Study on hypersonic forebody transition characteristics based on the amplification factor transport model

Xu Yuan; Wang Haiyang; Wang Chengyu; Liu Zaijie; Huang Hexia

doi:10.7638/kqdlxxb-2025.0230

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Study on hypersonic forebody transition characteristics based on the amplification factor transport model

更新时间：2026-05-28

- Study on hypersonic forebody transition characteristics based on the amplification factor transport model
- Vol. 44, Issue 3, Pages: 166-178(2026)
- 作者机构：
  
  南京航空航天大学能源与动力学院,南京,210016
- 作者简介：
- 基金信息：
- DOI：10.7638/kqdlxxb-2025.0230
  CLC： V231.2
- Published：2026
- 稿件说明：
移动端阅览
许愿, 王海洋, 王成宇, 等. 基于放大因子输运方程模型的高速前体转捩特性研究[J]. 空气动力学学报, 2026, 44(3): 166−178.

Xu Yuan, Wang Haiyang, Wang Chengyu, et al. Study on hypersonic forebody transition characteristics based on the amplification factor transport model[J]. 2026, 44(3): 166-178.
许愿, 王海洋, 王成宇, 等. 基于放大因子输运方程模型的高速前体转捩特性研究[J]. 空气动力学学报, 2026, 44(3): 166−178. DOI： 10.7638/kqdlxxb-2025.0230

Xu Yuan, Wang Haiyang, Wang Chengyu, et al. Study on hypersonic forebody transition characteristics based on the amplification factor transport model[J]. 2026, 44(3): 166-178. DOI： 10.7638/kqdlxxb-2025.0230.

摘要

为了明晰鼓包压缩面前体在高速条件下的转捩机制及其对发动机进气品质的影响，本文采用国家数值风洞风雷软件（PHengLEI）和放大因子输运方程模型开展了高速鼓包压缩面前体的转捩特性研究。首先通过HIFiRE-5与HyTRV构型开展了转捩模型校核，在此基础上，系统分析了雷诺数、攻角、侧滑角及马赫数对转捩阵面与气动特性的影响。结果表明：雷诺数与马赫数对转捩影响最为显著，转捩阵面随雷诺数增大前移、随马赫数增大后移；攻角增大使迎风面转捩阵面由“山”字型演变为“凹”字型；侧滑角增大导致转捩阵面呈现明显不对称分布。相较于层流计算结果，考虑转捩后升力系数、阻力系数和俯仰力矩系数分别最大增加11.7%、13.6%与10.7%，升阻比最大减小10.1%。本研究验证了两方程AFT模型在复杂三维前体转捩预测中的可靠性，为高速前体气动设计与热防护优化提供了有效的数值工具与数据支撑。

Abstract

The bump-compression forebody constitutes a critical aerodynamic component for hypersonic air-breathing vehicles. Its transition characteristics directly influence the quality of the flowfield entering the engine

thereby impacting the overall efficiency and operational stability of the propulsion system. However

there is currently a lack of systematic investigation into the transition characteristics of bump-compression forebodies

both domestically and internationally

which hampers the provision of an effective basis for related aerodynamic design. This study presents an investigation of the transition characteristics of a hypersonic bump-compression forebody using the National Numerical Wind Tunnel (NNW) software PHengLEIand the Amplification Factor Transport (AFT) model. First

the transition model was validated using the HIFiRE-5 and HyTRV configurations. On this basis

the effects of Reynolds number

angle of attack

sideslip angle

and Mach number on the transition front and aerodynamic characteristics were systematically analyzed. The results demonstrate that Reynolds number and Mach number exert the most significant influence on transition: the transition front moves forward with increasing Reynolds number and rearward with increasing Mach number. As the angle of attack increases

the transition front on the windward surface evolves from a mountain-shaped pattern to a concave-shaped configuration. An increase in the sideslip angle leads to a distinctly asymmetric distribution of the transition front. Compared to laminar flow predictions

accounting for boundary layer transition results in maximum increases of 11.7%

13.6%

and 10.7% in the lift

drag

and pitching moment coefficients

respectively

while the lift-to-drag ratio exhibits a maximum decrease of 10.1%. This research verifies the reliability of the two-equation AFT model for transition prediction on complex three-dimensional forebodies

providing an effective numerical tool and data support for the aerodynamic design and thermal protection optimization of hypersonic forebodies.

