GitHub / 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.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beingujjwalraj%2FMultiscale-Modelling-of-Material-Using-Machine-Learning

Topics: abaqus, ansys, finite-element-analysis, fortran, hall-petch-effect, heattransfer, machine-learning, materialoptimization, multiscale-modeling, polynomialregression, stress-strain, umat, vpsc

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