6 papers
Resource Analysis for Quantum Simulation of Spatially Varying Transport-Reaction Equations
Benjamin Jasperson, Krishna Garikipati, Siddhartha Srivastava
Spatially varying coefficients are the primary source of circuit complexity in quantum simulation of linear advection-diffusion-reaction equations. This work presents a resource an…
On Surrogate Modeling of Static Response of AM Short-Fiber Thermoplastics Using Graph Neural Networks
Pharindra Pathak, Vipin Kumar, Trenton M. Ricks +2
Short-fiber thermoplastic (SFT) composites are increasingly employed in lightweight aerospace and automotive structures owing to their favorable strength-to-weight ratio, high prod…
Bayesian Variational System Identification with Weak-Form Residual Likelihoods
Chengyang Huang, Siddhartha Srivastava, Krishna Garikipati +1
We consider system identification for discovering parameterized operators in governing partial differential equations (PDEs) from noisy spatiotemporal data. Building on variational…
Equivariant graph neural network surrogates for predicting the properties of relaxed atomic configurations
Jamie Holber, Siddhartha Srivastava, Krishna Garikipati
Density functional theory (DFT) calculations determine the relaxed atomic positions and lattice parameters that minimize the formation energy of a structure. We present an equivari…
Constitutive parameter inference using physics-based data-driven modeling in full volume datasets of intact and torn rotator cuff tendons
Carla Nathaly VillacÃs Núñez, Siddhartha Srivastava, Ulrich Scheven +3
In this work, we characterized the material properties of an animal model of the rotator cuff tendon using full volume datasets of both its intact and injured states by capturing i…
Inference of phase field fracture models
Elizabeth Livingston, Siddhartha Srivastava, Jamie Holber +2
The phase field approach to modeling fracture uses a diffuse damage field to represent a crack. This addresses the singularities that arise at the crack tip in computations with sh…