Development of a physics-informed machine learning method for aerodynamic and fluids simulation

An implementation of a non-data driven Physics Informed Neural Network (PINN) for simulation of steady state fluid flow is presented. Through the use of deep convolutional neural networks, the velocity and pressure fields were obtained by using computational fluid dynamics (CFD) simulations as compa...