Automated Meshless CFD Process using Cartesian Point Distribution

Abstract

The thesis deals with the meshless methods based on generalized finite difference procedure operating on the mere distribution of points. The work per se focuses on maturing the meshless LSFD-U solver as a standard industrial tool for Aerospace CFD. One of the purported advantages of this class of methods as opposed to finite- volume methods is that they can considerably ease the need for generating grids. This aspect has been truly exploited in this thesis by projecting the meshless LSFD-U solver as a Cartesian grid methodology. The point distribution required by the LSFD-U solver is obtained from Cartesian grids. The Cartesian grid with its immense potential for process automation and the LSFD-U method with its ability to discretize the conservation equations on any arbitrary point distribution, form a natural pair for solving complex engineering problems in an automated process. The thesis presents a number of complex configurations of industrial relevance where the point distribution for the meshless solver are obtained from Cartesian grids in short turn-around times and without any human intervention. The grid convergence of the 3D inviscid solver is also established on a sequence of Cartesian point distributions. The automation capability is one of the key requirements for solving multi-body dynamics, moving body and optimization problems. The CFD process on such problems primarily involves repetitive grid generation. Any need for human intervention and expertise in the CFD process seriously hampers the overall performance and productivity. The meshless LSFD-U solver offers complete automation in the CFD process regardless of the complexity in the configurations...