VisualDOC: A Practical Software Integration and General Purpose Design

Transcription

1 VisualDOC: A Practical Software Integration and General Purpose Design Optimization Solution Suite Ashwin P Gurnani, Juan Pablo Leiva, Garret N. Vanderplaats Vanderplaats Research & Development, Inc. Colorado Springs, CO, USA

2 Outline of Presentation Introduction VisualDoc Framework VisualDoc Grapical Interfaces and Key Windows Examples Summary Conclusions VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 2

3 Introduction Design of large scale products and processes require interaction from several different disciplines. These disciplines utilize computationally expensive analyses codes, for example, FEA, CFD etc. With rapidly increasing costs, never before has there been a need for producing optimally designed products. This paper presents a product design solution suite that provides engineers the capability to integrate multiple analyses software AND optimize designs over these multiple analyses codes. VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 3

4 VisualDOC Framework Database is the central component of the software. Saved as platform independent.vdb file VisualScript Integration Utility GUI 3 rd Party Analysis Database User Defined Analysis Program Gradient-based Optimization Design of Experiments Response Surface Optimization Evolutionary Optimization VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 4

5 VisualDOC Introduction VisualDOC GUI Inputs Responses VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 5

6 Optimization Modules Select Optimization Module VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 6

7 Gradient Based Optimization Constrained Unconstrained VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 7

8 Design of Experiments Create an experimental design Select Sampling Method Select DOE Action VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 8

9 Design of Experiments Select Sampling Method Approximate responses Select Approximation Model Select DOE Action VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 9

10 Design of Experiments RS coefficients Actual vs. Predicted VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 10

11 Response Surface Optimization Select the Approximation Model Order Conversion of Chemical Process (%) Conversion of Chemical Process (%) Select the Starting Strategy VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 11

12 Non-Gradient Based Optimization Select Optimization Algorithm Select Starting Strategy Define Algorithm related parameters VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 12

13 Probabilistic Analysis and Optimization Set up random Inputs and Responses Select Probabilistic Analysis Method VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 13

14 Probabilistic Analysis and Optimization Reliability Optimization Control the probability of failure Robust Optimization Control the variability of a response Probability Constraint Bound Probability of failure y 2 y 1 y 0 x 2 x 1 VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 14

15 Direct Interface --Excel Prepare Excel spreadsheet Define inputs and responses in VisualDOC VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 15

16 Direct Interface -- Excel Create VisualDOC- Excel interface Use the Interface as the analysis program VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 16

17 Direct Interface -- Matlab Prepare Matlab M-file Define the Inputs and Responses in VisualDOC VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 17

18 Direct Interface -- Matlab Create a task Specify the Matlab M-file as the analysis program VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 18

19 Coupling Third Party Software Through VisualScript Create analysis workflow in VisualScript Extract the Inputs from the input file Call third party analysis program Extract the Outputs from the output file VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 19

20 VisualDOC API VisualDOC C/C++ Application Programming Interface (API) functions allow users to embed all the capabilities of VisualDOC into users own program. These capabilities include Direct Gradient-based Optimization (DGO) Response Surface Approximate Optimization (RSA) Design Of Experiments (DOE) Non-gradient-based Optimization (NGO) Single Analysis Probabilistic Optimization. VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 20

21 Parallel Analysis Put multiple analysis elements in the Parallel Container Add Parallel Container to the workflow VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 21

22 Remote Run Analysis Remote computers VisualDOC local computer Define remote connection properties VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 22

23 Create and Run Task Create an optimization task Run the optimization task and graphically visualizing VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 23

24 Post Process the Optimization Results Plot Objective Plot Design Variables Plot Responses and show the constraints VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 24

25 What-If? Study Tool Original optimization result New optimization result Relax the displacement constraint Run Approximate Optimization with new constraint VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 25

26 Examples VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 26

27 Problem Description LS-Dyna Optimization VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 27

28 Optimization Problem Objective Maximize Internal Energy Design Variables Thickness of the shell elements Shape changes of the tube Linking to ensure symmetry Original Shape S7 ~ S10 S11 S3 ~ S6 S1 S2 S13 S12 VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 28 Perturbations except S13 Perturbation - S13

29 VisualScript Used to define the interaction between VisualDOC and LS-Dyna VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 29

30 VisualScript Design Variables Responses VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 30

31 VisualDOC VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 31

32 Results Initial Design Optimal Design Internal Energy = Internal Energy = VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 32

33 Results VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 33 Initial Design Optimal Design

34 Case Study Turbomachinery System Design Preliminary Design AxSTREAM Meshing Structural and CFD Analysis and Optimization GENESIS / VisualDOC Blades, Disks, Complete Systems VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 34

