| Using machine learning to construct velocity fields from OH-PLIF images S Barwey, M Hassanaly, V Raman, A Steinberg Combustion Science and Technology 194 (1), 93-116, 2022 | 40 | 2022 |
| Data-driven classification and modeling of combustion regimes in detonation waves S Barwey, S Prakash, M Hassanaly, V Raman Flow, Turbulence and Combustion 106, 1065-1089, 2021 | 36 | 2021 |
| A neural network-inspired matrix formulation of chemical kinetics for acceleration on gpus S Barwey, V Raman Energies 14 (9), 2710, 2021 | 30 | 2021 |
| Highly-scalable GPU-accelerated compressible reacting flow solver for modeling high-speed flows R Bielawski, S Barwey, S Prakash, V Raman Computers & Fluids 265, 105972, 2023 | 25 | 2023 |
| Experimental data-based reduced-order model for analysis and prediction of flame transition in gas turbine combustors S Barwey, M Hassanaly, Q An, V Raman, A Steinberg Combustion Theory and Modelling 23 (6), 994-1020, 2019 | 23 | 2019 |
| Data-based analysis of multimodal partial cavity shedding dynamics S Barwey, H Ganesh, M Hassanaly, V Raman, S Ceccio Experiments in Fluids 61, 1-21, 2020 | 20 | 2020 |
| Extracting information overlap in simultaneous OH-PLIF and PIV fields with neural networks S Barwey, V Raman, AM Steinberg Proceedings of the Combustion Institute 38 (4), 6241-6249, 2021 | 17 | 2021 |
| Multiscale Graph Neural Network Autoencoders for Interpretable Scientific Machine Learning S Barwey, V Shankar, V Viswanathan, R Maulik Journal of Computational Physics, 112537, 2023 | 16 | 2023 |
| Data-driven analysis of relight variability of jet fuels induced by turbulence M Hassanaly, Y Tang, S Barwey, V Raman Combustion and Flame 225, 453-467, 2021 | 12 | 2021 |
| A data-driven reduced-order model for stiff chemical kinetics using dynamics-informed training V Vijayarangan, HA Uranakara, S Barwey, RM Galassi, MR Malik, ... Energy and AI 15, 100325, 2024 | 11 | 2024 |
| A generative adversarial network (GAN) approach to creating synthetic flame images from experimental data A Carreon, S Barwey, V Raman Energy and AI 13, 100238, 2023 | 10 | 2023 |
| Data-driven reduction and decomposition with time-axis clustering S Barwey, V Raman Proceedings of the Royal Society A 479 (2274), 20220776, 2023 | 10* | 2023 |
| Accelerating turbulent reacting flow simulations on many-core/GPUs using matrix-based kinetics HA Uranakara, S Barwey, FEH Pérez, V Vijayarangan, V Raman, HG Im Proceedings of the Combustion Institute 39 (4), 5127-5136, 2023 | 3 | 2023 |
| Segmentation of high-speed flow fields using physics-informed clustering M Ullman, S Barwey, GS Lee, V Raman Applications in Energy and Combustion Science 15, 100181, 2023 | 2 | 2023 |
| Importance of equivariant and invariant symmetries for fluid flow modeling V Shankar, S Barwey, Z Kolter, R Maulik, V Viswanathan arXiv preprint arXiv:2307.05486, 2023 | 2 | 2023 |
| Data-driven modeling of compressible reacting flow using hardware-oriented algorithms S Barwey | 2 | 2022 |
| Jacobian-scaled K-means clustering for physics-informed segmentation of reacting flows S Barwey, V Raman Journal of Computational Physics, 113227, 2024 | 1 | 2024 |
| Detonation structure in the presence of mixture stratification using reaction-resolved simulations M Ullman, S Prakash, S Barwey, V Raman Combustion and Flame 264, 113427, 2024 | 1 | 2024 |
| Interpretable Fine-Tuning for Graph Neural Network Surrogate Models S Barwey, R Maulik arXiv preprint arXiv:2311.07548, 2023 | 1 | 2023 |
| Impact of operator splitting schemes on detonation convergence S Barwey, V Raman APS Division of Fluid Dynamics Meeting Abstracts, Q03. 001, 2021 | 1 | 2021 |
Venkat RamanProfessor, University of Michigan在 umich.edu 的电子邮件经过验证
