[02224] Numerical simulation of convective flow models in porous media using deep learning technique
Session Time & Room : 2D (Aug.22, 15:30-17:10) @D404
Type : Contributed Talk
Abstract : The outstanding computational ability of artificial neural networks (ANN) makes the deep learning (DL) branch more robust for solving various simple and complex convective models $\left(2D ~and~3D\right)$ in porous media. Moreover, it is an unsupervised learning approach in the DL that uses randomly sampled spatial and boundary collocation points as training data for ANN. A loss function according to the governing and boundary conditions is formulated and enforced to minimize at the sampled collocation points through the backpropagation algorithm using suitable optimization techniques. Eventually, a fine-tuned ANN is achieved after a sufficiently large number of training processes, and the tunned ANN is used to replicate the solution quickly.