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Nathaniel Trask
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Intercomparison of 3D pore-scale flow and solute transport simulation methods
X Yang, Y Mehmani, WA Perkins, A Pasquali, M Schönherr, K Kim, ...
Advances in water resources 95, 176-189, 2016
1662016
Thermodynamically consistent physics-informed neural networks for hyperbolic systems
RG Patel, I Manickam, NA Trask, MA Wood, M Lee, I Tomas, EC Cyr
Journal of Computational Physics 449, 110754, 2022
1472022
Smoothed particle hydrodynamics and its applications for multiphase flow and reactive transport in porous media
AM Tartakovsky, N Trask, K Pan, B Jones, W Pan, JR Williams
Computational Geosciences 20, 807-834, 2016
1302016
Multidimensional modeling of condensing two-phase ejector flow
M Colarossi, N Trask, DP Schmidt, MJ Bergander
International journal of refrigeration 35 (2), 290-299, 2012
1192012
A physics-informed operator regression framework for extracting data-driven continuum models
RG Patel, NA Trask, MA Wood, EC Cyr
Computer Methods in Applied Mechanics and Engineering 373, 113500, 2021
1102021
An asymptotically compatible meshfree quadrature rule for non-local problems with applications to peridynamics
N Trask, H You, Y Yu, M Parks
arxiv 1801.04488: preprint submitted to CMAME, 2018
932018
Data-driven learning of nonlocal physics from high-fidelity synthetic data
H You, Y Yu, N Trask, M Gulian, M D’Elia
Computer Methods in Applied Mechanics and Engineering 374, 113553, 2021
912021
Diesel spray CFD simulations based on the Σ-Υ Eulerian atomization model
JM Garcia-Oliver, JM Pastor, A Pandal, N Trask, E Baldwin, DP Schmidt
Atomization and Sprays 23 (1), 2013
892013
Robust training and initialization of deep neural networks: An adaptive basis viewpoint
EC Cyr, MA Gulian, RG Patel, M Perego, NA Trask
Mathematical and Scientific Machine Learning, 512-536, 2020
872020
A scalable consistent second-order SPH solver for unsteady low Reynolds number flows
N Trask, M Maxey, K Kim, M Perego, ML Parks, K Yang, J Xu
Computer Methods in Applied Mechanics and Engineering 289, 155-178, 2015
552015
Meshfree methods on manifolds for hydrodynamic flows on curved surfaces: A Generalized Moving Least-Squares (GMLS) approach
BJ Gross, N Trask, P Kuberry, PJ Atzberger
Journal of Computational Physics 409, 109340, 2020
522020
GMLS-Nets: A framework for learning from unstructured data
N Trask, RG Patel, BJ Gross, PJ Atzberger
arXiv preprint arXiv:1909.05371, 2019
522019
A high-order staggered meshless method for elliptic problems
N Trask, M Perego, P Bochev
SIAM Journal on Scientific Computing 39 (2), A479-A502, 2017
522017
Compressible modeling of the internal two-phase flow in a gas-centered swirl coaxial fuel injector
N Trask, DP Schmidt, M Lightfoot, S Danczyk
Journal of Propulsion and Power 28 (4), 685-693, 2012
462012
Machine learning structure preserving brackets for forecasting irreversible processes
K Lee, N Trask, P Stinis
Advances in Neural Information Processing Systems 34, 5696-5707, 2021
452021
Partition of unity networks: deep hp-approximation
K Lee, NA Trask, RG Patel, MA Gulian, EC Cyr
arXiv preprint arXiv:2101.11256, 2021
422021
Asymptotically compatible reproducing kernel collocation and meshfree integration for nonlocal diffusion
Y Leng, X Tian, N Trask, JT Foster
SIAM Journal on Numerical Analysis 59 (1), 88-118, 2021
392021
Scalable algorithms for physics-informed neural and graph networks
K Shukla, M Xu, N Trask, GE Karniadakis
Data-Centric Engineering 3, e24, 2022
382022
An asymptotically compatible approach for Neumann-type boundary condition on nonlocal problems
H You, XY Lu, N Task, Y Yu
ESAIM: Mathematical Modelling and Numerical Analysis 54 (4), 1373-1413, 2020
372020
Enforcing exact physics in scientific machine learning: a data-driven exterior calculus on graphs
N Trask, A Huang, X Hu
Journal of Computational Physics 456, 110969, 2022
362022
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