62 citations · 198 across the 13 of their papers we have counts for
5 papers · 1 filter
Robust, strong form mechanics on an adaptive structured grid: efficiently solving variable-geometry near-singular problems with diffuse interfaces
Vinamra Agrawal, Brandon Runnels
Many solid mechanics problems on complex geometries are conventionally solved using discrete boundary methods. However, such an approach can be cumbersome for problems involving ev…
A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks
Roberto Perera, Vinamra Agrawal
Despite their recent success, machine learning (ML) models such as graph neural networks (GNNs), suffer from drawbacks such as the need for large training datasets and poor perform…
Investigating shock wave propagation, evolution, and anisotropy using a moving window concurrent atomistic-continuum framework
Alexander S. Davis, Vinamra Agrawal
Despite their success in microscale modeling of materials, atomistic methods are still limited by short time scales, small domain sizes, and high strain rates. Multiscale formulati…
Dynamic and adaptive mesh-based graph neural network framework for simulating displacement and crack fields in phase field models
Roberto Perera, Vinamra Agrawal
Fracture is one of the main causes of failure in engineering structures. Phase field methods coupled with adaptive mesh refinement (AMR) techniques have been widely used to model c…
Transmitting multiple high-frequency waves across length scales using the concurrent atomistic-continuum method
Alexander S. Davis, Vinamra Agrawal
Coupled atomistic-continuum methods can describe large domains and model dynamic material behavior for a much lower computational cost than traditional atomistic techniques. Howeve…