Aerodynamic Optimization of Lowdrag Vehicle with Internal Flow Based on Genetic Algorithm

Abstract:

A parametric model of 18 parameters was established and a global optimization method based on genetic algorithm was developed. The aerodynamic optimization of the vehicle body with internal flow was carried out and a low-drag optimization shape with aerodynamic drag coefficient of 0.261 was obtained. Comparing the results of numerical simulation and test, it is found that the difference in aerodynamic drag coefficient is only 4%. The surface pressure coefficient and different cross-section velocity contours have the same distribution and small difference of magnitude, which indicates that the numerical simulation method is correct and feasible. Through the energy decomposition of the flow field in the tail section using the Proper Orthogonal Decomposition, it can be observed that the first nine modes occupy 54.5% of the total energy. Among them, the first-order mode with the highest energy shows the shape of the tail drag vortex and its vortex position does not change with time. In this paper, the global optimization method of the vehicle with internal flow was established, and the low-drag model with internal flow was validated by test, which can provide a method and reference for the development of related products.