HyperStudy Model Modification and Interpretation Approaches

Learn the four approaches in HyperStudy to modify a model and interpret the results.

The design of experiments (DOE) approach

The DOE approach can be defined as a test or a series of tests in which purposeful changes are made to the input variables of a process or system so that the reasons for changes in the output response can be identified and observed. Responses can be extracted, but will not affect how the model permutations are generated.

A fit approach

The fit approach approximates the response of a model by creating a mathematical equivalent of a model. This approach uses previous approaches as inputs that are used to predict how a model would behave for a change in design variables. This approach is recommended where computational resources are scarce.

The optimisation approach

Optimisation approaches are used to generate a model that behaves in the desired manner. The responses that are extracted from simulations are used to determine what the next model permutation should be.

The stochastic approach

Stochastic approaches are used to analyse the effect of tolerances in the design variables (for example, from material properties, manufacturing tolerances). These approaches can help identify the probability of responses adhering to defined specification.