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references

Zhou Heng, Zhang Hanxin. Two problems in the transition and turbulence for near space hypersonic flying vehicles[J]. Acta Aerodynamica Sinica, 2017, 35(2): 151−155 (in Chinese).

Chen Jianqiang, Tu Guohua, Zhang Yifeng, et al. Hypersnonic boundary layer transition: what we know, where shall we go[J]. Acta Aerodynamica Sinica, 2017, 35(3): 311−337 (in Chinese). doi: 10.7638/kqdlxxb-2017.0030

Huang H X, Tan H J, Li F B, et al. A review of the shock-dominated flow in a hypersonic inlet/isolator[J]. Progress in Aerospace Sciences, 2023, 143: 100952. doi: 10.1016/j.paerosci.2023.100952

Cai Jia, Huang Hexia, Tang Xuebin, et al. Aerodynamic design method and flow features of forebody/compression surface with controlled lateral pressure distribution[J]. Acta Aerodynamica Sinica, 2022, 40(1): 65−76 (in Chinese). doi: 10.7638/kqdlxxb-2021.0432

Sziroczak D, Smith H. A review of design issues specific to hypersonic flight vehicles[J]. Progress in Aerospace Sciences, 2016, 84: 1−28. doi: 10.1016/j.paerosci.2016.04.001

Wang Liang, Zhou Lin. Prediction of aerodynamic characteristics of hypersonic vehicle by improved k-ω-γ transition model[J ] . Acta Aerodynamica Sinica, 2021, 39(3): 51−61 (in Chinese). doi: 10.7638/kqdlxxb-2019.0146

Chen Jianqiang, Tu Guohua, Wan Bingbing, et al. Characteristics of flow field and boundary-layer stability of HyTRV[J]. Acta Aeronautica et Astronautica Sinica, 2021, 42(6): 124317 (in Chinese).

Zhu Y D, Lee C, Chen X, et al. Newly identified principle for aerodynamic heating in hypersonic flows[J]. Journal of Fluid Mechanics, 2018, 855: 152−180. doi: 10.1017/jfm.2018.646

Nair K A, Unnikrishnan S. Effects of nose bluntness on hypersonic transition over ogive-cylinder forebodies[J]. AIAA Journal, 2024, 62(2): 476−488. doi: 10.2514/1.j063130

Liu Z, Shi L, Zhou W J. Compressible extension of γ-Re θ transition model[C ] //Proceedings of the 11 th National Con Ference on Fluid Mechanics. Shenzhen, Chinese: Fluid Mechan ics Professional Committee, 2020: 1-12.

Hao Z H, Yan C, Qin Y P, et al. Improved γ-Reθt model for heat transfer prediction of hypersonic boundary layer transition[J]. International Journal of Heat and Mass Transfer, 2017, 107: 329−338. doi: 10.1016/j.ijheatmasstransfer.2016.11.052

Langtry R, Sengupta K, Yeh D T, et al. Extending the correlation based transition model for crossflow effects[C]//Proceedings of the 45th AIAA Fluid Dynamics Conference, AIAA 2015-2474, 2015.

Grabe C, Nie S Y, Krumbein A. Transport modeling for the prediction of crossflow transition[J]. AIAA Journal, 2018, 56(8): 3167−3178. doi: 10.2514/1.j056200

Xiang Xinghao, Zhang Yifeng, Yuan Xianxu, et al. C-γ-Re θ model for hypersonic three-dimensional boundary layer transition prediction[J ] . Acta Aeronautica et Astronautica Sinica, 2021, 42(9): 625711 (in Chinese).

