{"data":{"full_name":"beingujjwalraj/Multiscale-Modelling-of-Material-Using-Machine-Learning","name":"Multiscale-Modelling-of-Material-Using-Machine-Learning","description":"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.","stars":8.0,"forks":6.0,"language":"Jupyter Notebook","license":null,"archived":0.0,"subcategory":"chemical-property-ml","last_pushed_at":"2024-12-05T17:47:24+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":0.0,"adoption_score":4.0,"maturity_score":8.0,"community_score":16.0,"quality_score":28.0,"quality_tier":"experimental","risk_flags":"['no_license', 'stale_6m', 'no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-08T11:26:44.107203+00:00"}}