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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.
A Python tool for extrapolating compressive stress-strain data to ideal frictionless conditions using linear regression over multiple specimen geometries
Exploratory Project based on ML models predicting outcomes for various uses. Designed the frontend on HTML and styled using Tailwind CSS. Integrated ML using Flask.
🧭 Sundered Core SRD for a unified Source pool tabletop RPG focused on agency, tactics, and real costs. Burn resources, trade effects, and counter every move.