Enriching MRI mean flow data of inclined jets in crossflow with Large Eddy Simulations PM Milani, IE Gunady, DS Ching, AJ Banko, CJ Elkins, JK Eaton International Journal of Heat and Fluid Flow 80, 108472, 2019 | 21 | 2019 |
Shear layer of inclined jets in crossflow studied with spectral proper orthogonal decomposition and spectral transfer entropy PM Milani, DS Ching, AJ Banko, JK Eaton International Journal of Heat and Mass Transfer 147, 118972, 2020 | 15 | 2020 |
Investigation of geometric sensitivity of a non-axisymmetric bump: 3D mean velocity measurements DS Ching, CJ Elkins, JK Eaton Experiments in Fluids 59, 1-14, 2018 | 13 | 2018 |
Reduced order modeling of hypersonic aerodynamics with grid tailoring D Ching, PJ Blonigan, F Rizzi, JA Fike AIAA SCITECH 2022 Forum, 1247, 2022 | 11* | 2022 |
Large-eddy simulation study of unsteady wake dynamics and geometric sensitivity on a skewed bump DS Ching, JK Eaton Journal of Fluid Mechanics 885, 2020 | 11 | 2020 |
Unsteady vortex structures in the wake of nonaxisymmetric bumps using spiral MRV DS Ching, CJ Elkins, MT Alley, JK Eaton Experiments in Fluids 59, 1-17, 2018 | 10 | 2018 |
Machine Learning Modeling for RANS Turbulent Kinetic Energy Transport in 3D Separated Flows DS Ching, AJ Banko, PM Milani, JK Eaton 11th International Symposium on Turbulence and Shear Flow Phenomena, 2019 | 6 | 2019 |
Turbulence modeling for compressible flows using discrepancy tensor-basis neural networks and extrapolation detection E Parish, DS Ching, NE Miller, SJ Beresh, MF Barone AIAA SciTech 2023 Forum, 2126, 2023 | 4 | 2023 |
Sensitivity-informed bayesian inference for home PLC network models with unknown parameters DS Ching, C Safta, TA Reichardt Energies 14 (9), 2402, 2021 | 4 | 2021 |
3D Measurements of coupled freestream turbulence and secondary flow effects on film cooling DS Ching, HHA Xu, CJ Elkins, JK Eaton Experiments in Fluids 59, 1-16, 2018 | 4 | 2018 |
Efficient sampling methods for machine learning error models with application to surrogates of steady hypersonic flows EH Krath, DS Ching, PJ Blonigan AIAA SCITECH 2022 Forum, 1249, 2022 | 3 | 2022 |
Industrial PLC Network Modeling and Parameter Identification Using Sensitivity Analysis and Mean Field Variational Inference R Wonnacott, DS Ching, J Chilleri, C Safta, L Rashkin, TA Reichardt Sensors 23 (5), 2416, 2023 | 2 | 2023 |
WITHDRAWAL: Lipshitz-continuous tensor-basis neural networks for turbulence modeling in hypersonic flows E Parish, DS Ching, NE Miller, S Beresh, MF Barone, N Gupta, ... AIAA SCITECH 2024 Forum, 0070, 2024 | 1 | 2024 |
Residual minimization formulations for model reduction of steady hypersonic flow RL Van Heyningen, DS Ching, PJ Blonigan, EJ Parish, F Rizzi AIAA Aviation 2023 Forum, 3267, 2023 | 1 | 2023 |
On correcting the eddy-viscosity models in RANS simulations for turbulent flows and scalar transport around obstacles Z Hao, C Gorlé, DS Ching, JK Eaton arXiv preprint arXiv:2206.14469, 2022 | 1 | 2022 |
Reduced Order Models of Hypersonic Aerodynamics for Aerothermal Heating Analysis DS Ching, PJ Blonigan, MC Sands, JC Murray AIAA SCITECH 2024 Forum, 1293, 2024 | | 2024 |
A data-driven turbulence modeling framework for the Reynolds-averaged Navier-Stokes equations via discrepancy-based tensor-basis neural networks. E Parish, M Barone, N Miller, D Ching, S Beresh Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Grid Tailored Reduced-Order Models for Steady Hypersonic Aerodynamics. D Ching, P Blonigan, M Arienti, F Rizzi, J Fike Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021 | | 2021 |
Quantifying the impact of the initial guess for projection-based model reduction of steady hypersonic aerodynamics. D Ching, PJ Blonigan, F Rizzi, M Howard, JA Fike Sandia National Lab.(SNL-CA), Livermore, CA (United States); Sandia National …, 2020 | | 2020 |
Machine Learning Uncertainty Quantification for Reduced Order Models of Hypersonic Flows. D Ching, PJ Blonigan Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2020 | | 2020 |