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Entry № 001 · work · 2021

Machine Learning for Metal Manufacturing

Data-driven prediction of process–microstructure–property–performance relationships for cast and additively manufactured metals.

STATUS

ongoing

CATEGORY

work

YEAR

2021

TAGS

machine-learning · additive-manufacturing · metals · materials-science

Overview

Process decisions in metal casting and additive manufacturing propagate through microstructure into the final mechanical properties and part performance. This project builds ML surrogates that tie those stages together so that process parameters can be selected against a target performance envelope without running the full physical experiment loop every time.

Status

Ongoing. Public write-up pending — check back later.

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Data-Driven Metamaterials Design

2020 · academic