Multi-objective optimization design for a hydrodynamic retarder based on CFD simulation considering cavitation effect

Abstract

It is important to suppress cavitation phenomenon for lower vibration and noise, which can be realized by structure optimization to reduce cavitation bubbles of flow field. Nonetheless, performance factors in hydrodynamic retarder are usually conflicted when conducting a structure design, it is hard to simultaneously restrain cavitation and improve the retarding performance. In our study, a combination of comprehensive CFD simulation and multi-objective optimization is developed to improve the retarding torque ([Formula: see text]), lessen the volume of Retarder ([Formula: see text]) and reduce the volume of bubbles ([Formula: see text]) in the internal flow field. First, the elaborate CFD simulation calculation, included a refined hexahedral mesh and the stress-blended eddy simulation (SBES), is proposed to investigate the unsteady flow field considering the cavitation, and its accuracy is validated by experimental data. Then, the RSM (Respond Surface Method) approximation model is constructed by combination of DOE (Design of Method) and CFD methods. The NSGA-II (Non-Dominated Sorting Genetic Algorithm) is selected as multi-objective optimization algorithm, and the weight and scale factor of each sub objective are specified. The optimization results, verified by theoretical calculation, show that [Formula: see text] is increased by 22%–24%, [Formula: see text] is reduced by 32%–45% and [Formula: see text] is reduced by 1%. Furthermore, the comparison of the vortex distributions before and after optimization demonstrates that the optimization improves the flow field impact and pressure loss in the retarder and reduces the number of bubbles resulting in the increasing vortex. Additionally, parameters’ effect on the cavitation and the braking performance are analyzed to efficiently achieve the best comprehensive performance of the retarder design. The newly-developed optimization method, which can understand the optimization principle and guide a balance between the cavitation and the retarding performance improvement, will reduce huge trial cost and time cost in the manufacture.