124 citations · 125 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2021★ 124 cited
A physics-informed neural network for quantifying the microstructure properties of polycrystalline Nickel using ultrasound data
Khemraj Shukla, Ameya D. Jagtap, James L. Blackshire +2
We employ physics-informed neural networks (PINNs) to quantify the microstructure of a polycrystalline Nickel by computing the spatial variation of compliance coefficients (compres…
cs.LG2020★ 1 cited
Physics-informed neural network for ultrasound nondestructive quantification of surface breaking cracks
Khemraj Shukla, Patricio Clark Di Leoni, James Blackshire +2
We introduce an optimized physics-informed neural network (PINN) trained to solve the problem of identifying and characterizing a surface breaking crack in a metal plate. PINNs are…