A study is a self-contained project in which models, variables, output responses, and approaches are defined.
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.
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.
View the computational results from the Stochastic. approach
View new features for HyperStudy 2019.
Learn the basics and discover the workspace.
Discover HyperStudy functionality with interactive tutorials.
Explore the HyperStudy user interface.
Learn how to create, open, import and save models.
Before you can create approaches you must first setup your Study by defining input variables and output responses.
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.
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.
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.
Add approach to the study.
Select and review the input variables to include in the Stochastic approach.
Select and review the output responses to include in the Stochastic approach.
Select a numerical method to use when evaluating the Stochastic approach.
Run the approach.
Check the integrity of data.
View summary of run data.
Visualize data trends.
Analyze distributions of run data.
Analyze dependency between two sets of data.
Analyze dependency between three sets of data.
Visualize dimension reduction.
Plot the effects of input variables on output responses in hierarchical order (highest to lowest).
Lookup reliability values.
Visualize representations of system reliability.
Package reports for data generated during the approach.
Each approach in HyperStudy serves a different purpose in the design study.
Customize HyperStudy by registering solver scripts, functions, and optimizers, and defining user preferences files.
Keyboard shortcuts used to access HyperStudy features.
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