For shape optimization of a high-speed train head car with the objective to minimize the generated pressure wave, adjoint-based methods with the continuous approach were applied to determine the necessary shape modifications. Gradient-based shape optimization methods are iterative procedures, and their grade of convergency is coupled to the step size of each morphing process. To avoid re-meshing for each iteration, CAD free mesh morphing using radial basis function interpolation was employed to modify the initial computational grid according to the evaluated surface displacements for the next iteration. It was shown, that the tools and the coupling between numerical simulation, sensitivity analysis and mesh morphing work well. Up to now, the described approach was only tested for the flow around a sphere. Actually, after one iteration no significant improvement of the objective function could be observed. Thus, more iterations will be required to improve the aerodynamics of the object with regard to the considered objective function. Moreover, validation of the results against experiments (e.g. drag coeff of the sphere) and benchmarks of the improvements of the objective function are pending as well. Finally, the presented optimization procedure will be applied to a train head car.
Shape optimization of train head cars using adjoint-based computational fluid dynamics
2012
17 Seiten, 16 Bilder, 37 Quellen
Conference paper
Storage medium
English