4 citations · 6 across the 2 of their papers we have counts for
3 papers
cs.CE2025
Integrated physics-informed learning and resonance process signature for the prediction of fatigue crack growth for laser-fused alloys
Panayiotis Kousoulas, Rahul Sharma, Y. B. Guo
Fatigue behaviors of metal components by laser fusion suffer from scattering due to random geometrical defects (e.g., porosity, lack of fusion). Monitoring fatigue crack initiation…
cs.LG2025★ 2 cited
Computational, Data-Driven, and Physics-Informed Machine Learning Approaches for Microstructure Modeling in Metal Additive Manufacturing
D. Patel, R. Sharma, Y. B. Guo
Metal additive manufacturing enables unprecedented design freedom and the production of customized, complex components. However, the rapid melting and solidification dynamics inher…
cs.LG2024★ 4 cited
Physics-Informed Machine Learning for Smart Additive Manufacturing
Rahul Sharma, Maziar Raissi, Y. B. Guo
Compared to physics-based computational manufacturing, data-driven models such as machine learning (ML) are alternative approaches to achieve smart manufacturing. However, the data…