T. P. Miyanawala

An Efficient Deep Learning Technique for the Navier-Stokes Equations: Application to Unsteady Wake Flow Dynamics

T. P. Miyanawala, Rajeev K. Jaiman · arXiv (Cornell University) · 2017 · 95 citations · Full text

Geometric Learning, Convolutional Neural Network, Deep Neural Networks +15

Explainable Machine Learning (XML) to predict external wind pressure of a low-rise building in urban-like settings

D.P.P. Meddage, I.U. Ekanayake, A.U. Weerasuriya et al. · Journal of Wind Engineering and Industrial Aerodynamics · 2022 · 86 citations · Full text

Engineering, Machine Learning, Explainable Machine Learning +17

Partitioned iterative and dynamic subgrid-scale methods for freely vibrating square-section structures at subcritical Reynolds number

Rajeev K. Jaiman, Minyuan Guan, T. P. Miyanawala · Computers & Fluids · 2016 · 61 citations

Numerical Analysis, Unsteady Flow, Engineering +12

Decomposition of wake dynamics in fluid–structure interaction via low-dimensional models

T. P. Miyanawala, Rajeev K. Jaiman · Journal of Fluid Mechanics · 2019 · 54 citations · Full text

Numerical Analysis, Engineering, Wake Dynamics +21

A Novel Deep Learning Method for the Predictions of Current Forces on Bluff Bodies

T. P. Miyanawala, Rajeev K. Jaiman · 2018 · 20 citations

Geometric Learning, Convolutional Neural Network, Engineering +18