Transcript Folie 1

Tutorial 1:
Sensitivity analysis of an
analytical function
Example: Analytical nonlinear function
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Additive linear and nonlinear terms and one coupling term
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Contribution to the output variance (reference values):
X1: 18.0%, X2: 30.6%, X3: 64.3%, X4: 0.7%, X5: 0.2%
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Tutorial 1: Sensitivity Analysis
Task description
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Parameterization of the problem
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Defining DOE scheme
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Evaluation of DOE designs
• Statistical post-processing of DOE
• Approximation post-processing of DOE
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Defining MOP search algorithm
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Evaluation of MOP workflow
• Statistical post-processing of MOP
• Approximation post-processing of MOP
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Reload results in Result Monitoring
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Use Matlab as solver
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Use Excel as solver
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Use Excel plug-in to export data in optiSLang format
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Tutorial 1: Sensitivity Analysis
Project manager
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Open the project manager
Define project name
Create a new project directory
Copy optiSLang examples/Coupled_Function
into project directory
Tutorial 1: Sensitivity Analysis
Parameterization of the problem
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1. Start a new parametrize workflow (double click)
2. Define workflow name
3. Create a new problem specification
4. Enter problem file name
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Tutorial 1: Sensitivity Analysis
Parameterization of the problem
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1. Click “open file” icon in parametrize editor
2. Browse for the SLang input file coupled_function.s
3. Choose file type as INPUT
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Tutorial 1: Sensitivity Analysis
Parameterization of the problem
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1. Mark value of X1 in the input file
2. Define X1 as input parameter
3. Enter parameter name
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Tutorial 1: Sensitivity Analysis
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Parameterization of the problem
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1. Open parameter in parameter three
2. Enter lower and upper bounds
3. Set as default for other variables
and repeat for X2 … X5
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Tutorial 1: Sensitivity Analysis
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Parameterization of the problem
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1. Click “open file” icon in parametrize editor
2. Browse for the SLang output file coupled_solution.s
3. Choose file type as OUTPUT
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Tutorial 1: Sensitivity Analysis
Parameterization of the problem
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Mark output value in editor
Define Y as output parameter
Enter parameter name
Close parametrize editor
Tutorial 1: Sensitivity Analysis
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Parameterization of the problem
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1. Check parameter overview for inputs
2. Check parameter overview for outputs
3. Close overview
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Tutorial 1: Sensitivity Analysis
Define Design Of Experiments (DOE)
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Start a new DOE workflow (double click)
Define workflow name
Define workflow identifier (working directory)
Enter problem file name
Tutorial 1: Sensitivity Analysis
Define Design Of Experiments (DOE)
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Enter solver call (slang –b coupled_function.s)
Enter number of parallel runs
Choose if design directories should be deleted
Start DOE workflow
Tutorial 1: Sensitivity Analysis
Generate DOE scheme
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Choose Latin hypercube sampling
Enter number of samples (50…100)
Generate samples
Close dialog and show samples
Tutorial 1: Sensitivity Analysis
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Generate DOE scheme
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1. Start evaluation of samples
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Tutorial 1: Sensitivity Analysis
Statistics post-processing
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Linear correlation matrix (In-In, In-Out, Out-In and Out-Out)
Quadratic correlation matrix (total values or difference to linear)
Histogram of input/output (select variable in 1.)
Anthill plot (select variables in 1.)
CoD/CoI values (linear: select in 1., quadratic: select in 2.)
Ranked linear or quadratic correlations of single response
Tutorial 1: Sensitivity Analysis
Statistics post-processing
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1. Switch between CoD/CoI visualization
2. Extended correlation matrix (optiSLang 3.2)
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Tutorial 1: Sensitivity Analysis
Statistics post-processing
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1. Statistical properties of single variable
2. Traffic light plot of response for given
safety & failure limit (optiSLang 3.2)
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Tutorial 1: Sensitivity Analysis
Statistics post-processing
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1. Show development of
correlation coefficients
2. Show design table
3. Export DOE to Excel
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Tutorial 1: Sensitivity Analysis
Statistics post-processing
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1. Principal Component Analysis (PCA) of linear correlations
2. Parallel coordinates plot to show designs having an input/output
within certain lower and upper bounds
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Tutorial 1: Sensitivity Analysis
Statistics post-processing
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1. Significance filter for CoD/CoI
2. Manual filter for CoD/CoI
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Tutorial 1: Sensitivity Analysis
Approximation post-processing
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1. Anthill plot of parameter 1 and the response
2. Contour plot of approximation function in terms of parameter 1
and 2 (remaining are set to their mean) vs. the response
3. Surface plot of approximation function
4. Details about approximation settings and properties
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Tutorial 1: Sensitivity Analysis
Approximation post-processing
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4a. 4b.
