Aerodynamic shape optimization of an urban maglev train

With rapid development of urban rail transit, maglev trains, benefiting from its comfortable, energy-saving and environmentally friendly merits, have gradually entered people's horizons. In this paper, aiming at improving the aerodynamic performance an train, optimization design has been performed. An improved two-point infill criterion adopted to construct cross-validated Kriging model. Meanwhile, multi-objective genetic algorithm complex three-dimensional geometric parametrization method used, optimize streamlined head train. Several optimal shapes obtained. Results reveal that strategy used in paper is sufficiently accurate time-efficient for can be applied practical engineering. Compared prototype shape benefits higher lift leading car smaller drag whole Sensitivity analysis reveals length height a great influence on strong nonlinear relationships exist between these variables performance. The conclusions drawn study offer chance derive critical reference values characteristics trains.