Shape Optimization of Train Head Cars using Adjoint-based Computational Fluid Dynamics

Abstract

The operating conditions of modern high-speed trains require optimized aerodynamic shapes, which can be developed during the design phase using efficient numerical methods. In this context, many of the interesting aerodynamic features can be determined numerically by solving the Reynolds-averaged Navier-Stokes (RANS) equations. The focus of the presented study is to explore how far adjoint-based shape optimization using the continuous approach in conjunction with filtered gradients and CAD-free mesh morphing based on radial basis function interpolation is capable of meeting the requirements of aerodynamic train design. First results considering shape optimization with regard to the generated pressure wave in external flows reveal the feasibility and capability of the developed process chain. This paper is based upon D. Jakubek et al. [1]. The current version includes new results from modified testcases.