1. 华中科技大学 航天航空学院工程力学系,武汉,430074
2. 湖北省工程结构分析与安全评价重点实验室,武汉,430074
许平煜(2003—),博士研究生,研究方向:流固耦合数值模拟. E-mail:d202580941@hust.edu.cn
彭泽瑞*,副教授,研究方向:仿生流体力学、流固耦合. E-mail:zeruipeng@hust.edu.cn
纸质出版:2026
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许平煜, 周庆春, 罗梓锋, 等. 基于LBM-IBM的流固耦合高效数值框架与应用[J]. 空气动力学学报, 2026, 44(3): 132−144.
Xu Pingyu, Zhou Qingchun, Luo Zifeng, et al. An efficient numerical framework for fluid-structure interaction based on the LBM-IBM method and its applications[J]. 2026, 44(3): 132-144.
许平煜, 周庆春, 罗梓锋, 等. 基于LBM-IBM的流固耦合高效数值框架与应用[J]. 空气动力学学报, 2026, 44(3): 132−144. DOI: 10.7638/kqdlxxb-2025.0245
Xu Pingyu, Zhou Qingchun, Luo Zifeng, et al. An efficient numerical framework for fluid-structure interaction based on the LBM-IBM method and its applications[J]. 2026, 44(3): 132-144. DOI: 10.7638/kqdlxxb-2025.0245.
针对传统贴体网格方法在处理复杂流固耦合问题时存在的网格生成困难、计算效率低和稳健性不足等瓶颈,本文构建了一种基于格子玻尔兹曼-浸入边界方法(lattice Boltzmann-immersed boundary method
LB-IBM)的高效流固耦合数值求解框架。该框架采用LBM求解不可压缩Navier-Stokes方程,基于有限差分方法求解柔性体结构动力学方程,并结合四阶混合线性多步格式处理刚体振动方程,通过罚函数形式的浸入边界法实现流体与结构的耦合求解,在刚体涡激振动算例中振幅预测误差控制在5%以内。此外,本框架融合了多块网格加密技术以及MPI/OpenMP混合并行技术以支持大规模高效计算,典型算例表明网格量减少约40%,且斯特劳哈尔数、阻力系数等关键参数的误差均保持在5%以下。最后,通过钝体绕流、流致振动以及仿生蜻蜓扑翼等典型算例进行了验证和应用。结果表明,本文提出的计算框架避免了传统贴体网格方法的局限性,适用于具有复杂几何外形、大位移、大变形或多体运动等特征的流固耦合问题的数值模拟,具有良好的计算效率、可靠性和稳健性。
To address the limitations of conventional body-fitted grid methods—such as difficulties in mesh generation
low computational efficiency
and poor robustness in complex fluid-structure interaction (FSI) simulations—this paper develops an efficient numerical framework based on the lattice Boltzmann-immersed boundary method (LB-IBM). In this framework
the lattice Boltzmann method (LBM) is employed to solve the incompressible Navier-Stokes equations
the finite difference method (FDM) is used to discretize the structural dynamics of flexible bodies
and a fourth-order hybrid linear multi-step scheme is adopted to handle rigid-body vibrations. Fluid-structure coupling is achieved through a penalty-based immersed boundary method (IBM)
with the amplitude prediction error controlled within 5% in rigid-body vortex-induced vibration cases. Additionally
the framework integrates multi-block grid refinement and hybrid MPI/OpenMP parallel computing to support large-scale high-efficiency simulations. Typical benchmark tests show that the mesh count is reduced by approximately 40%
while the errors in key parameters such as the Strouhal number and drag coefficient remain below 5%. The framework is validated and applied through representative cases
including bluff body flows
flow-induced vibrations
and bio-inspired dragonfly flapping. Results demonstrate that the proposed approach effectively overcomes the limitations of conventional body-fitted methods
exhibiting good computational efficiency
reliability
and robustness in simulating FSI problems characterized by complex geometries
large displacements
large deformations
or multi-body motions.
