基于互相关的光流测速法在湍流热对流中的应用

田野; 黄仕迪

doi:10.7638/kqdlxxb-2022.0017

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基于互相关的光流测速法在湍流热对流中的应用

专栏——热湍流 | 更新时间：2026-05-28

- 基于互相关的光流测速法在湍流热对流中的应用
- Simultaneous measurements of large- and small-scale flow properties in turbulent convection by cross-correlation based optical flow velocimetry
- 空气动力学学报 2022年40卷第2期页码：215-222
- 作者机构：
  
  1. 南方科技大学力学与航空航天工程系,深圳,518055
  2. 南方科技大学复杂流动及软物质研究中心,深圳,518055
- 作者简介：
  
  田野（1995-），男，博士研究生，研究方向：湍流、浮游生物. E-mail：tiany2020@mail.sustech.edu.cn
  黄仕迪*（1986-），男，副教授，研究方向：湍流、活性物质、海洋动力学. E-mail：huangsd@sustech.edu.cn
- 基金信息：
  
  国家自然科学基金（11702128，91752201，11961160719）
- DOI：10.7638/kqdlxxb-2022.0017
  中图分类号： O357.5
- 纸质出版：2022
- 稿件说明：
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田野, 黄仕迪. 基于互相关的光流测速法在湍流热对流中的应用[J]. 空气动力学学报, 2022, 40(2): 215−222.

TIAN Ye, HUANG Shidi. Simultaneous measurements of large- and small-scale flow properties in turbulent convection by cross-correlation based optical flow velocimetry[J]. 2022, 40(2): 215-222.
田野, 黄仕迪. 基于互相关的光流测速法在湍流热对流中的应用[J]. 空气动力学学报, 2022, 40(2): 215−222. DOI： 10.7638/kqdlxxb-2022.0017

TIAN Ye, HUANG Shidi. Simultaneous measurements of large- and small-scale flow properties in turbulent convection by cross-correlation based optical flow velocimetry[J]. 2022, 40(2): 215-222. DOI： 10.7638/kqdlxxb-2022.0017.

摘要

同时准确地测量大尺度流动结构和小尺度湍流统计特性对于理解湍流的能量传递规律有着重要意义。尽管粒子成像测速（PIV）技术得到了广泛的应用，但由于算法原理的要求以及商用相机分辨率的限制，PIV 技术在同时获取大、小尺度流动特性方面并不实用。另一方面，近年来逐渐引起关注的光流测速法虽然可以实现单像素分辨率的大区域速度场测量，但其准确性通常受限于应用场景而难以保证。本文采用一种基于互相关的光流测速法来分析Rayleigh-Bénard对流的粒子图像，进而同时获得全局速度场和小尺度湍流特性。结果表明，这种方法不仅可以获得与PIV技术一致的全局场和流动强度，还能有效地解析出湍流耗散区的速度结构函数。进一步的，分别基于速度结构函数和定义直接计算而获得的能量耗散率不仅在数值大小上互相吻合，还与直接数值模拟的结果以及理论预测相一致。这些结果表明基于互相关的光流测速法在同时测量大尺度流动结构和小尺度统计特性上有很好的应用潜力。

Abstract

How to accurately measure both large-scale flow structure and small-scale turbulent statistics simultaneously is crucial for understanding the energy transfer mechanism in turbulent flows. Although Particle image velocimetry (PIV) has become the most prominent technique for velocity field measurement

the requirement of its basic principle and the limited spatial resolution of commercial cameras have made current PIV impractical to acquire large- and small-scale flow properties simultaneously. In recent years

optical flow velocimetry has received growing attention because of its capacity in measuring large-area flow field with single-pixel resolution. However

its accuracy is limited by the detailed application circumstances. In this work

we apply a cross-correlation based optical flow velocimetry to analyze the particle images of Rayleigh-Bénard convection

based on which we obtain the global velocity field and small-scale turbulent statistics simultaneously. It is found that this method is capable to obtain the mean flow field that is in good agreement with the PIV result

and meanwhile can resolve the velocity structure function in the dissipation range. Moreover

the energy dissipation rate obtained from the velocity structure function and that directly calculated from the definition agree with each other quantitatively

and they are consistent with previous direct numerical simulation and theoretical prediction as well. These results suggest that the cross-correlation based optical flow velocimetry is a promising tool for simultaneous measurements of large- and small-scale properties in turbulent flows.

