基于粗粒化离散元方法的旋翼沙尘云数值模拟研究

  • 周永泽 ,
  • 王玉齐 ,
  • 胡锐锋 ,
  • 朱伟 ,
  • 王国华 ,
  • 张卫国
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  • 1. 兰州大学
    2. 中国空气动力研究与发展中心

收稿日期: 2025-12-12

  修回日期: 2026-02-04

  网络出版日期: 2026-02-09

基金资助

国家自然科学基金;中央高校基本科研业务费;甘肃省自然科学基金

Numerical Simulation of Rotor-Induced Dust Cloud Based on the CG-DEM Method

  • ZHOU Yong-Ze ,
  • WANG Yu-Qi ,
  • HU Rui-Feng ,
  • ZHU Wei ,
  • WANG Guo-Hua ,
  • ZHANG Wei-Guo
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Received date: 2025-12-12

  Revised date: 2026-02-04

  Online published: 2026-02-09

摘要

在沙漠环境中,由旋翼下洗流诱导的沙尘云(“沙盲”现象)由海量沙尘颗粒构成,会导致飞行器周边能见度急剧下降,形成严重飞行安全隐患。已有相关数值模拟研究中,采用追踪真实颗粒的方法计算成本极高,而减少颗粒数量的模拟仅能实现定性分析,难以满足定量预测要求。本研究基于粗粒化离散元方法,同时采用四向耦合考虑颗粒间碰撞及颗粒对流场的反馈,通过追踪粗粒化颗粒即可获得与旋翼沙尘云实际发展定量吻合的模拟结果。为考虑湍流对旋翼沙尘云中颗粒输运的影响,采用了考虑湍流脉动的颗粒拖曳力模型。研究结果表明:粗粒化离散元方法能够有效实现旋翼沙尘云的定量模拟;对于本文算例,采用考虑湍流效应的拖曳力模型提升了预测精度,稳定阶段空中颗粒数量较传统模型增加约 27%,输沙率预测与实验值的误差小于5%。

本文引用格式

周永泽 , 王玉齐 , 胡锐锋 , 朱伟 , 王国华 , 张卫国 . 基于粗粒化离散元方法的旋翼沙尘云数值模拟研究[J]. 航空学报, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2026.33229

Abstract

In desert environments, the dust cloud induced by rotor downwash (the "brownout" phenomenon) consists of an enormous number of sand and dust particles. It causes a sharp drop in visibility around the aircraft, posing a serious flight safety hazard. In existing relevant numerical simulation studies, the method of tracking real particles incurs extremely high computational costs, while simulations with reduced particle counts can only achieve qualitative analysis, failing to meet the requirements of quantitative prediction. Based on the coarse-grained discrete element method (CG-DEM), this study adopts four-way coupling to account for inter-particle collisions and the feedback effect of particles on the flow field. By tracking coarse-grained particles, simulation results that quantitatively agree with the actual development of rotor-induced dust clouds can be obtained. To consider the influence of turbulence on particle transport in rotor dust clouds, a particle drag force model incorporating turbulent effect is employed. The results show that the CG-DEM can effectively realize the quantitative simulation of rotor dust clouds; for the case in this study, the use of the drag force model considering turbulent effect improves the prediction accuracy. In the steady state, the number of airborne particles increases by approximately 27% compared with the traditional drag model, and the error between the predicted sand transport rate and the experimental measurement is less than 5%.

