

Hands-on Training

Workshop 2: Solid Shell Composites Modeling

12:15-12:45 Lunch

12:45-2:15

Progressive Ply Failure and Delamination Modeling

Hands-on Training

Workshop 3: Open-Hole-Tension Test Coupon

2:15-2:30 Break

2:30-4:00


Hands-on Training

Workshop 4: Minimizing the Weight of a Composite Wing

4:00-4:30 Curing, Draping, and Direct CAD Interface

4:30-4:45 Feedback/Wrap-up

What is Optimization?

Objective

Design variables

Constraints

Optimization Problem Statement

Maximize your understanding

of composites technology

available from MSC Software

Topical lectures and hands-on

workshops

Limited by the clock and my

own personal understanding

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What is Design Optimization? • Automated modifications of the analysis model parameters to achieve

a desired objective while satisfying specified design requirements

• Design Variables • Element properties (I, J, Area, t, etc.)

• Grid locations (shape optimization)

• Topology (remove structure)

• Objective • Minimize weight

• Minimize Error Function (test/analysis)

• Design Constraints • Direct Response

• Stress Limit, Freq, Disp.

• Derived Response

• Equation

• DESVAR range ( .04<t<.25)

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Optimization in MSC Nastran

• SOL 200 is the solution sequence that performs optimization

• Analysis Types

– Statics

– Normal modes

– Buckling

– Direct complex eigenvalue

– Modal complex eigenvalue

– Direct frequency

– Modal frequency

– Modal transient

– Static aero elasticity

– Aeroelastic flutter

Structural

Optimization

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Gradient Based Numerical Optimization

Optimization

Objective

Structural

Optimization

Constraints

Optimization

Design

Variables

Numerical

Optimizer

Improved

Design

Repeat

And

Refine

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b

h

L

A/b = h /b = -6M/b2h2

A/h = b /h = -12M/bh3

So what is “gradient based” optimization?

• In a nutshell – “go downhill … go

downhill fast …”

• Nastran calculates the sensitivity of

each response to changes in the

design variables

• The Optimizer uses these gradients

(think slopes) to determine which

design variables to change

– Method of Steepest Descent along with

other more efficient methods are used

• Don’t forget about constraints!

– Search direction must be feasible, i.e.,

can’t violate constraints

A constraint on the path

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How do I know it is the “optimal” solution?

• Depends on what “optimal” means

– Out of all possible designs, this one is “the best” - Maybe

– Global max/min? - Maybe

– Local max/min? - Yes

– Improved design? - Yes

• MSC Nastran finds local

minimums

• Several factors influence

which minimum will be

found

– Starting location, step size

both have big effect

– And don’t forget constraints!

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Optimization Applications

• Structural design improvements

– Minimize thickness, hence weight

• Generation of feasible designs from infeasible

designs

– Original model violates stress levels

• Preliminary Design

– Candidate designs from topology optimization

• Model matching to produce similar response

– Frequency response, modal test

• Sensitivity evaluation

– Identify which regions of the model are most

“sensitive” to design changes or imperfections


Copyright 2012 MSC.Software Corporation S4- 11

Composites Optimization

using Patran and MSC Nastran



Set up an Optimization Job

• Pre-Processing – Build the optimization model

– Logical guided workflow

• Post-Processing – Results

– XY Plot



Creating Design Model

• Objective

– Minimize Weight

• Design Variable

– Thickness, Area, etc.

• Constraint

– Allowable deflection, allowable stress, etc.

• Response

– Deflection, Von Mises Stress, Sxy, etc.

• Constraint Set

– Collection of active constraints

• MinMax

– Minimize the max response – frequency response

• Variable Relation

– Linking variables, i.e., think linking ply thicknesses and/or orientations

• Design Study

– Select which variables, constraints, etc. are active



FIRST CREATE DESIGN VARIABLES

a) Tools/Design Study/ Pre-Process

b) Create/Design Variable/ Material

c) Enter Variable Name “ply1_0_thick”

d) Enter Analysis Model Value

“0.0054”

e) Category:

Composite

f) Selected Composites(s)

Select Material Sets

8Ply-symmetric-quasi

g) Select Material Properties

Select ply 1

h) Apply

i) Repeat steps f-h for each additional

ply

Creates Nastran entries:

DESVAR entries, design variables

DVPREL1, DVMREL1, and DVCREL1 relate DESVAR to PSHELL, MAT1, CQUAD4, etc.

a

b

c

d

e

g

f

h

f

g



NEXT CREATE DESIGN OBJECTIVE

Create/Objective

Solution: Global

Response: Weight

Enter Objective Name

Apply

Creates Nastran entries:

