124 citations · 127 across the 3 of their papers we have counts for
3 papers
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…
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…
Laser Micromachining of Coated YBa2Cu3O6+x Superconducting Thin Films
Kenneth E. Hix, Matthew C. Rendina, James L. Blackshire +1
Over the last decade advances in high temperature superconducting (HTS) materials have generated a renewed optimism in the use of this technology in future high-power applications…