关键词

Keywords

references

MONIN A S, YAGLOM A M. Statistical fluid mechanics: Mechanics of turbulence, vol. 2[M]. Cambridge: The MIT Press, 1975.

ADRIAN R J, WESTERWEEL J. Particle image velocimetry[M]. Cambridge: Cambridge University Press, 2011.

RAFFEL M, WILLERT C E, SCARANO F, et al. Particle image velocimetry: A practical guide[M]. 3rd ed. Berlin: Springer, 2018.

ADRIAN R J. Particle-imaging techniques for experimental fluid mechanics[J]. Annual Review of Fluid Mechanics, 1991, 23: 261-304. DOI:10.1146/annurev.fl.23.010191.001401

WANG F, HUANG S D, ZHOU S Q, et al. Laboratory simulation of the geothermal heating effects on ocean overturning circulation[J]. Journal of Geophysical Research: Oceans, 2016, 121(10): 7589-7598. DOI:10.1002/2016JC012068

WANG F, HUANG S D, XIA K Q. Contribution of surface thermal forcing to mixing in the ocean[J]. Journal of Geophysical Research: Oceans, 2018, 123(2): 855-863. DOI:10.1002/2017JC013578

STANISLAS M, OKAMOTO K, KÄHLER C J, et al. Main results of the third international PIV Challenge[J]. Experiments in Fluids, 2008, 45(1): 27-71. DOI:10.1007/s00348-008-0462-z

KÄHLER C J, ASTARITA T, VLACHOS P P, et al. Main results of the 4th international PIV challenge[J]. Experiments in Fluids, 2016, 57(6): 1-71. DOI:10.1007/s00348-016-2173-1

MENDES L P N, RICARDO A M C, BERNARDINO A J M, et al. A comparative study of optical flow methods for fluid mechanics[J]. Experiments in Fluids, 2021, 63(1): 1-26. DOI:10.1007/s00348-021-03357-7

HORN B K P, SCHUNCK B G. Determining optical flow[J]. Artificial Intelligence, 1981, 17(1-3): 185-203. DOI:10.1016/0004-3702(81)90024-2

BARRON J L, FLEET D J, BEAUCHEMIN S S. Performance of optical flow techniques[J]. International Journal of Computer Vision, 1994, 12(1): 43-77. DOI:10.1007/BF01420984

HAUSSECKER H W, FLEET D J. Computing optical flow with physical models of brightness variation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(6): 661-673. DOI:10.1109/34.927465

QUÉNOT G M, PAKLEZA J, KOWALEWSKI T A. Particle image velocimetry with optical flow[J]. Experiments in Fluids, 1998, 25(3): 177-189. DOI:10.1007/s003480050222

RUHNAU P, KOHLBERGER T, SCHNÖRR C, et al. Variational optical flow estimation for particle image velocimetry[J]. Experiments in Fluids, 2005, 38(1): 21-32. DOI:10.1007/s00348-004-0880-5

CORPETTI T, HEITZ D, ARROYO G, et al. Fluid experimental flow estimation based on an optical-flow scheme[J]. Experiments in Fluids, 2006, 40(1): 80-97. DOI:10.1007/s00348-005-0048-y

LIU T S, SHEN L X. Fluid flow and optical flow[J]. Journal of Fluid Mechanics, 2008, 614: 253-291. DOI:10.1017/s0022112008003273

LIU T S, MERAT A, MAKHMALBAF M H M, et al. Comparison between optical flow and cross-correlation methods for extraction of velocity fields from particle images[J]. Experiments in Fluids, 2015, 56(8): 1-23. DOI:10.1007/s00348-015-2036-1

