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Perform Studies
A study is a self-contained project in which models, variables, output responses, and approaches are defined.
Setup the Approaches
Once the study Setup is complete, an unlimited combination of approaches can be added to a study. A study approach is a specific set of steps taken to study the mathematical model of a design.
Setup Sampling Fit Studies
A Sampling Fit is a combination of space-filling DOE method and mathematical model trained by the data generated.
Post Processing
View the computational results from the Sampling Fit.
Summary Post Processing
View summary of run data.

Welcome
What's New
View new features for HyperStudy 2024.1.
Get Started
Learn the basics and discover the workspace.
Tutorials
Discover HyperStudy functionality with interactive tutorials.
Manage Files and Data
Create, open, import, and save models.
Perform Studies
A study is a self-contained project in which models, variables, output responses, and approaches are defined.
- Setup the Study
  Before you can create approaches you must first setup your Study by defining input variables and output responses.
- Setup the Approaches
  Once the study Setup is complete, an unlimited combination of approaches can be added to a study. A study approach is a specific set of steps taken to study the mathematical model of a design.
  - Setup DOE Studies
    A DOE is a series of tests in which purposeful changes are made to the input variables to investigate their effect upon the output responses and to get an understanding of the global behavior of a design problem. By running a DOE, you can determine which factors are most influential on an output response.
  - Setup Fit Studies
    A Fit is a mathematical model that is trained by data and is capable of predicting output response variables for a given set of input variables.
  - Setup Optimization Studies
    An Optimization is a mathematical procedure used to determine the best design for a set of given constraints, by changing the input variables in an automatic manner.
  - Setup Sampling Fit Studies
    A Sampling Fit is a combination of space-filling DOE method and mathematical model trained by the data generated.
    - Add a Sampling Fit Approach
      Add approach to the study.
    - Define Definition
      Define the models, input variables, and output responses to be used in the study.
    - Select a Numerical Method
      Select a numerical method to use when evaluating the Sampling Fit.
    - Evaluate
      Run the approach.
    - Post Processing
      View the computational results from the Sampling Fit.
      - Integrity Post Processing
        Check the integrity of data.
      - Summary Post Processing
        View summary of run data.
      - Parallel Coordinate Post Processing
        Visualize data trends.
      - Distribution Post Processing
        Analyze distributions of run data.
      - Scatter Post Processing
        Analyze dependency between two sets of data.
      - Scatter 3D Post Processing
        Analyze dependency between three sets of data.
      - Ordination Post Processing
        Visualize dimension reduction.
      - Data Sources Post Processing
        Analyze data sources.
      - Gradient Post Processing
        Visualize gradients using vectors.
      - Diagnostics Post Processing
        Analyze the response surface quality.
      - Residuals Post Processing
        Identify design errors.
      - Trade Off Post Processing
        Perform "What If" scenarios.
    - Create Reports
      Package reports for data generated during the approach.
  - Setup Stochastic Studies
    A Stochastic approach is a method of probabilistic analysis where the input variables are defined by a probability distribution, and consequently the corresponding output responses are not a single deterministic value, but a distribution.
  - Setup Basic Studies
    A Basic approach can be used to test nominal values and bounds by performing a nominal run, system bound check, or sweep.
  - Setup Verification Studies
    A Verification approach compares two data sets in a side by side comparison.
Learn the Approaches
Each approach in HyperStudy serves a different purpose in the design study.
Customize HyperStudy
Customize HyperStudy by registering solver scripts, functions, and optimizers, and defining user preferences files.
Keyboard Shortcuts
Keyboard shortcuts used to access HyperStudy features.
Frequently Asked Questions
This section provides quick responses to typical and frequently asked questions regarding HyperStudy.

Summary Post Processing

View summary of run data.

View Run Data Summary

View a detailed summary of all input variable and output response run data in a tabular format from the Summary post processingEvaluation Data tab.

From the Evaluate step, click the Evaluation Data tab.
From the Post Processing step, click the Summary tab.
From the Channel selector, select the channels to display in the summary table.
Analyze the run data summary.
Optional: Disable run data from post processing without deleting it entirely from the study by clearing a run's corresponding checkbox in the Post Process column.
When a run is disabled, it will be removed from all plots, tables, and calculations in the Post Processing step.