| An efficient deep learning technique for the Navier-Stokes equations: Application to unsteady wake flow dynamics TP Miyanawala, RK Jaiman arXiv preprint arXiv:1710.09099, 2017 | 142 | 2017 |
| Partitioned iterative and dynamic subgrid-scale methods for freely vibrating square-section structures at subcritical Reynolds number RK Jaiman, MZ Guan, TP Miyanawala Computers & Fluids 133, 68-89, 2016 | 66 | 2016 |
| Decomposition of wake dynamics in fluid–structure interaction via low-dimensional models TP Miyanawala, RK Jaiman Journal of Fluid Mechanics 867, 723-764, 2019 | 54 | 2019 |
| Explainable Machine Learning (XML) to predict external wind pressure of a low-rise building in urban-like settings DPP Meddage, IU Ekanayake, AU Weerasuriya, CS Lewangamage, ... Journal of Wind Engineering and Industrial Aerodynamics 226, 105027, 2022 | 38 | 2022 |
| A hybrid data-driven deep learning technique for fluid-structure interaction TP Miyanawala, RK Jaiman International Conference on Offshore Mechanics and Arctic Engineering 58776 …, 2019 | 26 | 2019 |
| A novel deep learning method for the predictions of current forces on bluff bodies TP Miyanawala, RK Jaiman International conference on offshore mechanics and arctic engineering 51210 …, 2018 | 23 | 2018 |
| Self-sustaining turbulent wake characteristics in fluid–structure interaction of a square cylinder TP Miyanawala, RK Jaiman Journal of Fluids and Structures 77, 80-101, 2018 | 17 | 2018 |
| Data-driven computing with convolutional neural networks for two-phase flows: Application to wave-structure interaction X Mao, V Joshi, TP Miyanawala, RK Jaiman International Conference on Offshore Mechanics and Arctic Engineering 51210 …, 2018 | 15 | 2018 |
| “A lowdimensional learning model via convolutional neural networks for unsteady wake-body interaction T Miyanawala, R Jaiman arXiv preprint arXiv:1807.09591, 2018 | 7 | 2018 |
| A hybrid data-driven deep learning technique for fluid-structure interaction TP Miyanawala, RK Jaiman arXiv preprint arXiv:1807.09591, 2018 | 4 | 2018 |
| Flow-induced vibrations of a square cylinder with combined translational and rotational oscillations TP Miyanawala, M Guan, RK Jaiman International Conference on Offshore Mechanics and Arctic Engineering 49934 …, 2016 | 4 | 2016 |
| Control of flow-induced motion in multi-column offshore platform by near-wake jets MZ Guan, K Narendran, TP Miyanawala, PF Ma, RK Jaiman International Conference on Offshore Mechanics and Arctic Engineering 57649 …, 2017 | 3 | 2017 |
| Deep learning techniques for effective prediction of aerodynamic properties of elliptical bluff bodies WMU Weerasekara, H Gunarathna, W Wanigasooriya, TP Miyanawala Fluids Engineering Division Summer Meeting 85284, V001T02A053, 2021 | 2 | 2021 |
| Analysis of Flow Induced Vibration of High Head Francis Turbine GPR Chandima, TP Miyanawala, ID Nissanka 2023 Moratuwa Engineering Research Conference (MERCon), 568-573, 2023 | 1 | 2023 |
| Real-time prediction of hydrodynamic forces and dynamic responses of a generic jack-up platform using deep learning TP Miyanawala, Y Li, YZ Law, H Santo Ocean Engineering 306, 118003, 2024 | | 2024 |
| Deep Learning Based Prediction of Hydrodynamic Forces on Offshore Platforms TP Miyanawala, Y Li, YZ Law, H Santo ASME 2023 42nd International Conference on Ocean, Offshore and Arctic …, 2023 | | 2023 |
| A hybrid data-driven deep learning technique for fluid-structure interaction R Jaiman, T Miyanawala Bulletin of the American Physical Society 65, 2020 | | 2020 |
| Using Deep Neural Networks for Data-Driven Prediction of Fluid Forces on Aerofoils T Miyanawala, P Henadeera, N Samaraweera, R Jaiman APS Division of Fluid Dynamics Meeting Abstracts, L20. 001, 2019 | | 2019 |
| DATA-DRIVEN MODELING AND DEEP LEARNING FOR FLUID-STRUCTURE INTERACTION TP MIYANAWALA | | 2019 |
| A Machine Learning Model for Unsteady Wake Dynamics T Miyanawala, R Jaiman Bulletin of the American Physical Society 63, 2018 | | 2018 |
RAJEEV K. JAIMANProfessor and NSERC/Seaspan Research Chair, University of British Columbia, Vancouver在 mech.ubc.ca 的电子邮件经过验证
