4 papers
Acoustics-based Active Control of Unsteady Flow Dynamics using Reinforcement Learning Driven Synthetic Jets
Siddharth Rout, Khai Phan, Chao-An Lin
Flow generated noise are caused shear flows and, hence, they can be used as feedback to control the flow. Existing flow control uses state variables like velocity, pressure, or vor…
PINN for Dynamical Partial Differential Equations is Not Training Deeper Networks Rather Learning Advection and Time Variance
Siddharth Rout
The concepts and techniques of physics-informed neural networks (PINNs) is studied and limitations are identified to make it efficient to approximate dynamical equations. Potential…
Airfoil Shape Optimization using Deep Q-Network
Siddharth Rout, Chao-An Lin
The feasibility of using reinforcement learning for airfoil shape optimization is explored. Deep Q-Network (DQN) is used over Markov's decision process to find the optimal shape by…
Numerical Approximation in CFD Problems Using Physics Informed Machine Learning
Siddharth Rout, Vikas Dwivedi, Balaji Srinivasan
The thesis focuses on various techniques to find an alternate approximation method that could be universally used for a wide range of CFD problems but with low computational cost a…