-
湍流直接数值模拟受限于计算域尺寸, 无法完全解析湍动能谱低波数区的所有波数, 造成计算数据中部分大尺度信息丢失. 随着湍流的演化, 湍动能谱的峰值波数会向低波数迁移, 使得低波数缺失现象进一步加剧, 导致所计算的积分尺度和湍流耗散相关统计量偏离物理真实. 本研究基于von Kármán谱模型的推广形式, 充分考虑数值计算未完全解析的低波数区湍动能谱, 并利用该模型对均匀各向同性自由衰减湍流的积分尺度和湍流耗散相关统计量进行修正. 研究结果表明: 修正后的积分尺度$ L $显著高于未修正值, 且其随时间的变化规律符合Saffmann理论预测的$ L\propto {t}^{2/5} $幂律关系; 修正前湍流耗散系数$ {C}_{\varepsilon } $为常数, 说明此时湍流为均衡状态, 而修正后耗散系数$ {C}_{\varepsilon } $的演化满足湍流非均衡耗散规律$ {C}_{\varepsilon }\sim{Re}_{\varLambda }^{-1} $. 将数值计算缺失的低波数区湍动能谱引入后, 湍流状态由均衡向非均衡转变, 说明大尺度对湍流耗散有很强的调控作用, 这与学术界普遍认为的大尺度结构是造成湍流非均衡性本质原因的结论相一致. 在有限雷诺数或者受初始条件影响较大的湍流流动中, 大尺度结构对流动的影响显著, 湍流无法在全尺度实现均衡.
-
关键词:
- 各向同性湍流 /
- 积分尺度 /
- 低波数缺失 /
- von Kármán谱模型
Turbulence modeling relies critically on accurate characterization of large-scale structures, with the integral length scale $ L $ serving as a key parameter for industrial applications ranging from combustion stability optimization to wind farm design and aerodynamic load prediction. However, direct numerical simulation (DNS) of turbulence faces inherent limitations in resolving all wavenumbers within the low-wavenumber region of the turbulent kinetic energy spectrum due to finite computational domain sizes. This unresolved low-wavenumber deficiency leads to incomplete characterization of large-scale structures and introduces systematic deviations in key statistical quantities, particularly the integral length scale $ L $ and turbulence dissipation coefficient $ {C}_{\varepsilon } $. As turbulence evolves, the spectral peak wavenumber $ {k}_{p} $ migrates toward lower wavenumbers, exacerbating the loss of large-scale information and causing computed statistics to diverge from physical reality. In this study, we perform high-fidelity DNS of homogeneous isotropic decaying turbulence in a periodic cubic domain of side length 4π with $ {384}^{3} $ grid points. The DNS is executed by using a standard pseudospectral solver and a fourth-order Runge-Kutta time integration scheme, with a semi-implicit treatment of the viscous term. The spatial resolution $ {k}_{\mathrm{m}\mathrm{a}\mathrm{x}}\eta =1.65 $ ensures adequate resolution of dissipative scales ($ \eta $ is the Kolmogorov scale). Simulations start from a fully developed field initialized with a spectrum matching Comte-Bellot and Corrsin’s experimental data and evolve within a time interval where turbulence exhibits established isotropic decay characteristics. Existing correction models, predominantly based on equilibrium turbulence assumptions, fail to accurately represent the non-equilibrium dynamics governed by large-scale structures. According to the generalized von Kármán spectrum model, we use a correction framework to explain the unresolved low-wavenumber contributions in homogeneous isotropic decaying turbulence. The DNS data reveal that the uncorrected integral scale $ {L}_{{\mathrm{m}}} $ significantly underestimates the true $ L $, with errors escalating as $ {k}_{L}/{k}_{p} $ increases, where $ {k}_{L} $ is the minimum resolvable wavenumber in the simulation domain. After correction, $ L $ exhibits a temporal evolution following the Saffmann-predicted power-law relationship $ L\propto {t}^{2/5} $, contrasting sharply with the underestimated pre-correction values. Although the spectral correction substantially increases the spectral integral scale $ L $, its value remains less than the physically derived integral scale $ \varLambda $ computed from the velocity correlation function, which is primarily due to the finite domain size limiting large-scale statistics and the moderate grid resolution, though higher-resolution simulations with the