Solutions of Navier Stokes equation and application on aerodynamics

Abstract

The Navier-Stocks equation (NSE) was derived based on Newtons second law and Eulers equation with the viscosity effect. The continuity of mass, conservation of momentum and energy contribute to the motion of fluid. This paper discusses the hypothesis and theories of the solution of the 3D NSE corresponding to the boundary and initial conditions from previous research. Meanwhile, this paper focuses on the study of solutions and turbulence models of NSE contributed to the applications of aerodynamics. Machine Learning and Neural Networks are applied to the solution of the NSE to improve the accuracy of prediction of fluid motion. Aerodynamics applications on airfoil, turbulence model, design of propeller and ejection seats are discussed with analysis of solutions of Navier-Stocks equation. With the contribution of Machine learning, accurate and global solutions are expected to be computed for the NSE in the future.