Development on Unsteady Aerodynamic Modeling Technology at High Angles of Attack

IF 9.7 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Archives of Computational Methods in Engineering Pub Date : 2024-10-16 DOI:10.1007/s11831-024-10180-w
Baigang Mi, Shixin Cheng, Hao Zhan, Jingyi Yu, Yiming Wang
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Abstract

Directly obtaining the dynamic values of the unsteady aerodynamics at large angle of attack by either the CFD or experimental technologies to present further analysis should pay great costs. Therefore, the unsteady aerodynamic modeling based on a few calculations or experimental data has been established and developed. This study mainly discusses the development and challenges of unsteady aerodynamic modeling of aircraft at high angle of attack, investigates the accuracy, efficiency, and future development of the conventional and modern intelligent models divided according to the established physical basis. The conventional methods have been built on valuating changing law of either the macroscopic aerodynamic performance or microscopic flow separating characteristics, which is mainly composed of linear/nonlinear aerodynamic derivative model, integrated models, differential models, aerodynamic incremental model and angular rate model. The intelligent methods are represented by fuzzy logic, support vector machines and shallow / deep neural network models, all of which are proposed by training the sample data based on various intelligence algorithms. Compared to the conventional aerodynamic models, these intelligent models have strong generalization ability and high predication efficiency. However, they are poorly interpretable due to the lack of physical basis on the dynamic flow fields. In general, the future unsteady aerodynamic models should be developed by focusing on the intelligently characterization of physical meaning of the nonlinear dynamic flow fields to improve the predication accuracy and efficiency on the complex aerodynamic forces/moments, and the applications in aircraft design and flight dynamics.

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开发高迎角下的非稳态空气动力学建模技术
通过 CFD 或实验技术直接获取大迎角下的非稳态空气动力学动态值以进行进一步分析,需要付出高昂的成本。因此,基于少量计算或实验数据的非稳态空气动力学模型已经建立和发展起来。本研究主要讨论了高攻角飞行器非稳态气动建模的发展与挑战,研究了根据既定物理基础划分的传统模型和现代智能模型的精度、效率和未来发展。传统方法建立在对宏观气动性能或微观气流分离特性变化规律的评估上,主要包括线性/非线性气动导数模型、综合模型、微分模型、气动增量模型和角速率模型。智能方法以模糊逻辑、支持向量机和浅/深神经网络模型为代表,这些方法都是基于各种智能算法对样本数据进行训练而提出的。与传统的空气动力学模型相比,这些智能模型具有较强的泛化能力和较高的预测效率。然而,由于缺乏动态流场的物理基础,它们的可解释性较差。总体而言,未来的非稳态气动模型应着重于非线性动态流场物理意义的智能表征,以提高对复杂气动力/力矩的预测精度和效率,以及在飞机设计和飞行动力学中的应用。
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来源期刊
CiteScore
19.80
自引率
4.10%
发文量
153
审稿时长
>12 weeks
期刊介绍: Archives of Computational Methods in Engineering Aim and Scope: Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication. Review Format: Reviews published in the journal offer: A survey of current literature Critical exposition of topics in their full complexity By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.
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