Abstract: Machine learning offers a powerful tool for predicting heat transfer in lid-driven cavities, a well-known problem in fluid mechanics. This study compared various ML regression models and ...

If you have trouble following the instruction below, feel free to join OSCER weekly zoom help sessions. If you're doing deep learning neural network research, tensorflow need no introduction. It is ...

ABSTRACT: The formulation and implementation of a high-order Cartesian cut-stencil finite difference method (CCST-FDM) to 2-D steady incompressible fluid flow in regular and irregular domains is ...

Python code for solving Napier Stokes equation using finite volume method in the scenario of Lid driven flow. The quasi Rhie Chow algorithm has been implemented to arrive at the solution. VLEO-DSMC ...

A Physics-Informed Neural Network that solves the 2D steady incompressible Navier-Stokes equations on a lid-driven cavity, validated against the Ghia et al. (1982) benchmark. Physics-Informed Neural ...

The formulation and implementation of a high-order Cartesian cut-stencil finite difference method (CCST-FDM) to 2-D steady incompressible fluid flow in regular and irregular domains is considered in ...

Chronic left-to-right shunting, as occurs with congenital heart disease or persistent ductus-like flow, exposes pulmonary circulation to sustained high-flow shear and pulsatile pressure and causes ...