HS-1810: Post Process with HyperStudy

Learn how to create various approaches (Design of Experiment, Approximation, Optimization, Stochastic) and explore a variety of tools and post processing methods offered by HyperStudy.

Before you begin, complete HS-4415: Optimization Study of a Landing Beam Using Excel or import the HS-4415.hstx archive file, available in <hst.zip>/HS-1810/.

Run Fractional Factorial DOE

  1. Add a DOE.
    1. In the Explorer, right-click and select Add from the context menu.
    2. In the Add dialog, select DOE and click OK.
  2. Define specifications.
    1. Go to the DOE 1 > Specifications step.
    2. In the work area, set the Mode to Fractional Factorial.
    3. In the Settings tab, set Resolution to III.


      Figure 1.
    4. Click Apply.
  3. Evaluate tasks.
    1. Go to the DOE 1 > Evaluate step.
    2. Click Evaluate Tasks.
    3. While the DOE is in progress, click the Tasks tab to view the feedback on the results of the evaluation.
    4. During the execution of the DOE, you can monitor the evaluation of the 16 runs in either the Evolution Plot or Evolution Data tabs.
  4. Post process results.
    1. Go to the DOE 1 > Post-Processing step.
    2. Click the Summary tab to view all input variable and output response run data in a table.
      Tip: Use the Sort and Find options in the right-click context menu to sort and search data.


      Figure 2.
    3. Click the Integrity tab to view statistical measures over the population (samples of the DOE) for all of the input variables and output responses.


      Figure 3.
    4. Click the Scatter tab to plot the DOE results.


      Figure 4.
    5. Click the 3D Scatter tab to view DOE results in a scatter plot.
      Tip: If the 3D Scatter tab is not enabled, click (Show or Hide Tabs), and select 3D Scatter from the Standard Tabs.
      Only one input variable/output response can be selected for the X and Y axes, whereas multiple input variables/output responses can be selected for the Z axis.


      Figure 5.
    6. Click the Linear Effects tab to review the effect of an input variable on an output response, ignoring the effects of other input variables.
    7. Above the Channel selector, click to plot the linear effects. Use the Channel selector to select the variables AA_w1 and AA_w2 and the output response Area ACE.


      Figure 6.
    8. Above the Channel selector, click to view the linear effects in a table.
      Tip: From the Channel selector, use the Sort and Filter options in the right-click context menu to sort and filter effects.


      Figure 7.

Run Hammersley DOE

  1. Add a DOE.
    1. In the Explorer, right-click and select Add from the context menu.
    2. In the Add dialog, select DOE and click OK.
  2. Define specifications.
    1. Go to the DOE 2 > Specifications step.
    2. In the work area, set the Mode to Hammersley.
    3. In the Settings tab, change the Number of Runs to 50.
    4. Click Apply.
  3. Evaluate tasks.
    1. Go to the DOE 1 > Evaluate step.
    2. Click Evaluate Tasks.

Run Latin HyperCube DOE

  1. Add a DOE.
    1. In the Explorer, right-click and select Add from the context menu.
    2. In the Add dialog, select DOE and click OK.
  2. Define specifications.
    1. Go to the DOE 3 > Specifications step.
    2. In the work area, set the Mode to Latin HyperCube.
    3. In the Settings tab, change the Number of Runs to 15.
    4. Click Apply.
  3. Evaluate tasks.
    1. Go to the DOE 1 > Evaluate step.
    2. Click Evaluate Tasks.

Run Radial Basic Function Fit

  1. Add a Fit.
    1. In the Explorer, right-click and select Add from the context menu.
    2. In the Add dialog, select Fit and click OK.
  2. Import matrices
    1. Go to the Fit 1 > Specifications step.
    2. Click Add Matrix three times to add three matrices.
    3. Define the matrices by selecting the options indicated in the Figure 8.
    4. Click Apply.


    Figure 8.
  3. Define specifications.
    1. In the work area, Fit Type column, select Radial Basis Function (RBF) for all output responses.
    2. Click Apply.


    Figure 9.
  4. Evaluate Fit.
    1. Go to the Fit 1 > Evaluate step.
    2. Click Evaluate Tasks.
    3. To review the values of the output responses and their approximations while the evaluation is in progress, click the Evaluation Data and Evaluation Plot tabs.