Bhat S S, Govardhan R N. Stall flutter of NACA 0012 airfoil at low Reynolds numbers[J]. Journal of Fluids and Structures, 2013, 41: 166−174. doi: 10.1016/j.jfluidstructs.2013.04.001
Garrick I E, Reed Ⅲ W H. Historical development of aircraft flutter[J]. Journal of Aircraft, 1981, 18(11): 897−912. doi: 10.2514/3.57579
Li Yongchang, Han Yizhe, Dai Yuting, et al. Numerical and experimental study on flutter characteristics of a wing with drag rudder[J]. Acta Aerodynamica Sinica, 2025 (in Chinese). doi: 10.7638/kqdlxxb-2024.0022
Yan Yu, Lu Bo, Yang Xinghua, et al. Review on buzz wind tunnel test technology for aircraft control surfaces[J]. Acta Aerodynamica Sinica, 2022, 40(3): 1−9 (in Chinese). doi: 10.7638/kqdlxxb-2021.0303
Williamson C H, Govardhan R. Vortex-induced vibrations[J]. Annual Review of Fluid Mechanics, 2004, 36(1): 413−455.
Wang Lei, Zhang Zhenhua, Liang Shuguo, et al. Some phenomena of vortexinduced vibration in super high-rise building[J]. Acta Aerodynamica Sinica, 2021, 35(5): 665−669 (in Chinese). doi: 10.7638/kqdlxxb-2015.0184
Shan Longxiang, Li Ke, Guo Chengpeng, et al. Vortex-induced vibration characteristics of harbor seal whisker under different wakes[J]. Acta Aerodynamica Sinica, 2024, 42(12): 55−63 (in Chinese). doi: 10.7638/kqdlxxb-2024.0032
Chin D D, Lentink D. Flapping wing aerodynamics: from insects to vertebrates[J]. Journal of Experimental Biology, 2016, 219(7): 920−932. doi: 10.1242/jeb.042317
Nagai H, Isogai K, Fujimoto T, et al. Experimental and numerical study of forward flight aerodynamics of insect flapping wing[J]. AIAA Journal, 2009, 47(3): 730−742. doi: 10.2514/1.39462
Chen Lili, Song Bifeng, Song Wenping, et al. Numerical aerodynamic structural coupling research for flexible flapping wing[J]. Acta Aerodynamica Sinica, 2015, 33(1): 125−133 (in Chinese). doi: 10.7638/kqdlxxb-2012.0210
Zhu Hanxi, Guo Chengpeng, Zhang Tiejun, et al. Fluid-structure interaction characteristics of butterfly flexible flapping wings in the forward flight[J]. Acta Aerodynamica Sinica, 2026, 44(2): 81−92 (in Chinese). doi: 10.7638/kqdlxxb-2024.0189
Wang Yongtao, Zhou Zhiteng, Wang Shizhao. Effect of pitch angle on the flapping flight and sound generation[J]. Acta Aerodynamica Sinica, 2025, 43(3): 14−28 (in Chinese). doi: 10.7638/kqdlxxb-2024.0053
Mittal R, Seo J H, Vedula V, et al. Computational modeling of cardiac hemodynamics: Current status and future outlook[J]. Journal of Computational Physics, 2016, 305: 1065−1082. doi: 10.1016/j.jcp.2015.11.022
Hou G, Wang J, Layton A. Numerical methods for fluid-structure interaction—a review[J]. Communications in Computational Physics, 2012, 12(2): 337−377. doi: 10.4208/cicp.291210.290411s
Zhuang Z, Xie Y M, Li Q, et al. A 172-line Matlab code for structural topology optimization in the body-fitted mesh[J]. Structural and Multidisciplinary Optimization, 2023, 66(1): 11. doi: 10.1007/s00158-022-03464-x
Li H, Kondoh T, Jolivet P, et al. Three-dimensional topology optimization of a fluid–structure system using body-fitted mesh adaption based on the level-set method[J]. Applied Mathematical Modelling, 2022, 101: 276−308. doi: 10.1016/j.apm.2021.08.021
