| Lagrangian large eddy simulations via physics-informed machine learning Y Tian, M Woodward, M Stepanov, C Fryer, C Hyett, D Livescu, ... Proceedings of the National Academy of Sciences 120 (34), e2213638120, 2023 | 7 | 2023 |
| Physics informed machine learning of SPH: Machine learning lagrangian turbulence MJ Woodward, Y Tian, C Hyett, C Fryer, D Livescu, M Stepanov, ... | 7 | 2021 |
| Physics-informed machine learning with smoothed particle hydrodynamics: Hierarchy of reduced Lagrangian models of turbulence M Woodward, Y Tian, C Hyett, C Fryer, M Stepanov, D Livescu, ... Physical Review Fluids 8 (5), 054602, 2023 | 6 | 2023 |
| Control of line pack in natural gas system: Balancing limited resources under uncertainty C Hyett, L Pagnier, J Alisse, L Sabban, I Goldshtein, M Chertkov PSIG Annual Meeting, PSIG-2314, 2023 | 2 | 2023 |
| Machine learning statistical lagrangian geometry of turbulence C Hyett, M Chertkov, Y Tian, D Livescu APS Division of Fluid Dynamics Meeting Abstracts, S01. 024, 2020 | 2 | 2020 |
| Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning M Chertkov, Y Tian, M Stepanov, C Fryer, M Woodward, C Hyett, ... Bulletin of the American Physical Society 67, 2022 | 1 | 2022 |
| Machine Learning Lagrangian Large Eddy Simulations with Smoothed Particle Hydrodynamics Y Tian, M Chertkov, M Woodward, M Stepanov, C Fryer, C Hyett, ... APS Division of Fluid Dynamics Meeting Abstracts, A11. 008, 2021 | 1 | 2021 |
| Machine Learning Statistical Evolution of the Coarse-Grained Velocity Gradient Tensor C Hyett, M Chertkov, Y Tian, D Livescu, M Stepanov APS Division of Fluid Dynamics Meeting Abstracts, E31. 009, 2021 | 1 | 2021 |
| Quantifying Structural Reliability in Off-Shore Wind Turbines: Sampling, Instanton, and Sensitivity Analysis Y Liu, C Hyett, M Chertkov Bulletin of the American Physical Society, 2023 | | 2023 |
| Velocity gradient prediction using parameterized Lagrangian deformation models C Hyett, Y Tian, M Stepanov, D Livescu, M Chertkov Bulletin of the American Physical Society, 2023 | | 2023 |
| System-Wide Emergency Policy for Transitioning from Main to Secondary Fuel L Pagnier, I Goldshtein, C Hyett, R Ferrando, J Alisse, L Saban, ... arXiv preprint arXiv:2311.08686, 2023 | | 2023 |
| Differentiable Simulator For Dynamic & Stochastic Optimal Gas & Power Flows C Hyett, L Pagnier, J Alisse, I Goldshtein, L Saban, R Ferrando, ... arXiv preprint arXiv:2310.18507, 2023 | | 2023 |
| Applicability of Machine Learning Methodologies to Model the Statistical Evolution of the Coarse-Grained Velocity Gradient Tensor C Hyett, Y Tian, M Woodward, M Chertkov, D Livescu, M Stepanov Bulletin of the American Physical Society 67, 2022 | | 2022 |
| Physics Informed Machine Learning with Smoothed Particle Hydrodynamics: Compressiblity and Shocks M Woodward, Y Tian, C Hyett, C Fryer, D Livescu, M Stepanov, ... Bulletin of the American Physical Society 67, 2022 | | 2022 |
| Physics-informed Machine Learning for Reduced-order Modeling of Lagrangian Turbulence Y Tian, M Woodward, M Stepanov, C Fryer, C Hyett, M Chertkov, ... APS March Meeting Abstracts 2022, S49. 006, 2022 | | 2022 |
| Intended for: Web MJ Woodward, Y Tian, CM Hyett, CL Fryer, D Livescu, M Stepanov, ... arXiv preprint arXiv:2110.13311, 2021 | | 2021 |
| Data-Analysis of the Coarse-Grained Velocity Gradient Tensor C Hyett, Y Tian, M Chertkov, D Livescu, M Stepanov APS Division of Fluid Dynamics Meeting Abstracts, N01. 011, 2021 | | 2021 |
| Physics Informed Machine Learning of Smooth Particle Hydrodynamics: Validation of the Lagrangian Turbulence Approach M Woodward, Y Tian, M Chertkov, M Stepanov, D Livescu, C Hyett, ... APS Division of Fluid Dynamics Meeting Abstracts, T24. 008, 2021 | | 2021 |
| Physics Informed Machine Learning of Smooth Particle Hydrodynamics: Solving Inverse Problems using a mixed mode approach M Woodward, M Chertkov, Y Tian, M Stepanov, D Livescu, C Hyett, ... APS Division of Fluid Dynamics Meeting Abstracts, N01. 050, 2021 | | 2021 |
