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최적화의 최신 트렌드- 다중모델의 동시최적화 (MDO)
2011.07
한국엠에스씨소프트웨어㈜
김정원
목 차
1. 최적화란 무엇인가?
2. 최적화 기법들에 대한 비교검토
3. 다중모델에 대한 동시최적화 기법검토
4. 최적화 업무 적용에 있어서 주의할 사항들
5. 향후 최적화 기술의 발전방향
2
1. 최적화란 무엇인가?
3
Design Optimization이란?
• Design Optimization이란?
• 해석 모델의 자동 수정이다.
• (목적함수를 달성)
• (주어진 설계조건을 유지하면서…)
• 응용분야?
• o 구조설계 개선 (Sizing, Property, Shape, Topology/Topometry/Topogrphy)
• o 현실성 없는 설계로부터 현실성 있는 설계로 변환
• o 구조응답을 동일하게 구현하기 위한 모델변환
• o 시스템의 지배적인 인자 도출
• o 모델구성 평가
• o 민감도 분석
• o 기타 (설계자의 창의적인 구상 검증 등)
4
Design Optimization 개념도?
5
구조응답해석
민감도 해석
FE해석
근사 등가모델 Optimizer
Many Times
Design Cycle
Hard / Soft Convergence?
Design Optimization 의 종류?
6
• Sizing 최적화
• Property 변화
• Topometry (v2008r1부터)지원
• Shape 최적화
• GRID 위치 형상변화
• Topography (v2008r1부터)지원 (Bead Optimization)
• Topology 최적화• 불필요한 부분 제거
• v2007부터 Frequency Response지원
• v2007부터 Transient Response 지원
Other Topics?
7
• Multi-disciplinary Topology?
• Nastran SOL200의 기본제공 기능
• Composite Optimization?
• PCOMPG 지원 (v2008r1부터)
• Global Ply ID – Layer Control (v2008r1부터)
• Topology based sizing & shape Optimization?
• Topology / Topometry / Topography 지원 (v2008r1부터)
• 매우 빠른 속도로 Preliminary Design Optimization수행가능
Nonlinear Optimization?
8
• SOL400 Optimization (MD Nastran v2011 New) – 대변형 최적화
• Bi-directional SOL400_to_SOL200 internal_loop
Design Optimization Results?
9
• Response Improvement
• Input Data Update
Defining The ANALYSIS DISCIPLINES
• Executive Section
SOL 200
• Case Control Section
AcousticsInclude*
Analysis
STATICS Statics
MODES Normal Modes
BUCK Buckling
DFREQ Direct Frequency*
MFREQ Modal Frequency*
MTRAN Modal Transient*
DCEIG Direct Complex Eigenvalue Analysis*
MCEIG Modal Complex Eigenvalue Analysis*
SAERO Static Aeroelasticity
FLUTTER Flutter
10
Graphical Support
• Since Patran 2005r2:– Preprocessing of static and eigenvalue topology optimization
– Preprocessing of global minimum member size
– Smoothing, remesh and generate IGES files for 2D
– Smoothing of 3D topology designs
11
Trust Region – Adaptive Move Limits
• Move limits in SOL 200 approximate optimization can be now adjusted
in an adaptive fashion
• Merit function is a combination of objective function and maximum
violated constraint
• Trust region is ratio of the exact versus the predicted reduction of the
merit function
• Trust region is used to keep, increase, or decrease move limits
• Adjustment of move limits leads to improved quality
of the approximate model
• Should provide more robust optimization results and
faster convergence (fewer design cycles)
• Rejection of bad designs smoothes the design
optimization process
12
Trust Region – ExampleStiffened Panel
-0,2
0,0
0,2
0,4
0,6
0,8
1,0
1,2
1,4
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28
Design Cycle
Maxim
um
Co
nstr
ain
t
MaxCon_nTr
MaxCon_Tr
13
$
PSHELL, 1, 2, 2.5
DESVAR, 1, THICK, 1., 0.1, 10.
DVPREL1, 1, PSHELL, 1, T
1, 2.0
Support of Analysis Model Value Overriding
- Design Model Value
• Example: Design plate thickness
• Leads to .f06 output
Plate thickness defined on PSHELL = 2.5
Design model value = 1. * 2.0 = 2.0
overwrites
analysis model
14
Support of Analysis Model Value Overriding
- Analysis Model Value
• Example: Design plate thickness
• Leads to in .f06
$
PSHELL, 1, 2, 2.5
DESVAR, 1, THICK, 1., 0.1, 10.