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Manual approximation settings:
• Parameter subspace
• Polynomial or MLS (exponential or regularized)
• Basis polynomial, constant or density dependent influence
• Transformation settings
Tutorial 1: Sensitivity Analysis
Meta-Model of Optimal Prognosis (MOP)
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Start a new MOP workflow (double click)
Define workflow name
Define workflow identifier (working directory)
Choose DOE result file
Choose optional problem file
Tutorial 1: Sensitivity Analysis
Meta-Model of Optimal Prognosis (MOP)
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CoP settings (sample splitting or cross validation)
Investigated approximation models
DCoP - accepted reduction in prediction quality to simplify model
Filter settings
Selection of inputs and outputs
Tutorial 1: Sensitivity Analysis
Meta-Model of Optimal Prognosis (MOP)
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optiSLang console gives detailed information about the
investigated models and obtained optimal CoP values
Tutorial 1: Sensitivity Analysis
Meta-Model of Optimal Prognosis (MOP)
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Approximation post-processing automatically shows surface and
contour plot of the two most important variables vs. the response
CoP values for single variables are shown
Tutorial 1: Sensitivity Analysis
Overview of different significance values
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MOP/CoP close to reference values (detects optimal subspace
automatically, represents nonlinear and coupling terms)
CoD, k=5
CoI, k=5
CoI, k=3
CoP, k=3
Reference
75%
75%
74%
97%
100%
X1
2%
14%
14%
18%
18%
X2
18%
30%
28%
31%
31%
X3
41%
34%
39%
62%
64%
X4
0%
0%
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0.7%
X5
0%
1%
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0.2%
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Tutorial 1: Sensitivity Analysis
(all inputs)
Full model
(all inputs)
(manual)
(automatic)
Reload DOE or MOP in Result Monitoring
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Start a new Results Monitoring workflow (double click)
Define workflow name
Choose DOE or MOP result file
Start Post-Processing
Tutorial 1: Sensitivity Analysis
Tutorial 1:
Use Matlab as solver
Use Matlab as solver
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Matlab input file: coupled_function.m
1. Input parameter definition
2. Function evaluation
3. Writing the result file
4. Exit Matlab execution!
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Tutorial 1: Sensitivity Analysis
Use Matlab as solver
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Call Matlab from Windows: matlab_windows.bat
1. Disable splash
2. Disable desktop
3. Disable java virtual machine
4. Minimize remaining command window
5. Wait until Matlab is terminated
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Tutorial 1: Sensitivity Analysis
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Use Matlab as solver
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Call Matlab from Linux: matlab_linux.sh
1. Set empty display
2. Disable splash
3. Disable desktop
4. Disable java virtual machine
5. Wait until Matlab is finished
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Tutorial 1: Sensitivity Analysis
Use Matlab as solver
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1. Parameterize inputs in optiSLang from coupled_function.m
2. Parameterize output from coupled_solution.txt
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Tutorial 1: Sensitivity Analysis
Use Matlab as solver
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1. Open new DOE workflow and select “Run a script file”
2. Choose the batch script and start DOE process
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Tutorial 1: Sensitivity Analysis
Tutorial 1:
Use Excel as solver
Use Excel as solver
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1. Generate Excel file with all inputs in one row
and all outputs in one column
2. Mark first input as inputParams
3. Mark first output as outputParams
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Tutorial 1: Sensitivity Analysis
Use Excel as solver
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1. Show Macros
2. Enter Macro name
3. Create Macro
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Tutorial 1: Sensitivity Analysis
Use Excel as solver
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1. In Visual Basic environment use import file feature
2. Import predefined macro file inout.bas
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Tutorial 1: Sensitivity Analysis
Use Excel as solver
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1. inout module should be shown in the module list
2. Delete the empty default module
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Tutorial 1: Sensitivity Analysis
Use Excel as solver
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The visual basic macro
1. Input file name
2. Output file name
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Tutorial 1: Sensitivity Analysis
Use Excel as solver
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Java script to run Excel in batch mode
1. Excel file name
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Tutorial 1: Sensitivity Analysis
Use Excel as solver
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Batch script to run Excel java script
1. Call of java script with full path,
modify path if necessary!
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Tutorial 1: Sensitivity Analysis
Use Excel as solver
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1. Parameterize inputs in optiSLang from input.txt
2. Parameterize output from output.txt
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Tutorial 1: Sensitivity Analysis
Use Excel as solver
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1. Open new DOE workflow and select “Run a script file”
2. Choose the batch script and start DOE process
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Tutorial 1: Sensitivity Analysis
Tutorial 1:
Use Excel plug-in
Use Excel plug-in
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1. Start the plug-in in Excel
2. Mark input data including parameter names
3. Check parameter names and data array
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Tutorial 1: Sensitivity Analysis
Use Excel plug-in
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1. Mark output data including parameter names
2. Check parameter names and data array
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Tutorial 1: Sensitivity Analysis
Use Excel plug-in
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1. Choose design numbers
2. Finish and save data in optiSLang *.bin file
3. Open *.bin in result monitoring workflow
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Tutorial 1: Sensitivity Analysis