DESOBJ(MIN) case

control

DRESP1 bulk data entry



NEXT CREATE DESIGN CONSTRAINT AND

CONSTRAINT SET

a) Create/Constraint

b) Solution: Linear Static

c) Response: Comp. Fail

d) Enter Constraint

Name:

“ply_1_fail_constr”

e) Select Property Set

comp

f) Lower Bound: “-.1”

g) Upper Bound: “1.0”

h) Apply

i) Repeat steps e-h for

each ply

This creates Nastran

entries:

DRESP1

DCONSTR

j) Create/Constraint

Set

k) Solution: Linear

Static

l) Constraint Set

Name: “Comp Fail”

m) Constraints to be

included: select all

n) Apply

a

b

c

d

e

f g

h

j

k

l

m

n



NEXT CREATE DESIGN STUDY – SELECT RESPONSES,

OBJECTIVE, AND CONSTRAINTS

a) Select Responses:

Select All

Close

b) Select Objective:

Click on “Min_Weight”

Close

c) Select Constraints:

Select All

Close

d) Apply

a

a

b

b

c

c

d



a) Analysis

b) Action/Optimize

c) Method/Analysis Deck

d) Job Name/ “sem9”

e) Design Study Select

Select “Comp_Strength”

f) Global Obj/Constr Select:

Min_Weight

g) OK

FINALLY SET UP THE OPTIMIZATION JOB a

d

c

b

e

f

e

f

g



SET UP THE OPTIMIZATION JOB (CONT.)

a) Optimization Parameters

Set parameters as desired

This creates the Nastran

DOPTPRM entry

a




a) Subcases

b) Solution Type: Linear Static

c) Select Untitled.SC1

d) Select

Constraints/Objective

e) Click on Constraint Sets

f) Select “Comp_Failure”

g) OK

h) Apply

i) Cancel

j) Apply

a

b

c

d

e

f

g

h j i




a) Subcase Select

b) Solution Type: Linear Static

c) Make sure it looks something like

this under Subcases Selected

d) OK

e) Apply

a

b

d e

c

c



NASTRAN OPTIMIZATION OUTPUT

.f06 file excerpt

● Review the Design Variable history at the end of the f06 printout.




● Review the Objective and Constraint history in the f06 file.

● A positive constraint value is a failed constraint.




● The convergence condition is also stated.



PATRAN OPTIMIZATION OUTPUT

• If the op2 result file is used (param,post,-1) for optimization post

processing in Patran, then the following plots are available:

– Design variable value versus design cycle XY plot

– Objective value versus design cycle XY plot

– Constraint value versus design cycle XY plot



PATRAN OPTIMIZATION OUTPUT (Cont.)

XY Plot

Post/XY Window

Post/Unpost XY Windows

“Design Variable History”



Repeat for “Maximum Constraint History” and “Objective Function History”





Results:

Create/ Fringe

Select Result Case

“StaticSubcaseD9

Select Fringe

Result

“MaximumIndices”

Apply



Topometry Optimization of Composites

• Topometry Optimization is element-by-element sizing optimization

– Shell thickness

– Rod area

– Bushings, fasteners, etc.

• Because each element is a design variable, it often finds a better

design than conventional property set based optimization

– Why? More design variables …

• Applied to composite laminates allows ply-by-ply element thickness

variation/optimization

• Material distribution is optimized across all elements

0 degree Ply 90 degree Ply +45 degree Ply -45 degree Ply



Example: composite plate with in-plane shear load

• Objective

– Minimize Compliance, aka

maximize Stiffness

• Constraint

– Fractional mass, i.e., final mass

should be ½ of the initial mass

– Effectively this allows for the

selection of a target weight

• Design Variables

– Ply-by-ply element thickness

– 640 elements x 4 plies

– 2560 variables

(0/90/45/-45)s

Final combined thickness distribution



Composite plate topometry optimization results

• Optimal ply placement/distribution

• For this loading and from the perspective of maximizing

stiffness

– 0o plies aren’t necessary

– General placement and coverage of individual plies

– If adding a reinforcing ply

• Choose +/- 45’s or 90’s

• General location and coverage

0 degree Ply 90 degree Ply +45 degree Ply -45 degree Ply



Topometry optimization post-processing

• Optimization results (ply thicknesses) are accessed via

Design Study: Post-Process

• The thickness of each ply is output in files named

<jobname>.ply*




• Visualize ply thickness

– Design Study: Post-Process

– Standard Results Fringe plots




• Optionally, optimized ply coverage may be smoothed to remove

jagged boundaries

• Can be used to

guide general

placement and

coverage of

individual plies



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