Physics-informed neural networks for modeling rate- and temperature-dependent plasticity

no code implementations • 20 Jan 2022 • Rajat Arora, Pratik Kakkar, Biswadip Dey, Amit Chakraborty

This work presents a physics-informed neural network (PINN) based framework to model the strain-rate and temperature dependence of the deformation fields in elastic-viscoplastic solids.

Frequency-compensated PINNs for Fluid-dynamic Design Problems

no code implementations • 3 Nov 2020 • Tongtao Zhang, Biswadip Dey, Pratik Kakkar, Arindam Dasgupta, Amit Chakraborty

We demonstrate this approach by predicting simulation results over out of range time interval and for novel design conditions.