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Design Exploration
Once the baseline model is prepared, you can define morph volumes, morph geometry, create design shapes and run DOE studies. These tool work for both AcuSolve and ultraFluidX-based workflows.
PhysicsAI
Create and Manage Datasets
Datasets are collections of one or more simulation results used for training or testing a model.

Welcome
What's New
View new features for HyperMesh CFD 2026.
Get Started
Learn the basics and discover the workspace.
Onboarding Resources
Discover HyperMesh CFD functionality with interactive tutorials and community resources.
Solution Layers
Solution-centric workflows allow you to traverse through modeling environments using a dedicated UI layer.
Manage Files and Data
Create, open, import, and save models.
Convert
Use the Convert tool to convert entire models between data types.
Geometry Repair
Manage CAD, FE, and 2D parametric sketch geometry.
Meshing
Generate surface/volume mesh by defining mesh controls, or interactively create and edit 2D surface mesh.
Setup
Prepare your model and run the simulation.
Post-Processing
Post-process the simulation results by creating visualizations and measurements.
Design Exploration
Once the baseline model is prepared, you can define morph volumes, morph geometry, create design shapes and run DOE studies. These tool work for both AcuSolve and ultraFluidX-based workflows.
- Morphing
  Rapidly change the shape of the FE mesh without severely sacrificing the mesh quality.
- PhysicsAI
  - PhysicsAI Capabilities in CFD
    PhysicsAI is an AI-powered tool designed to accelerate simulation workflows by leveraging historical simulation data.
  - Guidelines for PhysicsAI Usage
  - Create and Load Projects
    Each session starts with creating a new project or loading an existing project.
  - Create and Manage Datasets
    Datasets are collections of one or more simulation results used for training or testing a model.
    - Create Datasets
    - Curate and Manage Data
      It is important to carefully curate the datasets to avoid noise being introduced into the model due to the presence of outliers. This can be done after a dataset has been created.
    - CAE Data Compatibility
      Learn more about the data compatibility of PhysicsAI.
  - Train Models
    Train models using any physics, any mesh, and without design variable parametrization.
  - Test Models
    Use the Model Testing tools to test models and review test results.
  - Predict Results
    Use the predict tool to generate a model prediction.
  - Decimate
    The Decimate tool reduces the number of mesh elements while preserving key features of the geometry, simplifying complex models without sacrificing accuracy.
  - Similarity Score
    Like all machine learning models, PhysicsAI models are most accurate when the design being predicted is similar to the designs used for training.
  - Use Batch Mode
    Learn more about using batch mode.
  - Best Practices for PhysicsAI
    Learn more about the best practices for training and using PhysicsAI models.
  - Frequently Asked Questions
    This section provides quick responses to typical and frequently asked questions regarding PhysicsAI.
Automation
Automate simulation processes with templates and utility scripts.
Solver Help
More resources for AcuSolve and ultraFluidX solvers.

View All Altair HyperWorks Help

Create and Manage Datasets

Datasets are collections of one or more simulation results used for training or testing a model.

Note: Dataset creation times vary because each solver result/input deck must be processed separately.

The following files are supported for PhysicsAI:

Table 1. List of Supported Files
Supported Solvers	File Format
Abaqus	.odb
AcuSolve	.ensight .h3d
ANSYS	.rst .rth
Star-CCM+	.ensight
Custom/user-generated	.ensight .unv .h3d
Fluent	.ensight
LS-DYNA	.d3plot .d3eigv
Marc	.t16
Nastran	.op2 .h5 .xdb
PAM-CRASH	.dsy
OptiStruct	.h3d .op2 .out .pch
Radioss	.h3d .anim
ultraFluidX	.ensight .h3d .case

The required files based on the inputs and outputs to be used are summarized in Table 2.

Note: In Table 2, thickness and/or material is only for supported decks. See PhysicsAI-T: 3000 Custom Inputs with a Global Hook or PhysicsAI-T: 3010 Custom Inputs with a Nodal Hook for a list of supported decks.

Table 2.
Inputs				Outputs		Files Needed
Non-parametric	Parametric			Field result	KPI and/or curve
Geometry	Thickness and/or material	Global property	Nodal property	Field result	KPI and/or curve
✓	x	x	x	✓	x	Result files (.h3d, .odb, and so on)
✓	✓	x	x	✓	x	Result files + Input decks (.fem, .rad, and so on) with the same name
✓	x	x	x	x	✓	[Input deck or Result file] + .json file with the same name (outputs)
✓	✓	x	x	x	✓	Input deck + .json file with the same name
✓	x	✓	x	✓	x	Result file + .json with same name (inputs) + Global hooks
✓	x	✓	x	x	✓	[Input decks or Result file] + .json with the same name (inputs and outputs) + Global hook
✓	x	✓	x	✓	✓	Result file + .json with the same name (inputs and outputs) + Global hook
✓	✓	✓	x	✓	✓	Input deck + Result file .json with the same name (inputs and outputs) + Global hook
✓	✓	✓	✓	✓	✓	Input deck + Result file + .json with the same name (inputs and outputs) + .csv file + Global hook + Nodal hook
✓	x	x	✓	✓	x	Result file + .csv file + Nodal hook
✓	x	x	✓	x	✓	[Input deck or Result file] + .json with the same name (outputs) .csv file + Nodal hook
✓	x	x	✓	✓	✓	Result file + .json with the same name (outputs) + .csv file + Nodal hook
✓	✓	x	✓	✓	x	Input deck + Result file + .csv file + Nodal hook
✓	✓	x	✓	x	✓	Input deck + Result file + .json with the same name (outputs) + .csv file + Nodal hook
✓	✓	x	✓	✓	✓	Input deck + Result file + .json with the same name (outputs) + .csv file + Nodal hook