Creating Datasets for Simulation Models with PyMAPDL – Lesson 4

AI/ML Datasets using PyMAPDL Creating Datasets for Simulation Models with PyMAPDL – Lesson 4

This lesson features Ansys’ PyMAPDL tool, focusing on utilizing the “Pools” class to enhance computational efficiency. With the help of an example, it demonstrates how to create a synthetic dataset for AI/ML-based applications. For situations involving intense computation, the Pools class enables running multiple instances of MAPDL in parallel, distributing the workload across cores for a faster and efficient execution. The lesson discusses two methods for dealing with the Pools, namely creating the input files and defining a Python function that encapsulates MAPDL and the finite element method (FEM). The lesson explains the script and the procedure for setting up the model, mesh refinement, the solution, and post-processing details.