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Vinamra Agrawal

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cond-mat.mtrl-sci1
  • cs.CE1
  • cs.LG1
ORCID 0000-0002-1698-1371

identity via Semantic Scholar / OpenAlex

most citedMultiscale graph neural networks with adaptive mesh refinement for accelerating mesh-based simulations

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2025

A Foundation Model for Material Fracture Prediction

Agnese Marcato, Aleksandra Pachalieva, Ryley G. Hill +14

Accurately predicting when and how materials fail is critical to designing safe, reliable structures, mechanical systems, and engineered components that operate under stress. Yet,…

cond-mat.mtrl-sci2024

Ductile fracture in functionally graded materials: Insight into crack behavior within the gradient interface

Katherine Piper, Vinamra Agrawal

Despite advances in manufacturing making metal functionally graded materials (FGMs) more common, numerical methods for predicting fracture in ductile functionally graded materials…

cs.CE2024★ 1 cited

Multiscale graph neural networks with adaptive mesh refinement for accelerating mesh-based simulations

Roberto Perera, Vinamra Agrawal

Mesh-based Graph Neural Networks (GNNs) have recently shown capabilities to simulate complex multiphysics problems with accelerated performance times. However, mesh-based GNNs requ…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.