35 Case Study Turbomachinery System Design TIP/SHROUD Span Layer 100% (r = 5) CP1, LE s = 1 b CP2, s = 2 CP4, TE s = 4 The blade geometry is divided into 5 constant radius layers evenly distributed along the span (0.00% - Hub and 100 % - Shroud) Axis of Rotation (-z) HUB Span Layer 0% (r = 1) CP3, s = 3 + Z (M ) At each span layer, the mean (camber) line is generated using a 4-point Bezier control polygon M = R R + Z Z = Z M ' = M M ' = s M ' ds 0 R θ β = a tan M ' M ' ' *100 ' r s M = r s M r TE A radial interpolation between the airfoils at the each layer to generate the 3D blade Shape Each Bezier Control Point (CP) is specified as a (M r s, b) coordinate pair: (1 r 5) Hub to Shroud Index (1 s 4) LE to TE Index LE Edge Sweep (q r ) indicated at each Span Layer S - Fractional distance along the curve 0 S 1 VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 35

36 Case Study Turbomachinery System Design Objective: Maximize efficiency NEW DESIGN VARIABLES OPTIMIZER (VISUALDOC) GENERATE BLADE GEOMETRY [CFX-BLADEGEN] RESULTS BLADE PASSAGE CFD ANALYSES [CFX-BLADEGEN(PLUS)] VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 36

37 Case Study Turbomachinery System Design Blade Results: An average of 9% increase in total efficiency was obtained Robustness of the approach evidenced in its ability to yield significant efficiency gains in spite of the noisy objective function. VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 37

38 Case Study Engine Head Gasket 2-D Z-Flow engine cooling system (Block, Head, and Gasket) Objective: Design variables: Constraints: Analysis: Maximize the fluid velocity averaged at 10 locations Holes diameter and location (offset from center) (12 design variables total) Minimum velocity at 10 locations FLUENT CFD program HEAD Velocity_Head_Point_1 Velocity_Block_Point_1 Inlet Velocity (8.577 m/s) VHP_5 VHP_3 VHP_4 VHP_2 Hole 1 Hole 2 Hole 3 Hole 4 Hole 5 Hole 6 VBP_5 VBP_2 VBP_3 VBP_4 BLOCK Gasket 850 mm VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 38

39 Case Study Engine Head Gasket GAMBIT (mesher) journal file parameterization Blockhead.msh Block / Head mesh is unchanged during optimization HoleZone.msh Hole regions mesh is changed by VisualDOC using GAMBIT journal file Gasket Gasket Blockhead.msh VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 39

40 Case Study Engine Head Gasket Velocity constraint not satisfied at 2 locations initially Initial design Optimal design - 24 FLUENT calls - Constraints satisfied after 15 FLUENT calls - Average velocity increase: 20% VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 40

41 Case Study Integration with MoldFlow VisualDOC has been integrated with MoldFlow s MoldFlow Plastics Insight (MPI) software to determine Optimal gate location. Optimal gate location will be the geometry that minimizes the maximum pressure at the end of the filling. VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 41

42 Case Study Integration with MoldFlow The Flat Plate Below is Comprised of Four Different Thickness Regions VisualDOC Will Locate the Three Gates so that the Maximum Pressure at the End of Filling will be Minimized Initial Gate Locations VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 42

43 Case Study Integration with MoldFlow Optimization Process Sequence VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 43

44 Case Study Integration with MoldFlow Optimal Gate Locations VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 44

45 Case Study Integration with MoldFlow During 15 iterations, injector X and Y coordinates for each gate migrated to plate locations that minimized the maximum pressure at the end of fill time. Total 22 analyses were performed for this optimization. VisualDOC optimization parameters may be set to reduce total number of analyses to achieve better rather than best design. A better guess for the initial gate locations will also reduce total number of analyses. VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 45

46 Summary Set up Input and Output Set Optimization Module and Respective Options Integrate with Analysis Create and Run Task Post-processing What-If? Study VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 46

47 Conclusions This paper presents a solution suite for complete product design optimization, namely VisualDOC. VisualDOC has the capability to wrap design and optimization algorithms around any ASCII based 3 rd party analysis software. VisualDOC can be used within parallel computing clusters where different analysis are run concurrently on remote machines. This allows for solution of large scale optimization problems that involve several computationally intensive analysis codes. VisualDOC s optimization routines have proven to improve product designs and product design processes. VisualDOC: A Practical Software Integration and General Purpose Optimization Solution Suite 47