Liu Kunkun, Yan Chao, Hao Zihui. Cross-flow instability analysis and transition prediction of swept wing[J]. Physics of Gases, 2017, 2(5): 18−24 (in Chinese). doi: 10.19527/j.cnki.2096-1642.2017.05.003

Menter F R, Smirnov P E, Liu T, et al. A one-equation local correlation-based transition model[J]. Flow, Turbulence and Combustion, 2015, 95(4): 583−619. doi: 10.1007/s10494-015-9622-4

Sandhu J P S, Ghosh S. A local correlation-based zero-equation transition model[J]. Computers Fluids, 2021, 214: 104758. doi: 10.1016/j.compfluid.2020.104758

Menter F R, Matyushenko A, Lechner R, et al. An algebraic LCTM model for laminar–turbulent transition prediction[J]. Flow, Turbulence and Combustion, 2022, 109(4): 841−869. doi: 10.1007/s10494-022-00336-8

Walters D K, Cokljat D. A three-equation eddy-viscosity model for Reynolds-averaged navier–stokes simulations of transitional flow[J]. Journal of Fluids Engineering, 2008, 130(12): 121401. doi: 10.1115/1.2979230

Coder J G, Maughmer M D. Computational fluid dynamics compatible transition modeling using an amplification factor transport equation[J]. AIAA Journal, 2014, 52(11): 2506−2512. doi: 10.2514/1.j052905

Coder J G. Enhancement of the amplification factor transport transition modeling framework[C]//Proc of the 55th AIAA Aerospace Sciences Meeting, Grapevine, Texas. AIAA, 2017: AIAA 2017-1709. doi: 10.2514/6.2017-1709

Djeddi R, Coder J G, Ekici K. Calibration of the critical amplification factor for Reynolds-averaged navier–stokes-based transition modeling[J]. AIAA Journal, 2022, 60(9): 5094−5108. doi: 10.2514/1.j061476

Yan C, Jiang H J, Liu Z J. Improvement and application of local-variable-based transition models to complex three-dimensional configurations[J]. Physics of Fluids, 2024, 36(3): 034105. doi: 10.1063/5.0196850

Halila G L O, Martins J R R A, Fidkowski K J. Adjoint-based aerodynamic shape optimization including transition to turbulence effects[J]. Aerospace Science and Technology, 2020, 107: 106243. doi: 10.1016/j.ast.2020.106243

Liu Z J, Lu Y H, Yan C. Amplification factor transport transition model for high-speed flows[J]. Computers Fluids, 2023, 265: 106023. doi: 10.1016/j.compfluid.2023.106023

Liu Z J, Huang H X, Tan H J. One-equation amplification-factor-transport transition model for high-speed flows[J]. AIAA Journal, 2025, 63(1): 42−54. doi: 10.2514/1.j064267

Zhao Z, He L, He X Y. Design of general CFD software PHengLEI[J]. Computer Engineeringand Science, 2020, 42(2): 210−219. doi: 10.3969/j.issn.1007-130X.2020.02.004

Zhao Z, Zhang L P, He L, et al. PHengLEI: A large scale parallel CFD framework for arbitrary grids[J]. Chinese Journal of Computers, 2019, 42(11): 2368−2383.

Juliano T J, Borg M P, Schneider S P. Quiet tunnel measurements of HIFiRE-5 boundary-layer transition[J]. AIAA Journal, 2015, 53(4): 832−846. doi: 10.2514/1.J053189

Chen Jiufeng, Xu Yang, Jiang Wanqiu, et al. Infrared thermogram measurement experiment of hypersonic boundary-layer transition of a lifting body[J]. Journal of Experiments in Fluid Mechanics, 2024, 38(5): 98−106 (in Chinese). doi: 10.11729/syltlx20220030

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