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3-1 ANSYS, Inc. Proprietary © 2009 ANSYS, Inc. All rights reserved. May 28, 2009 Inventory #002670 Response Charts Chapter 3

3-1 ANSYS, Inc. Proprietary © 2009 ANSYS, Inc. All rights reserved. May 28, 2009 Inventory #002670 Response Charts Chapter 3

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Page 1: 3-1 ANSYS, Inc. Proprietary © 2009 ANSYS, Inc. All rights reserved. May 28, 2009 Inventory #002670 Response Charts Chapter 3

3-1ANSYS, Inc. Proprietary© 2009 ANSYS, Inc. All rights reserved.

May 28, 2009Inventory #002670

Response Charts

Chapter 3

Page 2: 3-1 ANSYS, Inc. Proprietary © 2009 ANSYS, Inc. All rights reserved. May 28, 2009 Inventory #002670 Response Charts Chapter 3

3-2ANSYS, Inc. Proprietary© 2009 ANSYS, Inc. All rights reserved.

May 28, 2009Inventory #002670

Training ManualChapter 3 - Contents

• Response Charts Defined• Response Charts Set up• Design of Experiments - charts overview• Parameter Correlation - charts overview • Response Surface - charts overview• Goal Driven Optimization - charts overview• Response Chart control - charts overview• Response Charts Quality - charts overview

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Training ManualResponse Charts Defined

• Response charts offer several methods to view the results of your optimization information.

• Broadly speaking there are 2 types of response charts:– 3D response surfaces.– 2D response curves.

• Keep in mind the following points:– The automatic samples discussed earlier represent actual calculated

results points.– The response charts allow one to explore the regions of the design where

NO actual solution is calculated.– Based on the response charts, candidate designs are selected.– Candidate designs should be re-solved to verify the actual solutions are

valid.

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Training ManualResponse Chart Setup

• The charts are controlled from the Response Surface Outline.

Chart Type

Input Parameters

Response and Derived Parameters

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Training ManualResponse Chart Setup . . .

• Properties of Response determines what is displayed in the response charts.

1 input versus 1 response = 2d Response Curve

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Training ManualResponse Chart Setup . . .

2 inputs versus 1 response = 3d Response Surface

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Training ManualDesign of Experiments – charts overview

• Parallel chart - graphical display of the DOE matrix using parallel Y axes to represent all of the inputs and outputs.

In Properties of Parameters Parallel check parameters that you would like to plot.

Chart is interactive –you can get design point number by clicking on the chart.

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Training Manual

• Design Points vs Parameter Chart - a graphical display for plotting design points vs. any input or output parameter.

Design of Experiments – charts overview

In Properties of Design Points vs. Parameter specify parameters that you would like to plot.

Chart is interactive –you can get the parameter value for every point by clicking on the chart.

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Training ManualParameters Correlation – charts overview

• Correlation scatter chart - to graphically view the sample values of one parameter vs. another. A trend line is drawn showing the correlation of the sample values.

In Properties of Correlation Scatter define parameters on X and Y axis.

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Training Manual

• Correlation Matrix – to visualize how closely the various input and output parameters are coupled. The strength of correlation is indicated by color in the matrix.

Parameters Correlation – charts overview

In Properties of Correlation Matrix check parameters that you would like to plot.

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Training ManualParameters Correlation – charts overview

• Sensitivities chart - to graphically view the global sensitivities of each output parameter with respect to the input parameters. The global, statistical sensitivities are based on a correlation analysis using the generated sample points, which are located throughout the entire space of input parameters.

In Properties of Sensitivities you can specify parameters and also chose bar of pie chart.

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Training ManualResponse Surface – charts overview• Response chart - allow you to graphically view the impact that

parameters have on one another. • Information can be displayed in 2d or 3d formats.• Displays are fully interactive.

• You can change the parameter values to explore other designs by moving the slider bars, or entering specific values in the accessible value boxes.

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Training Manual

• Single parameter sensitivities allow users to assess the relative impact each input parameter has on a single response parameter.

• Single Parameter Sensitivities – DesignXplorer calculates the change of the output based on the change of each input independently at the current value of each input parameter. Single parameter sensitivities are local sensitivities.

Response Surface – charts overview

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Training Manual

• Spider charts provide a visual indication of the impact on all responses when inputs are varied.

Response Surface – charts overview

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Training Manual

• Trade off chart - to view the Pareto fronts created from the samples generated in the GDO.

• Since DesignXplorer allows multi-objective optimization, it is often the case that desired goals conflict with one another.

• For example, two reasonable goals in structural analysis might be to reduce the overall mass and increase the stiffness. In such a case, one goal may be realized at the expense of the other.