参考文献

[1] SEDDON J, NEWMAN S, SEDDON B.Basic helicopter aerodynamics[M]. New York: Wiley John & Sons, 2001. [2] ANDERSON L, DOTY P, GRIEGO M, et al.Solutions analysis for helicopter brownout[C]//Proc of the 9th Annual NDIA Systems Engineering Conference. 2006. [3]U.S. Department of Defense. Study of rotorcraft survivability, Summary Briefing[R]. 2009. [4]张进虎.巴丹吉林沙漠高大沙山柽柳生态水文指示及其水来源[D]. 兰州: 兰州大学, 2018. [5]王少飞, 潘翀, 张卫国, 等.基于的直升机旋翼“沙盲”现象风沙两相流测量[J].实验流体力学, 2025, 39(4):28-35 [6]PHILLIPS C, KIM H W, BROWN R E.The flow physics of helicopter brownout[C]//Proc of the 66th Annual Forum of the American Helicopter Society. 2010. [7]CAPRACE D G, BAKER E, DIAZ P V, et al.Planetary helicopter brownout simulation of Ingenuity using a Eulerian dust transport model[J].AIAA Journal, 2025, 63(10):1-16 [8]SAHAI A, PALMER G.Variable-Fidelity Euler–Lagrange Framework for Simulating Particle-Laden High-Speed Flows[J].AIAA Journal, 2022, 60(5):3001-3019 [9]SYAL M, LEISHMAN J G.Modeling of Bombardment Ejections in the Rotorcraft Brownout Problem[J].AIAA Journal, 2013, 51(4):849-866 [10] GOVINDARAJAN B M.Evaluation of particle clustering algorithms in the prediction of brownout dust clouds[D]. College Park: University of Maryland, 2011. [11] HU Q, GUMEROV N A, SYAL M, et al.Toward improved aeromechanics simulation using recent advancements in scientific computing[C]// Proc of the 67th Annual Forum of the American Helicopter Society. 2011: 2105-2119. [12]谭剑锋, 何龙, 于领军, 等.基于黏性涡粒子沙粒的直升机沙盲建模[J].航空学报, 2022, 43(8):351-361 [13]LIN H, XU C, JIANG C, et al.Finite particle approach for high-fidelity simulation on helicopter brownout[J].AIAA Journal, 2024, 62(1):193-208 [14]吴林波, 孟澍, 张威, 等.直升机近地飞行扬沙抑制的旋翼布局参数研究[J].航空学报, 2025, NA(NA):NA-NA [15]NEEDHAM D J, LANGDON S.A mathematical model for wind-generated particle–fluid flow fields with an application to the helicopter cloud problem.[J].Journal of Fluid Mechanics, 2024, 998(NA):A61-NA [16]GRIFFITHS D A, ANANTHAN S, LEISHMAN J G.Predictions of rotor performance in ground effect using a free-vortex wake model[J].Journal of the American Helicopter Society, 2005, 50(4):302-314 [17]PHILLIPS C, BROWN R E.Eulerian simulation of the fluid dynamics of helicopter brownout[J].Journal of Aircraft, 2009, 46(4):1416-1429 [18]叶靓, 招启军, 徐国华.基于非结构嵌套网格方法的旋翼地面效应数值模拟[J].航空学报, 2009, 30(5):780-786 [19]朱明勇, 招启军, 王博.基于和混合配平算法的直升机旋翼地面效应模拟[J].航空学报, 2016, 37(8):2539-2551 [20]张卫国, 谭剑锋, 刘亚奎, 等.直升机“沙盲”现象研究进展[J].实验流体力学, 2023, 37(5):56-75 [21]王萍, 郑晓静.风沙两相流数值模拟研究进展[J].航空学报, 2021, 42(9):625767-625768 [22]SHAO Y P.A Lagrangian stochastic model for nonpassive particle diffusion in turbulent flows[J].Mathematical and Computer Modelling, 1995, 21(9):31-37 [23]KOK J F, RENNO N O.A comprehensive numerical model of steady state saltation (COMSALT)[J].Journal of Geophysical Research Atmospheres, 2009, 114(NA):D17-NA [24] COWHERD C, Jr.Sandblaster 2: support of see-throughtechnologies for particulate brownout[R]. Defence Advanced Research Projects Agency (DARPA), Technical Report 110565, 2007 [25] FERZIGER J H, PERI? M, STREET R L.Computational methods for fluid dynamics[M]. New York: Springer, 2002. [26]MENTER F R.Two-equation eddy-viscosity turbulence models for engineering applications[J].AIAA Journal, 1994, 37(8):1598-1605 [27]JONES W P, LAUNDER B E.The prediction of laminarization with a two-equation model of turbulence[J].International Journal of Heat and Mass Transfer, 1972, 15(2):301-314 [28]LAUNDER B E, SHARMA B I.Application of the