34 citations · 34 across the 2 of their papers we have counts for
2 papers
cs.LG2026
A Physics-Regulated Neural Framework for Learning 3D Grain Growth Dynamics
Zhihui Tian, Kang Yang, Michael Tonks +2
Grain growth is governed by the reduction in grain boundary energy and exhibits well-established statistical scaling laws. Developing data-driven surrogates that preserve these phy…
physics.comp-ph2022★ 34 cited
A Novel Physics-Regularized Interpretable Machine Learning Model for Grain Growth
Weishi Yan, Joseph Melville, Vishal Yadav +6
Experimental grain growth observations often deviate from grain growth simulations, revealing that the governing rules for grain boundary motion are not fully understood. A novel d…