Abstract. With the train speed becoming faster and faster, the aerodynamic drag turns to be one of the essential factor that restricts the train speed ascent. However, no public literature, abroad or abroad, has dealt with the flow field and aerodynamic performance of the train with the speed reaching 500km per hour. In this paper, an optimization study is carried out to reduce the aerodynamic drag of the high speed train (HST). First of all, a grid-based method is presented to parameterize the head shape of the HST, key variables are obtained by sensitivity analysis. Next, a response surface is constructed based on computational fluid dynamics (CFD) analysis to approximate the relationship of the drag and design variables at 500KPH. Finally, the genetic algorithm is used to optimize the head shape of the HST.

With the train speed becoming faster and faster, the aerodynamic drag turns to be one of the essential factor that restricts the train speed ascent. However, no public literature, home or abroad, has dealt with the flow field and aerodynamic performance of the train with the speed reaching 500 km per hour. This paper has studied in the flow field and the aerodynamic performance of the train at 500 km per hour with symmetrical and unsymmetrical nose shape. With the given two nose shape models, the authors composed four kinds train shapes and generated grids around the four train models. With the gathered and analyzed data, the paper comes to the conclusion that the unsymmetrical nose shape is better than the symmetrical one in aerodynamic performance. Comparing with the other three train shape, we found that the s-r composition best satisfies the practical demands.