same domain show $ L $ converging towards $ \varLambda $. Notably, the unmodified dissipation coefficient $ {C}_{\varepsilon } $ remains constant, which is consistent with equilibrium turbulence assumptions, whereas the corrected $ {C}_{\varepsilon } $ evolves according to the non-equilibrium scaling law $ {C}_{\varepsilon }\sim{Re}_{\varLambda }^{-1} $. Further analysis confirms that the ratio $ L/\varLambda $ shifts from Kolmogorov’s $ {Re}_{\varLambda }^{1} $dependence to a Reynolds-number-independent plateau after correction, fundamentally changing the turbulence dissipation paradigm. This transition from equilibrium to non-equilibrium dissipation behavior underscores the dominant role of large-scale structures in regulating energy cascade dynamics. Our results demonstrate that finite Reynolds numbers or strong initial-condition effects amplify the non-equilibrium characteristics of turbulence, hindering the full-scale equilibrium. These findings reconcile long-standing theoretical discrepancies and provide a paradigm for modeling scale interactions in turbulence.-
Keywords:
- isotropic turbulence /
- integral length scale /
- low-wavenumber deficiency /
- von Kármán spectrum model
-
图 1 算例能谱$ E\left(k\right) $随波数的演化. 其中能谱$ E\left(k\right) $用湍动能耗散率$ \text{e} $和运动黏度$ \text{n} $无量纲化, 波数$ k $用耗散尺度$ \text{h} $无量纲化. 双点划线满足$ E\left(k\right)\sim{k}^{-5/3} $关系. 能谱在惯性子区满足$ {k}^{-5/3} $标度律
Fig. 1. Example of the energy spectrum $ E\left(k\right) $ evolution with wavenumber. The energy spectrum $ E\left(k\right) $ is non-dimensionalized by the turbulent kinetic energy dissipation rate $ \varepsilon $ and the kinematic viscosity $ \text{n} $, while the wavenumber $ k $ is non-dimensionalized by the dissipation scale $ \text{h} $. The double dot-dash line corresponds to the $ E\left(k\right)\sim $$ {k}^{-5/3} $ relationship. The energy spectrum in the inertial subrange follows the $ {k}^{-5/3} $ scaling law.
图 3 泰勒尺度随时间的演化特征 (a) 泰勒尺度平方的时间导数, 曲线在$ t > 0.29725 $后呈现平坦特征, 双点划线为$ n=-1.40 $理论线; (b) 泰勒尺度平方, 双点划线满足$ {\varLambda }^{2}\sim{t}^{1} $关系
Fig. 3. Evolution characteristics of the Taylor scale over time: (a) Time derivative of the Taylor scale squared. The curve exhibits a flat characteristic for $ t > 0.29725 $, with the double dot-dash line representing the theoretical line $ n=-1.40 $; (b) Taylor scale squared. The double dot-dash line corresponds to the $ {\varLambda }^{2}\sim{t}^{1} $ relationship.
图 4 湍动能随时间演化. 双点划线满足$ {u}^{2}\sim{t}^{-6/5} $关系. 已知修正前后$ {u}^{2} $变化很小, 所以只做修正后的湍动能曲线
Fig. 4. Evolution of turbulent kinetic energy over time. The double dot-dash line corresponds to the $ {u}^{2}\sim{t}^{-6/5} $ relationship. Since the variation in $ {u}^{2} $ before and after correction is negligible, only the corrected turbulent kinetic energy curve is plotted.
图 7 修正前后耗散系数$ {C}_{\varepsilon } $随泰勒雷诺数$ {Re}_{\varLambda } $的变化. 双点划线满足$ {C}_{\varepsilon }\sim{Re}_{\varLambda }^{-1} $关系. 箭头指示方向为时间演化方向
Fig. 7. Variation of the dissipation coefficient $ {C}_{\varepsilon } $ with the Taylor Reynolds number $ {Re}_{\varLambda } $ before and after correction. The double dot-dash line corresponds to the $ {C}_{\varepsilon }\sim{Re}_{\varLambda }^{-1} $ relationship. The arrows indicate the direction of time evolution.
图 8 修正前后特征尺度$ L/\varLambda $比值随泰勒雷诺数$ {Re}_{\varLambda } $的演化. 双点划线满足$ L/\varLambda \sim{Re}^{1} $关系
Fig. 8. Evolution of the characteristic scale ratio $ L/\varLambda $ with the Taylor Reynolds number $ {Re}_{\varLambda } $ before and after correction. The double dot-dash line corresponds to the $ L/\varLambda \sim{Re}^{1} $ relationship.
