Multi-Objective Aerodynamic Optimization of Truck Deflector Using Genetic Algorithm and CFD Method

摘要：

Based on the aerodynamic theory and CFD method, the single/multi-objective aerodynamic optimization design of a truck deflector is completed. During the process, two approaches have been developed separately to improve its performance: (A) a suitable cut transversely on the back yard of the circular deflector; (B) deflector reshaping using B-spline. For single-objective optimization, truck speed is fixed as the precondition, drag is set to be the objective. Moreover, the multi-objective optimization is arranged by Hybrid Genetic Algorithm (HGA), including drag and aerodynamic acoustics. This research indicates that both approaches can improve the local flow status, and provide a better characteristics in reducing drag (4.50％-6.23％ and 3.16％-4.03％ respectively) and acoustics, which is valuable both in academic research practical application.

关键词： CFD B-spline drag aerodynamic acoustics hybrid genetic algorithm

作者: Zhao Xu Han Tianshi Yang Qiuping

作者单位: National Key Laboratory of Aerodynamic Design and Research, Northwestern Polytechnical University,Xi National Key Laboratory of Aerodynamic Design and Research, Northwestern Polytechnical University,Xi

会议类型: 国际会议

会议名称: 2010 Asia-Pacific International Symposium on Aerospace Technology(2010 亚太航空航天技术研讨会 APISAT 2010)

会议地点: 西安

会议语种:英文

页码: 432-434

在线出版日期: 2010-09-01（万方平台首次上网日期，不代表论文的发表时间）