Direct numerical simulation of the turbulent flow generated during a violent expiratory event A Fabregat, F Gisbert, A Vernet, S Dutta, K Mittal, J Pallarès Physics of Fluids 33 (3), 2021 | 62 | 2021 |
The target-matrix optimization paradigm for high-order meshes V Dobrev, P Knupp, T Kolev, K Mittal, V Tomov SIAM Journal on Scientific Computing 41 (1), B50-B68, 2019 | 61 | 2019 |
Nonconforming Schwarz-spectral element methods for incompressible flow K Mittal, S Dutta, P Fischer Computers & Fluids 191, 104237, 2019 | 40 | 2019 |
Reinforcement learning for adaptive mesh refinement J Yang, T Dzanic, B Petersen, J Kudo, K Mittal, V Tomov, JS Camier, ... International Conference on Artificial Intelligence and Statistics, 5997-6014, 2023 | 37 | 2023 |
Direct numerical simulation of turbulent dispersion of evaporative aerosol clouds produced by an intense expiratory event A Fabregat, F Gisbert, A Vernet, JA Ferré, K Mittal, S Dutta, J Pallarès Physics of Fluids 33 (3), 2021 | 31 | 2021 |
Mesh smoothing for the spectral element method K Mittal, P Fischer Journal of Scientific Computing 78, 1152-1173, 2019 | 30 | 2019 |
Simulation-driven optimization of high-order meshes in ALE hydrodynamics V Dobrev, P Knupp, T Kolev, K Mittal, R Rieben, V Tomov Computers & Fluids 208, 104602, 2020 | 29 | 2020 |
Multirate timestepping for the incompressible Navier-Stokes equations in overlapping grids K Mittal, S Dutta, P Fischer Journal of Computational Physics 437, 110335, 2021 | 20 | 2021 |
hr-Adaptivity for nonconforming high-order meshes with the target matrix optimization paradigm V Dobrev, P Knupp, T Kolev, K Mittal, V Tomov Engineering with Computers 38 (4), 3721-3737, 2022 | 19 | 2022 |
ARG-US remote area modular monitoring for dry casks and critical facilities H Tsai, B Craig, H Lee, K Mittal, Y Liu, J Shuler INMM 55th Annual Meeting, 2014 | 10 | 2014 |
Temperatures of Interest for the TN-32 Cask during Storage of High Burnup Fuel K Mittal, Z Han, J Li, H Tsai, Y Liu 55th Annual Institute of Nuclear Materials Management conference, 2014 | 9 | 2014 |
Multi-agent reinforcement learning for adaptive mesh refinement J Yang, K Mittal, T Dzanic, S Petrides, B Keith, B Petersen, D Faissol, ... arXiv preprint arXiv:2211.00801, 2022 | 8 | 2022 |
Adaptive surface fitting and tangential relaxation for high-order mesh optimization P Knupp, T Kolev, K Mittal, VZ Tomov arXiv preprint arXiv:2105.12165, 2021 | 8 | 2021 |
High-order mesh morphing for boundary and interface fitting to implicit geometries JL Barrera, T Kolev, K Mittal, V Tomov Computer-Aided Design 158, 103499, 2023 | 6* | 2023 |
Yet another parameter-free shape optimization method KE Swartz, K Mittal, M Schmidt, JL Barrera, S Watts, DA Tortorelli Structural and Multidisciplinary Optimization 66 (12), 245, 2023 | 5 | 2023 |
Accelerating high-order mesh optimization using finite element partial assembly on GPUs JS Camier, V Dobrev, P Knupp, T Kolev, K Mittal, R Rieben, V Tomov Journal of Computational Physics 474, 111808, 2023 | 5 | 2023 |
Impact of gaps on the flow statistics in an emergent rigid canopy P Ranjan, K Mittal, LP Chamorro, RO Tinoco Physics of Fluids 34 (6), 2022 | 5 | 2022 |
Direct numerical simulation of rotating ellipsoidal particles using moving nonconforming Schwarz-spectral element method K Mittal, S Dutta, P Fischer Computers & Fluids 205, 104556, 2020 | 5 | 2020 |
ARG-US CommBox: A Standalone Item-Based Tracking and Monitoring System B Craig, H Lee, K Byrne, K Mittal, J Scherer, H Tsai, YY Liu, J Shuler Proc. INMM 55th Annual Meeting, Atlanta, Georgia, 2014 | 5 | 2014 |
Highly scalable solution of incompressible Navier-Stokes equations using the spectral element method with overlapping grids K Mittal University of Illinois at Urbana-Champaign, 2019 | 4 | 2019 |