El Aouad S, Larcher A, Hachem E. Anisotropic adaptive bodyfitted meshes for CFD[J]. Computer Methods in Applied Mechanics and Engineering, 2022, 400: 115562. doi: 10.1016/j.cma.2022.115562
Lu Y, Chang X, Zhang Z, et al. A body-fitted adaptive mesh and Helmholtz-type filter based parameterized level-set method for structural topology optimization[J]. Acta Mechanica Sinica, 2025, 41(5): 424119. doi: 10.1007/s10409-024-24119-x
Kim W, Choi H. Immersed boundary methods for fluid-structure interaction: A review[J]. International Journal of Heat and Fluid Flow, 2019, 75: 301−309. doi: 10.1016/j.ijheatfluidflow.2019.01.010
Zhou H, Zhong K, Jia H, et al. Analysis of the effects of dynamic mesh update method on simulating indoor airflow induced by moving objects[J]. Building and Environment, 2022, 212: 108782. doi: 10.1016/j.buildenv.2022.108782
Kim N S, Jeong Y H. An investigation of pressure build-up effects due to check valve’ s closing characteristics using dynamic mesh techniques of CFD[J]. Annals of Nuclear Energy, 2021, 152: 107996. doi: 10.1016/j.anucene.2020.107996
Zhou C, Jiang X, Su J, et al. Injection lubrication for high-speed helical gears using the overset mesh method and experimental verification[J]. Tribology International, 2022, 173: 107642. doi: 10.1016/j.triboint.2022.107642
Huang J, Bathe K J. On the convergence of overlapping elements and overlapping meshes[J]. Computers Structures, 2021, 244: 106429. doi: 10.1016/j.compstruc.2020.106429
Glowinski R, Pan T W, Hesla T I, et al. A distributed Lagrange multiplier/fictitious domain method for particulate flows[J]. International Journal of Multiphase Flow, 1999, 25(5): 755−794. doi: 10.1016/S0301-9322(98)00048-2
Mittal R, Iaccarino G. Immersed boundary methods[J]. Annual Review of Fluid Mechanics, 2005, 37(1): 239−261. doi: 10.1146/annurev.fluid.37.061903.175743
Peskin C S. The immersed boundary method[J]. Acta Numerica, 2002, 11: 479−517. doi: 10.1007/springerreference_66908
Verzicco R. Immersed boundary methods: Historical perspective and future outlook[J]. Annual Review of Fluid Mechanics, 2023, 55(1): 129−155. doi: 10.1146/annurev-fluid-120720-022129
Mittal R, Seo J H. Origin and evolution of immersed boundary methods in computational fluid dynamics[J]. Physical Review Fluids, 2023, 8(10): 100501. doi: 10.1103/PhysRevFluids.8.100501
Fadlun E A, Verzicco R, Orlandi P, et al. Combined immersed-boundary finite-difference methods for three-dimensional complex flow simulations[J]. Journal of Computational Physics, 2000, 161(1): 35−60. doi: 10.1006/jcph.2000.6484
Liu W T, Zhang A M, Miao X H, et al. Investigation of hydrodynamics of water impact and tail slamming of high-speed water entry with a novel immersed boundary method[J]. Journal of Fluid Mechanics, 2023, 958: A42. doi: 10.1017/jfm.2023.120
Mittal R, Bhardwaj R. Immersed boundary methods for thermofluids problems[J]. Annual Review of Heat Transfer, 2021, 24.
Huang Q, Liu Z, Wang L, et al. Streamline penetration, velocity error, and consequences of the feedback immersed boundary method [J]. Physics of Fluids, 2022, 34(9).
