Study On Key Technologies Of Mulitidisciplinary Design Optimization Of High-speed Train Shape

As the train speed up, many aerodynamic problems are being raised with regard to aerodynamic drag, impulse forces occurring as two trains intersect each other, the safety of high speed train, impulse wave at the exit of tunnel, and so on. Many factors are responsible for these problems, but from the view of aerodynamics, the shape of the high speed train plays a key role. So the study about the shape design and optimization has arosed widely attention in the academic community and the railway industry.While most researches have been limited within one disciplinary or one line case, no global optima could be obtained without considering the coupling effects among those different disciplinaries or line cases.Under the above circumstances, key technologies for the MDO of high speed train shape is systematically investigated, supported by the National Key Technology R&D Program(No.2009BAG12A07) and the National Basic Research Program of China (No.2011CB711102). The content studied of the thesis includes the following several respects mainly:1) The approximate algorithm is discussed combing metamodel and Design of Experiment (DOE) technology. Union form design is programmed using FORTRAN code. Performance of four mostly used metamodels are compared and validated by two functions:Sum of squares and Schaffer F6.The results show that among those four metamodel Kriging and the support vector machine (SVM) have the best adaptability to those nonlinear problems.2) A hybrid GA-PSO algorithm combining the benefits of both the original algorithms GA and PSO is proposed in this research.GA is used in the globle search, while PSO is used in local search. The hybrid GA-PSO algorithm was observed to be robust and efficient in all the tests cases.3) The train-tunnel coupling design is performed to minimize the maximum value of the micro-pressure wave. As the prediction of micro-pressure wave requires expensive computation resource, an adaptive surrogate model based on Kriging was used during optimization.In the sequential approximate optimization process, a hybrid GA-PSO algorithm is used to find the optimum shapes of the train nose and the tunnel hood. As a result, the present study suggests an optimal train-tunnel shape that is an improvement over current design in terms of micro-pressure wave. 4) A method for high-speed nose shape design was proposed to provide a suitable nose shape under multi-line cases. An exemplary nose shapes under open air and passing tunnel line cases were designed by this technique. The comparison between the current CRH2and those optimal nose shapes demonstrated the capabilities of the method.5) The MDO model of high speed pantograph is setup, based on the coupling analysis of those concerned disciplinaries:structure, mechnical dynamic and aerodynamic. The objectives considered while finding the optimum design of panhead are aerodynamic drag for efficiency, generated noise for environment friendly. A multi objective shape optimization is performed to identify the aerodynamic shape which induces least drag and generates least aerodynamic noise. The optimum shapes of the panhead is compared to the original design.The results show that the optimum designs induces20%less drag and also generates13.36%less aerodynimac noise than the base design.