energy-dissipation model of turbulence to the calculation of flow near a spinning disc[J].Letters in Heat and Mass Transfer, 1974, 1(2):131-137 [29]WILCOX D C.Reassessment of the scale-determining equation for advanced turbulence models[J].AIAA Journal, 1988, 26(11):1299-1310 [30]BLADES E L, MARCUM D L.A sliding interface method for unsteady unstructured flow simulations[J].International Journal for Numerical Methods in Fluids, 2007, 53(3):507-529 [31]SCHILLER L, NAUMANN A.Uber die grundlegenden Berechnungen bei der Schwerkraftaufbereitung[J].Zeitschrift des Vereines Deutscher Ingenieure, 1933, 77(NA):318-321 [32]WANG Y, HU R.A stochastic force model for a finite-size spherical particle in turbulence[J].International Journal of Multiphase Flow, 2025, 191(NA):105300-NA [33]SAFFMAN P G.The lift on a small sphere in a slow shear flow[J].Journal of Fluid Mechanics, 1965, 22(2):385-400 [34]CUNDALL P A, STRACK O D L.A discrete numerical model for granular assemblies[J].Géotechnique, 1980, 30(3):331-336 [35]HERTZ H.Ueber die Berührung fester elastischer K?rper[J].J Reine Und Angewandte Mathematik, 1882, 92(NA):156-NA [36]MALONE K F, XU B H.Determination of contact parameters for discrete element method simulations of granular systems[J].Particuology, 2008, 6(6):521-528 [37]TSUJI Y, TANAKA T, ISHIDA T.Lagrangian numerical simulation of plug flow of cohesionless particles in a horizontal pipe[J].Powder Technology, 1992, 71(3):239-250 [38]ZHU Z, HU R, LEI Y, et al.Particle resolved simulation of sediment transport by a hybrid parallel approach[J].International Journal of Multiphase Flow, 2022, 152(NA):104072-NA [39]SAKAI M, KOSHIZUKA S.Large-scale discrete element modeling in pneumatic conveying[J].Chemical Engineering Science, 2009, 64(3):533-539 [40]HILTON J E, CLEARY P W.Comparison of non-cohesive resolved and coarse grain DEM models for gas flow through particle beds[J].Applied Mathematical Modelling, 2014, 38(17-18):4197-4214 [41]NASATO D S, GONIVA C, PIRKER S, et al.Coarse graining for large-scale DEM simulations of particle flow—an investigation on contact and cohesion models[J].Procedia Engineering, 2015, 102(NA):1484-1490 [42]BENYAHIA S, GALVIN J E.Estimation of numerical errors related to some basic assumptions in discrete particle methods[J].Industrial & Engineering Chemistry Research, 2010, 49(21):10588-10605 [43]LU L, XU Y, LI T, et al.Assessment of different coarse graining strategies to simulate polydisperse gas-solids flow[J].Chemical Engineering Science, 2018, 179(NA):53-63 [44]LU L, XU J, GE W, et al.EMMS-based discrete particle method (EMMS–DPM) for simulation of gas–solid flows[J].Chemical Engineering Science, 2014, 120(NA):67-87 [45]RENZO A D, NAPOLITANO E S, MAIO F P D.Coarse-grain DEM modelling in fluidized bed simulation: a review[J].Processes, 2021, 9(2):279-NA [46]BRANDT V, GRABOWSKI J, JURTZ N, et al.A benchmarking study of different DEM coarse graining strategies[J].Powder Technology, 2023, 426(NA):118629-NA [47]WELLER H G, TABOR G, JASAK H, et al.A tensorial approach to computational continuum mechanics using object-oriented techniques[J].Computers in Physics, 1998, 12(6):620-631 [48] 裴潇.考虑地效影响的旋翼桨尖涡演化规律实验研究[D]. 兰州: 兰州大学, 2025. [49]胡健平, 徐国华, 史勇杰, 等.基于-耦合数值模拟的全尺寸直升机沙盲形成机理[J].航空学报, 2020, 41(3):154-168 [50]RUCK B, MAKIOLA B.Particle dispersion in a single-sided backward-facing step flow[J].International Journal of Multiphase Flow, 1988, 14(6):787-800
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