Altair HyperStudy 2022.3 Release Notes

New Features

New Low-Discrepancy Quasi-Random Sampling Method
A Sobol Sequence based sampling method has been added in both DOE and Sampling Fit approaches. It is extensible and supports design variable constraints.
On-demand Model-Independent Responses
Internal metadata-type or user-defined responses can be optionally added as channels in the Post Processing step.
New Data Source Tool for Extracting Data of Text Files
A new extraction tool has been added to read data from XML files.
Parameterization of Additional Resource Files
Files added in Model Resource can be parameterized independent of the main resource file.
Understanding The Role of Each Design Variable Constraint in Generating Datasets
Each Design Variable Constraint plays a role in redefining the initial design space and it is important to identify their individual contributions. Hence, individual and combined pass rates have been added.


Improving Efficiency and Accuracy of Predictive Models
Zero gradient information, when available, is consumed by fit models to boost efficiency and accuracy.
Multiple Responses from a Single Text File
File Assistant now supports extracting multiple outputs from the same text file.
Confidence Interval Plots for Non-LSR Fit Models
Previously, confidence intervals were available only in LSR. Now, it is extended to MLSM and RBF.
Auto-Detecting Dependencies in RADIOSS Connection
Radioss integration identifies dependencies such as engine, include, and initial state files and auto-include them in the Model Resources area.
Customizable Model Connections
A model-specific settings option has been introduced to run integrated processes in a particular manner. For example, Excel connection can be set to save a copy of the updated session in each run directory.