beingujjwalraj/Multiscale-Modelling-of-Material-Using-Machine-Learning

This repository demonstrates multiscale modeling of copper heat pipes using machine learning, integrating grain-scale data with FEA via a UMAT. It highlights grain size’s impact on stress, strain, and heat transfer for optimized material design.

Language: Jupyter Notebook - Size: 9.33 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0