Import and Prepare Data
What file formats can be used for training PhysicsAI models?
The file reading technology is common throughout the ecosystem, for example HyperView. For more information, see Coverage.
| Supported Solvers | File Format |
|---|---|
| Abaqus | .odb |
| AcuSolve | .ensight .h3d |
| ANSYS | .rst .rth |
| 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 |
| Radioss | .h3d .anim |
| ultraFluidX | .ensight |
Are transient simulations supported?
Yes, both transient and static simulation are supported.
How much data is needed?
The number of result files required to get good quality predictions will vary between projects, and sufficient quality is itself subjective. Some application problems may require only a handful of results, while others require dozens or even hundreds. As a general guideline, it is recommended to train with at least 10 results before assessing tests of predictive quality.
Do meshes need to have the same number of element/nodes?
No, the meshes do not require equivalent mesh. The meshes do not even need to be topologically equivalent.
How much can the design data vary?
There is no specific limit on the allowed variation in the training data. But it is informative to keep two considerations in mind. First, the training data should be representative of the type of data on which predictions will be made. Second, datasets with higher variability require a correspondingly larger number of training examples to maintain quality. When predicting, the confidence score can be used to quantify how similar the design is to the training data.
How do I include simulation entities like thickness, materials, loads, boundary conditions, and so on in my PhysicsAI training?
PhysicsAI can support simulation entities with custom features. The preferred option is native support; see this list of natively supported entities. The second best option is to use a custom hook (See Custom Inputs: Global Hook and Custom Inputs: Nodal Hook for more information) that provides flexibility to support virtually any entity via reusable and sharable code. The third choice is the predefined nodal or global hook that provides a simple entry point for working with data via a simple human readable format.
How does PhysicsAI handle your data?
You control your own data. You can install PhysicsAI in your own system like conventional CAE software. You can create projects on your file systems, and any data created by PhysicsAI remains in this location and is not moved outside of the project's context. PhysicsAI supports offloading the calculations to HPC or cloud environments, but only by customization.