T. P. Miyanawala

发表

Convolutional Neural Networks for Wake Flow Predictions

T. P. Miyanawala, Rajeev K. Jaiman, 2017 .

A Machine Learning Model for Unsteady Wake Dynamics

T. P. Miyanawala, Rajeev K. Jaiman, 2018 .

Data-Driven Computing With Convolutional Neural Networks for Two-Phase Flows: Application to Wave-Structure Interaction

Vaibhav Joshi, T. P. Miyanawala, Rajeev K. Jaiman, 2018, Volume 2: CFD and FSI.

A Hybrid Data-driven Deep Learning Technique for Fluid-Structure Interaction

T. P. Miyanawala, R. K. Jaiman, 2018 .

Using Deep Neural Networks for Data-Driven Prediction of Fluid Forces on Aerofoils

T. P. Miyanawala, Rajeev K. Jaiman, Pasan Henadeera, 2019 .

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

T. P. Miyanawala, R. Jaiman, 2018, Journal of Fluid Mechanics.

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

T. P. Miyanawala, Rajeev K. Jaiman, R. Jaiman, 2017, 1710.09099.

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

T. P. Miyanawala, Rajeev K. Jaiman, R. Jaiman, 2016 .

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

T. P. Miyanawala, Rajeev K. Jaiman, 2018, Volume 2: CFD and FSI.

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

T. P. Miyanawala, A. U. Weerasuriya, C. Ramanayaka, 2022, Journal of Wind Engineering and Industrial Aerodynamics.

A Hybrid Data-Driven Deep Learning Technique for Fluid-Structure Interaction

T. P. Miyanawala, R. Jaiman, 2018, Volume 2: CFD and FSI.

Flow-Induced Vibrations of a Square Cylinder With Combined Translational and Rotational Oscillations

T. P. Miyanawala, R. Jaiman, M. Guan, 2016 .

Self-sustaining turbulent wake characteristics in fluid–structure interaction of a square cylinder

T. P. Miyanawala, R. Jaiman, 2018 .