Uhlmann M. An immersed boundary method with direct forcing for the simulation of particulate flows[J]. Journal of Computational Physics, 2005, 209(2): 448−476. doi: 10.1016/j.jcp.2005.03.017
Van Noordt W, Ganju S, Brehm C. An immersed boundary method for wall-modeled large-eddy simulation of turbulent highMach-number flows[J]. Journal of Computational Physics, 2022, 470: 111583. doi: 10.1016/j.jcp.2022.111583
Constant B, Péron S, Beaugendre H, et al. An improved immersed boundary method for turbulent flow simulations on Cartesian grids[J]. Journal of Computational Physics, 2021, 435: 110240. doi: 10.1016/j.jcp.2021.110240
Succi S. The lattice Boltzmann equation: for fluid dynamics and beyond[M]. Oxford University Press, 2001.
Shu C, Phan-thien N. Special issue on the lattice Boltzmann method[J]. Physics of Fluids, 2022, 34(10).
Oh H, Jo H. Turbulent flow boiling simulation based on pseudopotential lattice boltzmann method with developed wall boundary treatments and unit conversion[J]. Applied Thermal Engineering, 2024, 248: 123148. doi: 10.1016/j.applthermaleng.2024.123148
Simonis S, Oberle D, Gaedtke M, et al. Temporal large eddy simulation with lattice Boltzmann methods[J]. Journal of Computational Physics, 2022, 454: 110991. doi: 10.1016/j.jcp.2022.110991
Wang G, Fei L, Luo K H. Unified lattice Boltzmann method with improved schemes for multiphase flow simulation: Application to droplet dynamics under realistic conditions[J]. Physical Review E, 2022, 105(4): 045314. doi: 10.1103/PhysRevE.105.045314
Feng Z G, Michaelides E E. The immersed boundary-lattice Boltzmann method for solving fluid–particles interaction problems[J]. Journal of Computational Physics, 2004, 195(2): 602−628. doi: 10.1016/j.jcp.2003.10.013
Budinski L. Quantum algorithm for the advection–diffusion equation simulated with the lattice Boltzmann method.[J]. Quantum Information Processing, 2021, 20(2).
Smith S, Michalski P, Carette J, et al. State of the practice for Lattice Boltzmann method software[J]. Archives of Computational Methods in Engineering, 2024, 31(1): 313−350. doi: 10.1007/s11831-023-09981-2
Guo Z L, Zheng, C G, Shi, B C. Discrete lattice effects on the forcing term in the lattice Boltzmann method[J]. Physical Review E, 2002, 65(4): 046308. doi: 10.1103/PhysRevE.65.046308
Qian Y H, D’humières D, Lallemand P. Lattice BGK models for Navier-Stokes equation[J]. Europhysics Letters, 1992, 17(6): 479. doi: 10.1209/0295-5075/17/6/001
Timm K, Kusumaatmaja H, Kuzmin A, et al. The lattice Boltzmann method: principles and practice[J]. Cham, Switzerland: Springer International Publishing AG, 2016.
Guo Z, Shu C. Lattice Boltzmann method and its application in engineering: vol. 3[M]. World Scientific, 2013.