DVPREL1, 1, PSHELL, 1, T
1, PVAL
Design value is taken from the 4th entry
of PSHELL
15
SOL200 AESO Creation run
Sample input for an AESO creation run (aeso1.dat)
assign a file name to the assembly run
activate the AESO creation run
DRATIO (optional)
1
1
2 3
2
3
16
SOL200 AESO Assembly Run
Sample of the Assembly File (aeso1_2dat)
17
Dynamic road response optimization of a car
Model Statistics
Random inputs applied on left and right suspension, including cross-correlation
Examples 1 – SOL200 Optimization
Grids 23K
Total DOFs 137K
DOFs in Residual 7K
Elements 37K
Subcases 2
Frequencies 61
Response points 3-4.00E-03
0.00E+00
4.00E-03
8.00E-03
1.20E-02
1.60E-02
4 6 8 10 12 14
FrequencyIn
pu
t S
pectr
a
LEFT SUSP
RIGHT SUSP
REAL L/R
IMAG L/R
Input Power Spectra
18
Design Tasks
Design Variables : spring constant of 9 elastic elements to model
engine mount
Responses : PSD of accelerations at driver’s seat, passenger’s seat
and steering column
Case A: minimize the sum of RMS acceleration at Driver’s seat and
passenger’s seat while limiting the PSD response at steering
column
Case B: minimize the RMS acceleration at Driver’s seat and
maintain frequency dependent limits on driver’s seat
Examples 1 – SOL200 Optimization
19
Examples 1 – Case A : Objective Function– Case B : Design Objective
Sum of RMS
- reduced from 0.154 to 0.130
0.0E+00
1.0E-03
2.0E-03
3.0E-03
4.0E-03
5.0E-03
4 6 8 10 12 14
Frequency (Hz)
Su
mm
ed
Ac
ce
lera
tio
ns
SUM Init
Sum final
20
RMS
- reduced from 0.071 to 0.058
0.0E+00
5.0E-04
1.0E-03
1.5E-03
2.0E-03
2.5E-03
3.0E-03
4 6 8 10 12 14
Frequency (Hz)
Passen
ger A
cceleratio
n
2033 Init
2033 Final
Dynamic Optimization of A car body
Analysis model statistics
207098 grid points
1.24 million DOFs
209079 elements
Design task statistics
Design variables: vary the height and width of some
box cross sections of 183 beam elements
Objective: minimize the structural weight
Constraints: maintaining 1st, 2nd and 3rd modes above given limits.
Examples 2 - SOL200 AESO
Image vehicle model
21
0
100
200
300
400
500
600
700
1 2 3 4 5 6 7 8 9Design Cycle
Clo
ck
Tim
e (
Min
ute
) Total Time (Single Run)
Total Time (AESO)
Examples 2 - AESO Results and Performance
The final objective by AESO matches that of a single shot
run within a relative error of 1%.
Speed up is 4+ fold
22
2. 최적화 기법들에 대한 비교검토
23
Size / Shape Optimization
24
• Sizing 최적화
• Property 변화
• Topometry (v2008r1부터)지원
• Shape 최적화
• GRID 위치 형상변화
• Topography (v2008r1부터)지원 (Bead Optimization)
Topology Optimization
• 새로운 최적화 기법의 효시
• Topology / Topometry / Topography 방법의 기본 알고리즘
• 빠른 시간내에 해석결과를 도출
• 초기 개념 설계에 최적
25
Example: MBB Beam Baseline (Cont.)
$ BASELIN Toppology Optimization / XMY
SOL 200 $ OPTIMIZATION
$ Direct Text Input for Executive Control
CEND
TITLE = MBB BEAM Baseline
ECHO = NONE
$ Direct Text Input for Global Case Control Data
DESGLB = 1
SUBCASE 1
DESOBJ = 1
$ Subcase name : Default
SUBTITLE=Default
SPC = 2
LOAD = 2
ANALYSIS = STATICS
BEGIN BULK
PARAM POST 0
PARAM AUTOSPC YES
PARAM,NOCOMPS,-1
PARAM PRTMAXIM YES
$
DCONSTR 1 2 .5
TOPVAR, 1 , Tshel, Pshell, .5, , , , 1
DRESP1 2 FRMASS FRMASS
DRESP1 1 COMPL COMP
DOPTPRM, DESMAX, 100
INCLUDE 'model.dat'
ENDDATA
Optimization without restriction
26
Example: MBB Beam Baseline (Cont.)