WANG B, CAI Z M, SHEN L X, et al. An analysis of physics-based optical flow[J]. Journal of Computational and Applied Mathematics, 2015, 276: 62-80. DOI:10.1016/j.cam.2014.08.020

OZAWA Y, IBUKI T, NONOMURA T, et al. Single-pixel resolution velocity/convection velocity field of a supersonic jet measured by particle/schlieren image velocimetry[J]. Experiments in Fluids, 2020, 61(6): 1-18. DOI:10.1007/s00348-020-02963-1

HÉAS P, MÉMIN E, PAPADAKIS N, et al. Layered estimation of atmospheric mesoscale dynamics from satellite imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(12): 4087-4104. DOI:10.1109/TGRS.2007.906156

LIU T S, WANG B, CHOI D S. Flow structures of Jupiter's Great Red Spot extracted by using optical flow method[J]. Physics of Fluids, 2012, 24(9): 096601. DOI:10.1063/1.4752227

YANG Z F, JOHNSON M. Hybrid particle image velocimetry with the combination of cross-correlation and optical flow method[J]. Journal of Visualization, 2017, 20(3): 625-638. DOI:10.1007/s12650-017-0417-7

LIU T S, SALAZAR D M, FAGEHI H, et al. Hybrid optical-flow-cross-correlation method for particle image velocimetry[J]. Journal of Fluids Engineering, 2020, 142(5). doi: 10.1115/1.4045572

LIU T S, SALAZAR D M. OpenOpticalFlow_PIV: an open source program integrating optical flow method with cross-correlation method for particle image velocimetry[J]. Journal of Open Research Software, 2021, 9. DOI:10.5334/jors.326

SEONG J H, SONG M S, NUNEZ D, et al. Velocity refinement of PIV using global optical flow[J]. Experiments in Fluids, 2019, 60(11): 1-13. DOI:10.1007/s00348-019-2820-4

SCHMIDT B E, SUTTON J A. Improvements in the accuracy of wavelet-based optical flow velocimetry (wOFV) using an efficient and physically based implementation of velocity regularization[J]. Experiments in Fluids, 2020, 61(2): 1-17. DOI:10.1007/s00348-019-2869-0

WANG H P, HE G W, WANG S Z. Globally optimized cross-correlation for particle image velocimetry[J]. Experiments in Fluids, 2020, 61(11): 1-17. DOI:10.1007/s00348-020-03062-x

OUYANG Z X, YANG H, HUANG Y A, et al. A circulant-matrix-based hybrid optical flow method for PIV measurement with large displacement[J]. Experiments in Fluids, 2021, 62(11): 1-18. DOI:10.1007/s00348-021-03317-1

AHLERS G, GROSSMANN S, LOHSE D. Heat transfer and large scale dynamics in turbulent Rayleigh-Bénard convection[J]. Reviews of Modern Physics, 2009, 81(2): 503-537. DOI:10.1103/revmodphys.81.503

LOHSE D, XIA K Q. Small-scale properties of turbulent Rayleigh-Bénard convection[J]. Annual Review of Fluid Mechanics, 2010, 42: 335-364. DOI:10.1146/annurev.fluid.010908.165152

XIA K Q. Current trends and future directions in turbulent thermal convection[J]. Theoretical and Applied Mechanics Letters, 2013, 3(5): 052001. DOI:10.1063/2.1305201

SHRAIMAN B I, SIGGIA E D. Heat transport in high-Rayleigh-number convection[J]. Physical Review A, 1990, 42(6): 3650-3653. DOI:10.1103/physreva.42.3650

GROSSMANN S, LOHSE D. Scaling in thermal convection: a unifying theory[J]. Journal of Fluid Mechanics, 2000, 407: 27-56. DOI:10.1017/s0022112099007545

LI X M, HE J D, TIAN Y, et al. Effects of Prandtl number in quasi-two-dimensional Rayleigh–Bénard convection[J]. Journal of Fluid Mechanics, 2021, 915: A60. DOI:10.1017/jfm.2021.21

