| Quantification of Reynolds-averaged-Navier–Stokes model-form uncertainty in transitional boundary layer and airfoil flows M Chu, X Wu, DE Rival Physics of Fluids 34 (10), 2022 | 12 | 2022 |
| Model-form uncertainty quantification of Reynolds-averaged Navier–Stokes modeling of flows over a SD7003 airfoil M Chu, X Wu, DE Rival Physics of Fluids 34 (11), 2022 | 11 | 2022 |
| Multi-fidelity Deep Learning-based methodology for epistemic uncertainty quantification of turbulence models M Chu, W Qian arXiv preprint arXiv:2310.14331, 2023 | 2 | 2023 |
| Physics Based & Machine Learning Methods For Uncertainty Estimation In Turbulence Modeling M Chu arXiv preprint arXiv:2407.10615, 2024 | 1 | 2024 |
| Physics Constrained Deep Learning For Turbulence Model Uncertainty Quantification M Chu, W Qian arXiv preprint arXiv:2405.16554, 2024 | 1 | 2024 |
| A Deep Learning Approach For Epistemic Uncertainty Quantification Of Turbulent Flow Simulations M Chu, W Qian arXiv preprint arXiv:2405.08148, 2024 | 1 | 2024 |
| Convolutional Neural Networks For Turbulent Model Uncertainty Quantification M Chu, W Qian arXiv preprint arXiv:2408.06864, 2024 | | 2024 |
| Developing a Model-Consistent Reduced-Dimensionality training approach to quantify and reduce epistemic uncertainty in separated flows M Chu arXiv preprint arXiv:2408.00120, 2024 | | 2024 |
| Uncertainty Quantification in Computational Fluid Dynamics: Physics and Machine Learning Based Approaches M Chu arXiv preprint arXiv:2312.14684, 2023 | | 2023 |
| Uncertainty Quantification For Turbulent Flows with Machine Learning M Chu, W Qian arXiv preprint arXiv:2310.11435, 2023 | | 2023 |
| Multi-Fidelity Data Assimilation For Physics Inspired Machine Learning In Uncertainty Quantification Of Fluid Turbulence Simulations M Chu, W Qian arXiv preprint arXiv:2307.12453, 2023 | | 2023 |
| Quantification of Reynolds-averaged-Navier-Stokes Model Structural Hypothesis Uncertainty in Transitional Boundary Layer and Airfoil Flows M Chu Queen's University, 2022 | | 2022 |
| Prediction of turbulent flow over a flat plate with a step change from a smooth to a rough surface using a near-wall RANS model M Chu, DJ Bergstrom Journal of Fluids Engineering 142 (1), 011202, 2020 | | 2020 |
| ThesisMinghanChu2018 M Chu University of Saskatchewan, 2018 | | 2018 |
| Prediction of an internal boundary layer on a flat plate after a step change in roughness using a near-wall RANS model M Chu, F Meng, DJ Bergstrom APS Division of Fluid Dynamics Meeting Abstracts, G31. 007, 2017 | | 2017 |
David E. RivalProfessor, Institute of Fluid Mechanics, TU Braunschweig在 tu-braunschweig.de 的电子邮件经过验证
