What's New
View new features for HyperStudy 2025.1.
Altair HyperStudy 2025.1 Release Notes
New Features
- Interact with HyperStudy via Programming Interface
 - This release introduces a powerful and easy-to-use Python interface, enabling seamless integration of HyperStudy into workflows and applications.
 - Leveraging High Power Computing via Altair One
 - A new extension tool that enables submitting HyperStudy jobs from local workstations to Altair One appliances.
 - Twin Activate Model
 - A new model type to integrate multi-disciplinary, dynamic system models via Altair Twin Activate.
 - Auto Feature Reduction in Fit
 - HyperStudy FAST algorithm now monitors the sensitivity of each input variable on demand and automatically eliminates them based on the contribution threshold defined by the user.
 - Access to Tutorial Files within HyperStudy
 - Tutorial tab now allows downloading tutorial files directly within HyperStudy.
 
Enhancements
- Bounds and Modes tabs are consolidated to Define Input Variables tab.
 - Linking files between models via drag-and-drop in Model Resources.
 - Defining bounds for multiple Design Variables at once.
 
Resolved Issues
- There were several graphical issues in Dark Mode.
 - Pyfit files in Tutorial HS-4550 were broken.
 - XML Data Source tool incorrectly highlighted selected attributes.
 - Workbench model failed to import variables and extract results.
 
Announcements
- HyperStudy classic version is no longer available.
 - Twin Activate and romAI integrations are supported on Windows only. However, we are working to enable them for Linux in the future.
 
Altair HyperStudy 2025 Release Notes
New Features
- Leverage accuracy metrics as responses
 - HyperStudy Pyfit model now provides an option to include fit metrics as conventional responses. This allows monitoring accuracy and applying objectives which is useful in fit-based optimization approaches.
 - Deploy PhysicsAI model as solver
 - A new extension tool to auto-register trained PhysicsAI models as solvers.
 
Enhancements
- Perform trade-off studies following input variable formats
 - Tutorial HS-1100, Setting Up Existing Data Model
 - Tutorial HS-1695, Using Hooks in PhysicsAI Model
 
Resolved Issues
- Using labels instead of model parameters in hst_output.hstp files no longer prevents extracting values of different outputs with same labels.
 - Hidden or shown tabs no longer restore to default after reopening the application.
 
Announcements
- Data Source tool, Hstp Reader, has been deprecated and the updater will convert it to XML reader tool. Please use deprecate flag with 8319 to restore the tool.
 - “setDirectory” and “setFileHint” python functions have been removed from External Optimizer API. They have been replaced with getResourcePath(type: RESOURCE_TYPE)-> str on the setup class using the resource types RESOURCE_TYPE_WORK_DIRECTORY and RESOURCE_TYPE_FILE_HINT.