Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid Simulations

1 code implementation • 9 Jul 2021 • Pranshu Pant, Ruchit Doshi, Pranav Bahl, Amir Barati Farimani

Reduced Order Modelling (ROM) has been widely used to create lower order, computationally inexpensive representations of higher-order dynamical systems.

Dimensionality Reduction

State estimation with limited sensors -- A deep learning based approach

no code implementations • 27 Jan 2021 • Yash Kumar, Pranav Bahl, Souvik Chakraborty

We illustrate that utilizing sequential data allows for state recovery from only one or two sensors.