| 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 | 207 | 2022 |
| 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 | 189 | 2016 |
| 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 | 150 | 2021 |
| 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 (4), 807-834, 2016 | 143 | 2016 |
| 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 | 131 | 2012 |
| 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 | 115 | 2020 |
| 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 | 104 | 2021 |
| 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 | 99 | 2018 |
| 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 | 92 | 2013 |
| 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 | 69 | 2021 |
| Scalable algorithms for physics-informed neural and graph networks K Shukla, M Xu, N Trask, GE Karniadakis Data-Centric Engineering 3, e24, 2022 | 67 | 2022 |
| 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 | 67 | 2020 |
| 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 | 62 | 2017 |
| 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 | 60 | 2015 |
| GMLS-Nets: A framework for learning from unstructured data N Trask, RG Patel, BJ Gross, PJ Atzberger arXiv preprint arXiv:1909.05371, 2019 | 59 | 2019 |
| Partition of unity networks: deep hp-approximation K Lee, NA Trask, RG Patel, MA Gulian, EC Cyr arXiv preprint arXiv:2101.11256, 2021 | 58 | 2021 |
| 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 | 50 | 2022 |
| 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 | 48 | 2012 |
| 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 | 45 | 2020 |
| 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 | 43 | 2021 |
Ravi G PatelScientist, Sandia National LabsVerified email at sandia.gov