      Figure 10. Evaluation Plot
  5. Post process results.
    1. Go to the Fit 1 > Post-Processing step.
    2. Click the Residuals tab to identify errors for each design.
      The error (and percentage) between the original output response and the approximation is listed for each run of the input, cross-validation, or testing matrices.


      Figure 11.
    3. Click the Diagnostics tab to assess the accuracy of a Fit. Different criteria is displayed for the Input, Testing, and merged matrices.


      Figure 12.
    4. Click the Trade-Off tab to modify the values of input variables in order to see their effect on the output response approximations.
      Use the Channel selector to select the desired output responses to display in the Outputs pane. Input variable controls are located in the top frame (Inputs). Change each input variable by moving the slider in the first Value column, or by entering a value into the second Value column. Set input variables to their initial, minimum, or maximum values by moving the slider in the upper right-hand corner of the Inputs frame.


      Figure 13.
    5. In the Trade-Off tab plot variables and output responses in order to see the input variables effect on the output response approximations.
      Select input variables to plot by enabling its corresponding X Axis checkbox in the Inputs pane. Use the Channel selector to select output responses to plot. The values for the input variables which are not plotted are modified in the top frame (Inputs). Move the sliders in the Value column to modify the other input variables, while studying the output response throughout the design space.


      Figure 14.

Run ARSM Optimization

  1. Add an Optimization.
    1. In the Explorer, right-click and select Add from the context menu.
    2. In the Add dialog, select Optimization and click OK.
  2. Go to the Optimization 2 > Definition > Define Output Responses step.
  3. Click the Objectives/Constraints - Goals tab.
  4. Add an objective.
    1. Click Add Goal.
    2. In the Apply On column, select Area ACE (r_10).
    3. In the Type column, select Minimize.


    Figure 15.
  5. Add constraints.
    1. Click Add Goal nine times to add nines goals, which will be defined as constraints.
    2. Define Constraint 1 through Constraint 9 by selecting the options indicated in Figure 16.


    Figure 16.
  6. Define specifications.
    1. Go to the Optimization 2 > Specifications step.
    2. In the work area, set the Mode to Adaptive Response Surface Method (ARSM).
      Note: Only the methods that are valid for the problem formulation are enabled.
    3. Click Apply.
  7. Evaluate tasks.
    1. Go to the Optimization 2 > Evaluate step.
    2. Click Evaluate Tasks.
    3. Click the different tabs in the Evaluate step to monitor the progress of the Optimization.
    4. Click the Evaluation Plot tab to plot variables and output responses across runs (abscissa are run numbers, not iterations).


      Figure 17.
    5. Click the Iteration Plot tab to plot variables and output responses against iterations.


      Figure 18.
      When the constraint history is plotted, the constraint bounds can be marked with a datum line. Use the Channel selector to select a constraint, then click (located above the Channel selector) and select Bounds.


      Figure 19.

Run Hammersley Stochastic

  1. Add a Stochastic.
    1. In the Explorer, right-click and select Add from the context menu.
    2. In the Add dialog, select Stochastic and click OK.
  2. Define specifications.
    1. Go to the Stochastic > Specifications step.
    2. In the work area, set the Mode to Hammersley.
    3. In the Settings tab, change the Number of Runs to 100.
    4. Click Apply.
  3. Evaluate tasks.
    1. Go to the Stochastic > Evaluate step.
    2. Click Evaluate Tasks.
  4. Go to the Stochastic > Post-Processing step.
  5. Click the Integrity tab to access a series of statistical measures on input variables and output responses.
  6. Click the Distribution tab to view variable and output response data in a histogram.


    Figure 20.
  7. Click the Scatter tab to view sampling patterns and possible correlations between output responses or between input variables and output responses.


    Figure 21.
  8. Compute the probability of failure (bound is violated) and the reliability (bound is respected).
    1. Click the Reliability tab.
    2. Click Add Reliability.
    3. Define the reliability.
      • Set Response to Area ACE (r_10).
      • Set Bound Type to <= (less than or equal to).
      • For Bound Value, enter 70.000.
      HyperStudy computes the reliability and probability of failure in the Reliability and Probability of Failure columns.


      Figure 22.