-
[1] Pope S B 2001 Turbulent flows (Cambridge: Cambridge University Press
[2] Warhaft Z, Lumley J L 1978 J. Fluid Mech. 88 659
Google Scholar
[3] Porté-Agel F, Bastankhah M, Shamsoddin S 2020 Boundary-Layer Meteorol. 174 1
Google Scholar
[4] Trush A, Pospíšil S, Kozmar H 2020 WIT Trans. Eng. Sci. 128 113
[5] Cotela Dalmau J, Oñate Ibáñez de Navarra E, Rossi R 2016 Applications of turbulence modeling in civil engineering (Barcelona: CIMNE
[6] Li M, Li M, Sun Y 2021 J. Sound Vib. 490 115721
Google Scholar
[7] Taylor G I 1935 Proc. R. Soc. London, Ser. A 151 421
Google Scholar
[8] Tennekes H, Lumley J L 1972 A first course in turbulence (Cambridge: MIT Press
[9] Kolmogorov A N 1941 Docl. Akad. Nauk SSSR A 31 538
[10] Dryden H L 1943 Q. Appl. Math. 1 7
Google Scholar
[11] Saffman P G 1967 J. Fluid Mech. 27 581
Google Scholar
[12] Oberlack M 2002 Proc. Appl. Math. Mech. 1 294
Google Scholar
[13] Comte-Bellot G, Corrsin S 1966 J. Fluid Mech. 25 657
Google Scholar
[14] Bos W J T, Shao L, Bertoglio J P 2007 Phys. Fluids 19 045101
Google Scholar
[15] Ishihara T, Morishita K, Yokokawa M, Uno A, Kaneda Y 2016 Phys. Rev. Fluids 1 082403
Google Scholar
[16] Thornber B 2016 Phys. Fluids 28 105107
[17] O’Neill P L, Nicolaides D, Honnery D, Soria J 2004 15th Australasian Fluid Mechanics Conference The University of Sydney, Sydney, Australia, December 13–17, 2004 p1
[18] Ishihara T, Gotoh T, Kaneda Y 2009 Annu. Rev. Fluid Mech. 41 165
Google Scholar
[19] Goto S, Vassilicos J C 2015 Phys. Lett. A 379 1144
Google Scholar
[20] George W K 1992 Phys. Fluids A 4 1492
[21] Liu F, Lu L P, Bos W J T, Fang L 2019 Phys. Rev. Fluids 4 084603
Google Scholar
[22] Wang H, Sonnenmeier J R, Gamard S, George W 2000 International Congress of Theoretical and Applied Mechanics Chicago, IL, August 27–September 1, 2000 p8
[23] de Bruyn Kops S M, Riley J J 1998 Phys. Fluids 10 2125
Google Scholar
[24] Von Karman T 1937 Proc. Natl. Acad. Sci. U. S. A. 23 98
Google Scholar
[25] Rogallo R S 1981 Numerical experiments in homogeneous turbulence (Washington: NASA
[26] Wang C H, Fang L 2018 Chin. Phys. Lett. 35 080501
Google Scholar
[27] Comte-Bellot G, Corrsin S 1966 J. Fluid Mech. 25 657
Google Scholar
[28] Gamard S, George W K 2000 Flow Turbul. Combust. 63 443
Google Scholar
[29] Wang H, George W K 2002 J. Fluid Mech. 459 429
Google Scholar
[30] George W K, Wang H, Wollblad C, Johansson T G 2001 14th Australasian Fluid Mechanics Conference Adelaide University, Adelaide, Australia, December 10–14, 2001 p41
[31] Batchelor G K 1953 The theory of homogeneous turbulence (Cambridge: Cambridge University Press
[32] Bos W J T, Rubinstein R 2017 Phys. Rev. Fluids 2 022601
Google Scholar
[33] Steiros K 2022 Phys. Rev. E 105 035109
[34] Goto S, Vassilicos J C 2016 Phys. Rev. E 94 053108
Google Scholar
[35] Krogstad P Å, Davidson P A 2012 Phys. Fluids 24 035103
Google Scholar
[36] Steiros K 2022 Phys. Rev. Fluids 7 104607
Google Scholar
[37] Vassilicos J C 2015 Annu. Rev. Fluid Mech. 47 95
Google Scholar
[38] Mazellier N, Vassilicos J C 2010 Phys. Fluids 22 075101
Google Scholar
[39] Valente P C, Vassilicos J C 2012 Phys. Rev. Lett. 108 214503
Google Scholar
[40] Liu F, Fang L, Shao L 2020 Chin. Phys. B 29 114702
Google Scholar
计量
- 文章访问数: 367
- PDF下载量: 18
- 被引次数: 0