Fast aerodynamic analysis method for three-dimensional morphing wings based on deep learning

IF 5 1区工程技术 Q1 ENGINEERING, AEROSPACE

Aerospace Science and Technology Pub Date : 2024-10-29 DOI:10.1016/j.ast.2024.109690

Ruolong Xie , Zhiqiang Wan , De Yan , Wenwei Qiu

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Abstract

Morphing wings have garnered widespread attention due to their superior aerodynamic efficiency. However, in the design process, accurately and efficiently obtaining the three-dimensional flow field of morphing wings remains a challenging issue. This paper proposes a Deep Learning-based method for predicting the flow field of a Biomimetic Morphing Wings to address this problem. Firstly, a Coordinate Transformation Mechanism is established for the studied Biomimetic Morphing Wing to ensure the consistency of grid point coordinates between different wing shapes. Secondly, a two-level Flow Field Prediction Model is constructed, consisting of grid point prediction level and physical quantity continuity adjustment level. Using this method, the flow field of the Biomimetic Morphing Wing was predicted, and the predication result were similar to those of numerical simulations. This indicates that the proposed method maintains high prediction accuracy while reducing computation time, thereby enhancing the analysis efficiency of the morphing wing's flow field.

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基于深度学习的三维变形机翼快速气动分析方法

变形机翼因其卓越的气动效率而受到广泛关注。然而，在设计过程中，准确有效地获取变形翼的三维流场仍然是一个具有挑战性的问题。本文针对这一问题，提出了一种基于深度学习的仿生变形翼流场预测方法。首先，针对所研究的仿生变形翼建立了坐标变换机制，以确保不同翼型之间网格点坐标的一致性。其次，构建了两级流场预测模型，包括网格点预测级和物理量连续性调整级。利用该方法对仿生变形翼的流场进行了预测，预测结果与数值模拟结果相似。这表明所提出的方法在减少计算时间的同时保持了较高的预测精度，从而提高了变形翼流场的分析效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Aerospace Science and Technology 工程技术-工程：宇航

CiteScore

10.30

自引率

28.60%

发文量

654

审稿时长

54 days

期刊介绍： Aerospace Science and Technology publishes articles of outstanding scientific quality. Each article is reviewed by two referees. The journal welcomes papers from a wide range of countries. This journal publishes original papers, review articles and short communications related to all fields of aerospace research, fundamental and applied, potential applications of which are clearly related to: • The design and the manufacture of aircraft, helicopters, missiles, launchers and satellites • The control of their environment • The study of various systems they are involved in, as supports or as targets. Authors are invited to submit papers on new advances in the following topics to aerospace applications: • Fluid dynamics • Energetics and propulsion • Materials and structures • Flight mechanics • Navigation, guidance and control • Acoustics • Optics • Electromagnetism and radar • Signal and image processing • Information processing • Data fusion • Decision aid • Human behaviour • Robotics and intelligent systems • Complex system engineering. Etc.