• The trade off plot allows DX users to visualize this give and take among response parameters with stated goals

– Note, desired values must be specified before trade off studies are available within a GDO.

Goal Driven Optimization – chart overview

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Training Manual

In this example the goals were to minimize both mass and deformation. The trade off plot shows the line along which no improvement in one parameter’s goal can be achieved without sacrificing the other (Pareto optimal).

The slider in Properties of the Tradeoff allows control over the number of Pareto points to be displayed. As the number of points is increased, Pareto points of lesser optimality are added (see next slide).

For more detail on the algorithms and techniques used see the “Theory” section of the DesignXplorer documentation for “Goal Driven Optimization”.

Goal Driven Optimization – chart overview

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Training Manual

Notice that additional Pareto points of less optimality are displayed in different colors from blue to red.

Pareto or non-dominated set, are a group of solutions such that selecting any one of them in place of another will always sacrifice quality for at least one objective, while improving at least one other.

Goal Driven Optimization – chart overview

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Training ManualGoal Driven Optimization – chart overview

• Samples chart - to visually explore a sample set given defined objectives.

• The aim of this chart is to provide a multidimensional graphical representation of the parameter space you are studying. The chart uses the parallel Y axes to represent all of the inputs and outputs. Each sample is displayed as a group of line curves where each point is the value of one input or output parameter. The color of the curve identifies the Pareto front that the sample belongs to, or the chart can be set so that the curves display the best candidates and all other samples.

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Training Manual

• The Samples chart is a powerful exploration tool because of its interactivity. It allows you to first pick a Y axis with the mouse then slide the yellow arrows that appear on the bottom and the top of each axis up or down in order to increase or decrease the axis bounds. Samples are dynamically hidden if they fall outside of the bounds. Repeating the same operation with each axis allows you to manually explore and find trade-offs.

Goal Driven Optimization – chart overview

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• Sensitivities chart (GDO) - to graphically view the global sensitivities of each output parameter with respect to the input parameters.

• The sensitivities available under the Goal Driven Optimization and Six Sigma Analysis are statistical sensitivities. Statistical sensitivities are global sensitivities, whereas the single parameter sensitivities available under the Responses view are local sensitivities. The global, statistical sensitivities are based on a correlation analysis using the generated sample points, which are located throughout the entire space of input parameters.

Goal Driven Optimization – chart overview

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Training ManualResponse Chart Controls . . .

• By RMB on response surface you can toggle from 2D/3D Chart. Also you can insert response point and design point. Also you can save Image as and edit properties.

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• You can change the parameter values to explore other designs by moving the slider bars, or entering specific values in the accessible value boxes.

Response Chart Controls . . .

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• The triad control at the bottom left in the 3D Response chart window allows you to rotate the chart in freehand mode or quickly view the chart from a particular plane. To zoom any part of the chart, use the normal zooming controls (Shift-middle mouse button, or scroll wheel).

Response Chart Controls . . .

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Training ManualResponse Chart Controls . . .

• You can have as many charts as you like under a response point. You can change the name of a chart cell by clicking on it twice and entering the new name.

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Training ManualResponse Chart Quality• In the Outline of Response Surface you can select output parameter and

Properties of Output reports qualitative information about the “Goodness-of-Fit” of the results.

• Look at different measures of goodness of fit since all subsequent optimization/probabilistic analyses are based on the response surface!

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• Coefficient of Determination (R2 measure):– Measures how well the response surface represents output parameter

variability.– Should be as close to 1.0 as possible.

• Adjusted Coefficient of Determination: – Takes the sample size into consideration when computing the Coefficient of

Determination. – Usually this is more reliable than the usual coefficient of determination when

the number of samples is small ( < 30).

• Maximum Relative Residual:– Similar measure for response surface using alternate mathematical

representation.– Should be as close to 0.0 as possible.

Response Chart Quality . . .

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• Root mean square error:

– Square root of the average square of the residuals at the DOE points for regression methods.

• Relative Root Mean Square Error:

– Square root of the average square of the residuals scaled by the actual output values at the DOE points for regression methods.

• Relative Maximum Absolute Error:

– Absolute maximum residual value relative to the standard deviation of the actual outputs.

• Relative Average Absolute Error:

– Absolute maximum residual value relative to the standard deviation of the actual output data, modified by the number of samples.

– Useful when the number of samples is low ( < 30).

Response Chart Quality . . .

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Training ManualResponse Chart Quality . . . • Refinement Option – if goodness-of-fit measures are low.

• Kriging option to provide a comprehensive goodness of fit report of a standard response surface.