Desmax
default
27
Example: MBB Beam - Minimum Member Size
$ Toppology Optimization with Minimum Size Control Example 1/ XMY
SOL 200 $ OPTIMIZATION
CEND
TITLE = MBB BEAM Minimum Member Size (global)
ECHO = NONE
$ Direct Text Input for Global Case Control Data
DESGLB = 1
SUBCASE 1
DESOBJ = 1
$ Subcase name : Default
SUBTITLE=Default
SPC = 2
LOAD = 2
ANALYSIS = STATICS
BEGIN BULK
PARAM POST 0
PARAM AUTOSPC YES
PARAM,NOCOMPS,-1
PARAM PRTMAXIM YES
$
DOPTPRM, TDMIN, 0.5, DESMAX, 100
DCONSTR 1 2 .5
TOPVAR, 1 , Tshel, Pshell, .5, , , , 1
DRESP1 2 FRMASS FRMASS
DRESP1 1 COMPL COMP
INCLUDE 'model.dat'
ENDDATA
first option: global minimum thickness
(applies to complete design region)
28
Example: MBB Beam
$ Toppology Opt with Minimum Size Control and symmetry
SOL 200 $ OPTIMIZATION
CEND
TITLE = MBB BEAM Minimum Member Size + Symmetry
ECHO = NONE
$ Direct Text Input for Global Case Control Data
DESOBJ = 1
DESGLB = 1
SUBCASE 1
$ Subcase name : Default
SUBTITLE=Default
SPC = 2
LOAD = 2
ANALYSIS = STATICS
BEGIN BULK
PARAM POST 0
PARAM AUTOSPC YES
PARAM,NOCOMPS,-1
PARAM PRTMAXIM YES
$
CORD1R 1 10001 10002 10003
GRID 10001 3. 1. 0.0
GRID 10002 3. 1. 1.0
GRID 10003 4. 1. 0.0
DCONSTR 1 2 .5
TOPVAR, 1 , Tshel, Pshell, .5, , , , 1
, SYM , 1 YZ, ZX
, TDMIN, 0.15
DRESP1 2 FRMASS FRMASS
DRESP1 1 COMPL COMP
DOPTPRM, DESMAX, 100
INCLUDE 'model.dat'
ENDDATA
minimum member size + double symmetry
30 design cycles
100 design cycles
29
One die+ YZ
Symmetry
Two dies + YZ
Symmetry
Torsion Beam – Other Options
30
Example: Engine Mount (cont.)casting constraints in x and y direction
14 loadcases
Without restriction With restriction
31
Topometry Optimization
• 설계 영역에 속해 있는 요소들의 대한 요소 특성 값들을 주어진 조건에 맞도록 변경.
사용자는 요소 특성 (두께 등.)과 재료 물성(E, GE 등)을 설계
• Topometry는 전통적인 전응력설계(Fully Stressed Design, FSD)로 쉽게 확장 가능
• 재료의 가감에 대한 아이디어를 제공 (topology는 제거만 가능)
• Topology의 결과는 0-1로 표현 되지만 topometry는 연속 변수로 표현 가능
• 요소 사이즈 결정에 대한 아이디어 제공
• Test-Analysis Correlation
• Non-volume 요소의 최적 위치에 대한 아이디어
• PDAMP, PELAS, PMASS, PBUSH, PVISC, PGAP, NSM, NSM1, NSML,
PACBAR, PFAST
32
Example 2 – Topometry
• Element results in jobname.des
• Use Patran/Results to display
TOMVAR, 1 , PSHELL, 10, T , 2.0, 1.0, 3.0
TOMVAR, 2 , PSHELL, 39150, T , 2.4, 1.2, 3.6
33
Topography Optimization
• Reinforcement bead 패턴을 주어진 bead 치수 한계(bead의 최소 넓이, 최대 높이, draw angle등) 내에서 제한 조건을 만족하는 최적 모델을 제공하는 형상 최적화 기능의 일종
• Shape Optimization의 일종
• Sheet metal part에 유용
• 기존 Optimization 파일에 BEADVAR 명령 추가
34
• Topography Optimization Features
– Bead minimum width (MW). This parameter controls the width of the beads.