Lallemand P, Luo L S. Theory of the lattice Boltzmann method: Dispersion, dissipation, isotropy, Galilean invariance, and stability[J]. Physical Review E, 2000, 61(6): 6546. doi: 10.1103/PhysRevE.61.6546
D’humières D. Multiple–relaxation–time lattice Boltzmann models in three dimensions[J]. Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 2002, 360(1792): 437−451. doi: 10.1098/rsta.2001.0955
Tran S B Q, Leong F Y, Le Q T, et al. Lattice Boltzmann Method for high Reynolds number compressible flow[J]. Computers Fluids, 2022, 249: 105701. doi: 10.1016/j.compfluid.2022.105701
Yu H, Luo L S, Girimaji S S. LES of turbulent square jet flow using an MRT lattice Boltzmann model[J]. Computers fluids, 2006, 35(8- 9): 957−965. doi: 10.1016/j.compfluid.2005.04.009
Goldstein D, Handler R, Sirovich L. Modeling a no-slip flow boundary with an external force field[J]. Journal of Computational Physics, 1993, 105(2): 354−366. doi: 10.1006/jcph.1993.1081
Huang W X, Chang C B, Sung H J. An improved penalty immersed boundary method for fluid–flexible body interaction[J]. Journal of Computational Physics, 2011, 230(12): 5061−5079. doi: 10.1016/j.jcp.2011.03.027
Rohde M, Kandhai D, Derksen J J, et al. A generic, mass conservative local grid refinement technique for lattice-Boltzmann schemes[J]. International Journal for Numerical Methods in Fluids, 2006, 51(4): 439−468. doi: 10.1002/fld.1140
Huang W X, Shin S J, Sung H J. Simulation of flexible filaments in a uniform flow by the immersed boundary method[J]. Journal of Computational Physics, 2007, 226(2): 2206−2228. doi: 10.1016/j.jcp.2007.07.002
Zhang W, Jiang Y, Ye Z. Two better loosely coupled solution algorithms of CFD based aeroelastic simulation[J]. Engineering Applications of Computational Fluid Mechanics, 2007, 1(4): 253−262. doi: 10.1080/19942060.2007.11015197
Zhan Hao, Li Wanping, Fang Qinhan, et al. Numerical simulation of the flow around a circular cylinder at varies Reynolds number[J]. Journal of Wuhan University of Technology, 2008, 30(12): 129−132 (in Chinese).
Shields D, Leonard A, Roshko A. Flow-induced vibration of a circular cylinder at limiting structural parameters[J]. Journal of Fluids and Structures, 2001, 15(1): 3−21. doi: 10.1006/jfls.2000.0330
Shen L W, Chan E S, Lin P Z. Calculation of hydrodynamic forces acting on a submerged moving object using immersed boundary method[J]. Computers Fluids, 2009, 38(3): 691−702. doi: 10.1016/j.compfluid.2008.07.002
Rajamuni M M, Thompson M C, Hourigan K. Transverse flow-induced vibrations of a sphere[J]. Journal of Fluid Mechanics, 2018, 837: 931−966. doi: 10.1017/jfm.2017.881
Yao W, Jia X, Zhang H, et al. Suppression of vortex-induced vibration of an elastically mounted sphere by electromagnetic force[J]. Physics of Fluids, 2023, 35(9).
Peng Z R, Huang H, Lu X Y. Hydrodynamic schooling of multiple self-propelled flapping plates[J]. Journal of Fluid Mechanics, 2018, 853: 587−600. doi: 10.1017/jfm.2018.634
Peng Z R, Huang H, Lu X Y. Collective locomotion of two closely spaced self-propelled flapping plates[J]. Journal of Fluid Mechanics, 2018, 849: 1068−1095. doi: 10.1017/jfm.2018.447
Peng Z R, Huang H, Lu X Y. Collective locomotion of two selfpropelled flapping plates with different propulsive capacities[J]. Physics of Fluids, 2018, 30(11).
Sun Y, Peng Z R, Yang D, et al. Dynamics of a rigid-flexible coupling system in a uniform flow[J]. Journal of Fluid Mechanics, 2022, 943: A44. doi: 10.1017/jfm.2022.466
Peng Z R, Sun Y, Yang D, et al. Scaling laws for drag-to-thrust transition and propulsive performance in pitching flexible plates[J]. Journal of Fluid Mechanics, 2022, 941: R2. doi: 10.1017/jfm.2022.268
Tong Binggang, Lu Xiyun. A review on biomechanics of animal flight and swimming[D]. Advances in Mechanics, 2004 (in Chinese).
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