NI R, HUANG S D, XIA K Q. Local energy dissipation rate balances local heat flux in the center of turbulent thermal convection[J]. Physical Review Letters, 2011, 107(17): 174503. DOI:10.1103/PhysRevLett.107.174503

LI X M, HUANG S D, NI R, et al. Lagrangian velocity and acceleration measurements in plume-rich regions of turbulent Rayleigh-Bénard convection[J]. Physical Review Fluids, 2021, 6(5): 053503. DOI:10.1103/physrevfluids.6.053503

THIELICKE W, STAMHUIS E J. PIVlab–towards user-friendly, affordable and accurate digital particle image velocimetry in MATLAB[J]. Journal of Open Research Software, 2014, 2: 30. DOI:10.5334/jors.bl

XIA K Q, SUN C, ZHOU S Q. Particle image velocimetry measurement of the velocity field in turbulent thermal convection[J]. Physical Review E, 2003, 68(6): 066303. DOI:10.1103/PhysRevE.68.066303

SUN C, CHEUNG Y H, XIA K Q. Experimental studies of the viscous boundary layer properties in turbulent Rayleigh–Bénard convection[J]. Journal of Fluid Mechanics, 2008, 605: 79-113. DOI:10.1017/s0022112008001365

HUANG S D, WANG F, XI H D, et al. Comparative experimental study of fixed temperature and fixed heat flux boundary conditions in turbulent thermal convection[J]. Physical Review Letters, 2015, 115(15): 154502. DOI:10.1103/PhysRevLett.115.154502

CHEN X, HUANG S D, XIA K Q, et al. Emergence of substructures inside the large-scale circulation induces transition in flow reversals in turbulent thermal convection[J]. Journal of Fluid Mechanics, 2019, 877: R1. DOI:10.1017/jfm.2019.624

SUN C, ZHOU Q, XIA K Q. Cascades of velocity and temperature fluctuations in buoyancy-driven thermal turbulence[J]. Physical Review Letters, 2006, 97(14): 144504. DOI:10.1103/PhysRevLett.97.144504

ZHOU Q, SUN C, XIA K Q. Experimental investigation of homogeneity, isotropy, and circulation of the velocity field in buoyancy-driven turbulence[J]. Journal of Fluid Mechanics, 2008, 598: 361-372. DOI:10.1017/s0022112008000189

KACZOROWSKI M, XIA K Q. Turbulent flow in the bulk of Rayleigh–Bénard convection: small-scale properties in a cubic cell[J]. Journal of Fluid Mechanics, 2013, 722: 596-617. DOI:10.1017/jfm.2013.74

HUANG S D, XIA K Q. Effects of geometric confinement in quasi-2-D turbulent Rayleigh–Bénard convection[J]. Journal of Fluid Mechanics, 2016, 794: 639-654. DOI:10.1017/jfm.2016.181

DORON P, BERTUCCIOLI L, KATZ J, et al. Turbulence characteristics and dissipation estimates in the coastal ocean bottom boundary layer from PIV data[J]. Journal of Physical Oceanography, 2001, 31(8): 2108-2134. DOI:10.1175/1520-0485(2001)0312108: tcadei2.0.co;2

LUZNIK L, ZHU W, GURKA R, et al. Distribution of energy spectra, Reynolds stresses, turbulence production, and dissipation in a tidally driven bottom boundary layer[J]. Journal of Physical Oceanography, 2007, 37(6): 1527-1550. DOI:10.1175/jpo3076.1

HUANG S D, KACZOROWSKI M, NI R, et al. Confinement-induced heat-transport enhancement in turbulent thermal convection[J]. Physical Review Letters, 2013, 111(10): 104501. DOI:10.1103/PhysRevLett.111.104501

KACZOROWSKI M, CHONG K L, XIA K Q. Turbulent flow in the bulk of Rayleigh–Bénard convection: aspect-ratio dependence of the small-scale properties[J]. Journal of Fluid Mechanics, 2014, 747: 73-102. DOI:10.1017/jfm.2014.154

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