– Maximum bead height (MH). This parameter sets the maximum height
– Draw angle in degrees (ANG)
– Buffer zone between designed and non-designable parts
MW
MHANG
Non-design elementsNon-design elements
Design elementsno buffer zone
Buffer zone
Topography Optimization
35
Example 1 – Topography
• A square fixed at all boundary
• Objective Maximize 1st Frequency
– Minimum width = 10.0
– Maximum height = 20.0
– Draw angle = 70.0
– Grids associated BC is fixed
• Initial design
– 1st Frequency = 0.568HZ
• Output quantities
– Design history in *.f06
– Updated grid location *.pchSOL200 1st Freq. =4.78 Hz
36
Example 2 – Topography
• Minimize Sum of Compliance over four load cases
(i.e., maximize stiffness) = 2.06E+3 at initial
– CQAD4 13817
– GRID 14095
– PSHELL 2
– Minimum width = 50.0
– Maximum height = 10.0
– Draw angle = 70.0
– Grids associated BC is fixed
• Output quantities
– Design history in *.f06
– Updated grid location *.pch
37
Example 3 – Topography (from Auto Customer)
• Maximize 1st Frequency
– Design the base only
– Minimum width = 10.0
– Maximum height = 20.0
– Draw angle = 70.0
– Grids associated RBE2 is fixed
– Use Case Control Set and
BEADVAR “NGSET” to
fix grids
– 1st Freq = 582 HZ SOL200 Result 654 Hz
38
3. 다중모델에 대한 동시최적화 기법검토
39
MultiOpt (MD Nastran - interenal-loop)
40
Example - MultiOpt
• 108 Design Variable
- Static Model
- NVH Model
41
Nonlinear Expansion
(MD Nastran DRESP3 Entry - external-loop)
42
External Multi-Model Process
(MD Nastran + Model Center)
43
4. 최적화 업무 적용에 있어서 주의할 사항들
44
Design Optimization 업무에서 주의할 사항들…
45
• 응용분야?
• o 구조설계 개선 (Sizing, Property, Shape, Topology/Topometry/Topogrphy)
• o 현실성 없는 설계로부터 현실성 있는 설계로 변환
• o 구조응답을 동일하게 구현하기 위한 모델변환
• o 시스템의 지배적인 인자 도출
• o 모델구성 평가
• o 민감도 분석
• o 기타 (설계자의 창의적인 구상 검증 등)
최적화는 Peak만을 줄여준다.
부가된 제한조건만을 만족시킨다.
답은 여러 가지가 있을 수 있으며, 결과가 최선이 아닐 수 있다.
최적화를 강하게 하면 할수록 강건성은 계속 저하한다.
경험이 있는 엔지니어의 판단이
특히 더 중요하다.
5. 향후 최적화 기술의 발전방향
46
해석 개념의 발전방향 변화 트렌드
구조응답해석
(현상 규명)
47
응답최적화
(생산비용 최소화)
응답 강건성 검증
(A/S 비용의 최소화)
SOL103.
SOL111.
.
.
SOL200ANAL=Modes.
SOL200ANAL=MFREQ.
SOL200,SOL400Stochastic.
.
.
0
100
200
300
400
500
600
700
1 2 3 4 5 6 7 8 9Design Cycle
Clo
ck
Tim
e (
Min
ute
) Total Time (Single Run)
Total Time (AESO)
Enhancement of AESO
Further Enhancement of AESO
(Automatic External Superelement Optimization)
Speed up !!!
48
Enhancement of ACMS
• Example 1 (with K4 damping)– SOL 111
– DOF: 7,300,000
– Elements: 900,000
– 3600 modes up to 800Hz
– Forcing frequencies: 320
• Example 2 (with K4 damping)– SOL 111
– DOF: 8,500,000
– Elements: ~1 million
– 7197 modes up to 800Hz
– Forcing frequencies: 700
49
13.15
5.98
3.08
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00 Elapsed Time (Hrs)
47.28
9.74 4.39
0.00
10.00
20.00
30.00
40.00
50.00
Elapsed Time (Hrs)
2010 20112011 SMP=2
DMP=22010 2011
2011 SMP=2
DMP=2
Further Enhancement of ACMS
(Automatic Component Modal Synthesis)
Speed up !!!
OpenMDOTM External Optimizer Service
• Complements MSC’s optimization
capabilities
• User defined SCA service
introduced to access external
optimizers
• Benefits
– Flexibility to use third party or
internally developed optimizers
– Researchers to assess the ability
of their algorithms vs. COTS
implementations
50
Improved
Design
Ride &
Handling, E
xplicit
RSM
DOE
Linear Multi-Model Optimization
Nonlinear Multi-Model Optimization
Multi-Model / Multi-Disciplinary Optimization
MMO Auto Applications:
Analyze Systems with Common Parts
• 4 doors/2 doors Versions of a Car
• V6/V8 Cylinder Engine Configurations
• Sports/Standard Suspensions
MDO Auto Applications:
Analyze Systems with Multiple
Disciplines
• Brakes: Squeal (Acoustics), Wear
(Thermo-Mechanical)
• Engines: Whine (NVH), Durability
(Thermo-Mechanical)
• Full Vehicle: Durability, NVH, Ride &
Handling, Crash
51
감사합니다.
52