Study on the optimization f a slotted hydrofoil using Genetic algorithm (C++ and Matlab)

In this project, first sampling in the optimization space is done using Latin Hypercube Sampling (LHS) method. Then a set of simulations are done by calling a FV-based fluid flow solver in Matlab to train a surrogate based model which is Gaussian regression (Kriging metamodel). Then a genetic algotithm is used to do a multi objective optimization ,and finally a design point is selected in the Pareto front. In the part of the solver, I wrote a finite volume method to discretize Euler or Navier-Stokes equations. It can uses different methods including Jameson, MUSCL and Frink. There are also different options for numerical fluxes: Roe, AUSM family, Lax, HLL, HHLC, LDFS It can accurately and quickly simulate different incompressible/compressible single-/two-phase fluid flows with/without cavitation. More details can be found here