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.
Enhancements
- 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.