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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
Use Batch Mode
Learn more about using batch mode.

Welcome
What's New
View new features for HyperMesh CFD 2025.1.
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
- Morph
  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.
  - 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.
  - 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

Use Batch Mode

Learn more about using batch mode.

Note: While using hooks during prediction from the command line, the hooks directory can be specified using the --hooks_dir <hooks_path> argument. The python hook and the _predict_inp.json or predict_inp.csv should be present in the hooks directory.

Batch command for training a PhysicsAI model:

<install location>/altair/hwdesktop/hw/eds/linux/edspy.sh -physicsai -train <model name.psmdl to be trained> -dataset <path to dataset> -spec <path to model spec>

Note: In the batch command for training above, the dataset and spec files are already existing while the .psmdl file is generated after the execution of the command. You only specify the name of the PhysicsAI model.

For example, to train a model named Bracket_displacement, the command would be:

<install location>/altair/hwdesktop/hw/eds/linux/edspy.sh -physicsai -train Bracket_displacement.psmdl -dataset "C:\PhysicsAI\Ibeam_project\New folder\Bracket_train.psdata" -spec “C:\PhysicsAI\Ibeam_project\New folder\spec_24_02_21_17_29_59.pscfg”

This will train a model in batch mode and generate a model called Bracket_displacement.psmdl.

Batch command for predicting on a new mesh or CAD model:

<install location>/altair/hwdesktop/hw/eds/linux/edspy.sh -physicsai -predict_write <output file name> -model <path to model> -input_file <path to input file>

Note: On Windows, the paths above will be slightly different. For example:

<install>\hwdesktop\hw\eds\bin\win64\edspy.bat

Create a Dataset

Batch command to create a dataset:

edspy.bat --physicsai --create-dataset <dataset_path> --spec <spec_file>

<dataset_path> is the name of the dataset file you will create.

(*.psdata) <spec_file> is the path to the file that contains all the information about the dataset.