10 citations · 13 across the 4 of their papers we have counts for
3 papers · 1 filter
MeltpoolINR: Predicting temperature field, melt pool geometry, and their rate of change in laser powder bed fusion
Manav Manav, Nathanael Perraudin, Yunong Lin +4
We present a data-driven, differentiable neural network model designed to learn the temperature field, its gradient, and the cooling rate, while implicitly representing the melt po…
Calibration and Validation of a Phase-Field Model of Brittle Fracture within the Damage Mechanics Challenge
Jonas Heinzmann, Pietro Carrara, Chenyi Luo +6
In the context of the Damage Mechanics Challenge, we adopt a phase-field model of brittle fracture to blindly predict the behavior up to failure of a notched three-point-bending sp…
Phase-Field Modeling of Fracture with Physics-Informed Deep Learning
M. Manav, R. Molinaro, S. Mishra +1
We explore the potential of the deep Ritz method to learn complex fracture processes such as quasistatic crack nucleation, propagation, kinking, branching, and coalescence within t…