航空学报 > 2020, Vol. 41 Issue (5): 623348-623348   doi: 10.7527/S1000-6893.2019.23348

飞行器气动外形数值优化与设计专栏

通用飞行器气动优化设计数字化集成平台——DIPasda

孙俊峰, 周铸, 黄勇, 庞宇飞, 卢风顺, 许勇   

  1. 中国空气动力研究与发展中心 计算空气动力研究所, 绵阳 621000
  • 收稿日期:2019-08-06 修回日期:2019-08-13 出版日期:2020-05-15 发布日期:2020-05-28
  • 通讯作者: 周铸 E-mail:f_yforever@126.com

Digital integrated platform for universal aircraft aerodynamic design optimization: DIPasda

SUN Junfeng, ZHOU Zhu, HUANG Yong, PANG Yufei, LU Fengshun, XU Yong   

  1. Computational Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China
  • Received:2019-08-06 Revised:2019-08-13 Online:2020-05-15 Published:2020-05-28

摘要: 未来航空工业的发展,需要解决多学科综合设计的关键问题,为新型高性能飞行器的设计提供有力的设计方法和设计工具。DIPasda作为复杂外形设计的通用飞行器多学科优化设计平台,研制目的主要是提供一套新型通用、鲁棒、高效的优化设计架构,应用于通用飞行器工业设计环境,改善传统设计耗时低效的状况,提高新型飞行器设计的效率和精度。DIPasda平台系统包含了优化设计过程中所需用到的各类方法,主要包括数值优化算法、几何模型参数化方法、代理模型方法、高精度的学科分析工具等。通过详细介绍平台的系统架构、主要的功能模块、伴随优化设计和多目标优化设计流程,展现了DIPasda平台系统架构设计的灵活性和功能模块的完备性。最后通过优化算例展示了系统的综合优化设计能力。

关键词: 气动设计, 优化平台, 耦合伴随优化, 进化算法, 多目标优化, 多学科优化

Abstract: The development of the future aviation industry needs to solve the key problems of multidisciplinary integrated design and provide a powerful design method and tools for the design of new high-performance aircraft. This paper presents an automated digitalized integrated platform for aerodynamics synthetic design and assessment (DIPasda) for complex shape. Our goal is to present a new general-purpose, robust, and efficient optimization platform which is aimed at real-life constrained designs where the conventional design approaches are complicated and time-consuming. The DIPasda system consists of a collection of functional modules for performance design and optimization studies by numerical optimization schemes, geometry parameterization techniques, surrogate models, high-fidelity computational analysis tools for different disciplines and so on. By introducing the system architecture of the platform in detail, the main functional modules, adjoint optimization, and multi-objective optimization process, the flexibility of the system architecture design and the completeness of the functional modules are demonstrated. At last, optimization tests are presented to show the system's design optimization capability.

Key words: aerodynamic design, optimization platform, coupling adjoint optimization, evolutionary algorithm, multi-objective optimization, multidiscipline optimization

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