超音速大范围条件下扫掠支柱压力阻力的特征和预测研究

IF 3.1 2区 物理与天体物理 Q1 ENGINEERING, AEROSPACE
Guowei Luan, Junlong Zhang, Guangjun Feng, Xiaosi Li, Hongchao Qiu, Wen Bao
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引用次数: 0

摘要

本文在宽范围条件(Ma3 = 1.8 ∼ 5.0)下对扫弦冲压式喷气燃烧器进行了数值模拟,并讨论了扫弦的压力阻力特性。结果表明,扫掠支柱的压力阻力特性与燃烧器入口的马赫数和支柱的扫掠角有关。随着燃烧器入口马赫数的减小,支柱压力阻力系数的减小边界逐渐变大。当 Ma3 = 1.8 ∼ 2.0 时,压力阻力降低边界为 α = 15°。当 Ma3 = 2.2 ∼ 2.8 时,压力阻力减小边界为 α = 45°。当 Ma3 = 3.0 ∼ 4.0 时,压力阻力减小边界为 α = 60°。当 Ma3 = 5.0 时,压力阻力减小边界为 α = 65°。此外,随着燃烧器入口马赫数的降低,增加支杆扫掠角所带来的压力阻力降低性能效益也会逐渐增加。此外,还提出了一种基于深度学习的压力阻力系数预测模型,适用于多种工况和多种配置的扫掠支柱。该预测模型由两部分串联而成,包括基于多层感知器(MLP)的横梁表面压力系数预测模型和基于卷积神经网络(CNN)的横梁压力阻力系数预测模型。为了提高 MLP 模型的预测精度,在基于集合的不确定性量化基础上增加了新的训练样本,并通过重新训练获得了改进的 MLP 模型。结果表明,在多种复杂流动特性对支柱的影响下,两种预测模型都具有较高的预测精度。该研究结果有助于为宽体超音速燃烧器支杆的气动减阻设计提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on characteristics and prediction of the pressure drag of the swept strut under supersonic wide-range conditions
In this paper, the numerical simulation of the swept strut ramjet combustor was carried out under wide-range conditions (Ma3 = 1.8 ∼ 5.0), and the pressure drag characteristics of the swept strut were discussed. The results show that the pressure drag characteristics of the swept strut are related to the Mach number of the combustor inlet and the swept angle of the strut. The decreased boundary of the strut pressure drag coefficient gradually advances with the decrease of the Mach number of the combustor inlet. When Ma3 = 1.8 ∼ 2.0, the pressure drag reduction boundary is α = 15°. When Ma3 = 2.2 ∼ 2.8, the pressure drag reduction boundary is α = 45°. When Ma3 = 3.0 ∼ 4.0, the pressure drag reduction boundary is α = 60°. When Ma3 = 5.0, the pressure drag reduction boundary is α = 65°. In addition, with the decrease of the Mach number of the combustor inlet, the pressure drag reduction performance benefit brought by increasing the swept angle of the strut will gradually increase. Furthermore, a pressure drag coefficient prediction model suitable for wide-range conditions and multiple configurations of swept struts was proposed based on deep learning. The prediction model consists of two parts in series, which includes the prediction model of the surface pressure coefficient of the swept strut based on multilayer perceptron (MLP) and the prediction model of the pressure drag coefficient of the swept strut based on convolutional neural network (CNN). To improve the prediction accuracy of the MLP model, new training samples were added based on the ensemble-based uncertainty quantification, and the improved MLP model was obtained by retraining. The results show that both the two prediction models have high prediction accuracy under the effect of multiple complex flow characteristics on the strut. The results of this study are helpful to provide a reference for the aerodynamic drag reduction design of the strut in the wide-speed supersonic combustor.
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来源期刊
Acta Astronautica
Acta Astronautica 工程技术-工程:宇航
CiteScore
7.20
自引率
22.90%
发文量
599
审稿时长
53 days
期刊介绍: Acta Astronautica is sponsored by the International Academy of Astronautics. Content is based on original contributions in all fields of basic, engineering, life and social space sciences and of space technology related to: The peaceful scientific exploration of space, Its exploitation for human welfare and progress, Conception, design, development and operation of space-borne and Earth-based systems, In addition to regular issues, the journal publishes selected proceedings of the annual International Astronautical Congress (IAC), transactions of the IAA and special issues on topics of current interest, such as microgravity, space station technology, geostationary orbits, and space economics. Other subject areas include satellite technology, space transportation and communications, space energy, power and propulsion, astrodynamics, extraterrestrial intelligence and Earth observations.
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