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This paper investigates the characteristics of turbulent structures in combined wave-current boundary layers based on the standard $ k $-$ \varepsilon $ model. Good agreements were found between the numerical results and experimental data of the time-averaged mean velocity profiles. Periodic variations of turbulence parameters within a wave cycle (i.e. vorticity magnitudes, TKE and TKE dissipation rates etc.) were observed. The vorticity magnitudes, TKE and TKE dissipation rates all decrease during the deceleration phase, reach their minimum values during the wave trough, increase during the acceleration phase and reach their maximum values during the wave crest. The variations of turbulent structures are very high in the near-wall regions (53% for TKE dissipation rates), and are quite low in the outer regions (3% for TKE dissipation rates). The wave-current boundary layer thickness increases (decreases) during the deceleration phase (acceleration phase). The model developed in this study has solved the existing issue of low accuracy in the near-bed region by previous models based on the “high Reynolds number methods”. The present model performs well in describing the physical process of turbulence variations under the effects of wave-current interaction. This can provide some guidance for the sediment transport in coastal areas, beach erosion prediction and developments of marine renewable energy.

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本文基于$ k $-$ \varepsilon $ 模型研究了波流边界层内湍流结构特征。研究结果表明,时均流速分布数值解与实验结果高度吻合。一个波周期内湍流结构特征(如:涡量、湍动能、湍动能耗散率等)呈周期性变化规律,波浪作用引起涡量、湍动能及湍动能耗散率均在减速阶段减小,在波谷处达到最低值,而后在加速阶段增大,并在波峰处达到最大值。近壁面处湍流结构变化幅值较大(湍动能耗散率变化可达53%),远离壁面处变化幅值较平均值较小(仅3%)。波流边界层厚度在减速阶段增加,在加速阶段减小。本文所建立的数值模型克服了现有模型因采用“高雷诺数方法”引起的近壁区精度不高问题,可较好地描述波浪作用下湍流结构演变过程的物理机制,为河口海岸地区泥沙运动、岸滩演变及海洋可再生能源的开发利用提供一些指导意义。

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张炫(1990—),女,江苏省南京市人,副研究员,主要从事海岸水动力、波流相互作用、湍流边界层理论研究。E-mail:

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a. Linear axis;b. semi-log scale

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a. 线性坐标;b. 半对数坐标

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Lines for the numerical results; dots for the experimental results

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数值结果用实线表示;实验结果通过点表示

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a. Meshing tests, time step of 0.001 s, meshing of 50 000和200 000;b. time step tests,meshing of 50 000,time steps of 0.005 s and 0.001 s

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a. 网格敏感性测试,时间步长为0.001 s,网格分别为50 000和200 000;b. 时间步长敏感性测试,网格为50 000,时间步长分别为0.005 s和0.001 s

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a. Vorticity distributions during deceleration phases in the whole water column; b. vorticity distributions during deceleration phases near the wall; c. vorticity distributions during acceleration phases in the whole water column; d. vorticity distributions during acceleration phases near the wall

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a. 减速阶段全水深范围内涡度分布;b. 减速阶段近壁处涡度分布;c. 加速阶段全水深范围内涡度分布;d. 加速阶段近壁处涡度分布

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Experimental conditions of the wave-current boundary layers, WCA1 [34]

, figureFileSmall=null, figureFileBig=null, tableContent=
纯流工况CA波流工况WCA1
摩阻流速 $ {u}_{*} $ /(mm·s−18.668.89
底摩擦力 $ {\tau }_{{\mathrm{b}}} $ /($ {{10}^{-3}} $ Pa)75.079.1
边界层动量厚度 $ \theta $/mm11.68.1
外层流速 $ \overline{u}_{{\infty }} $ /(mm·s−1205196
黏度系数${\nu } $ /(mm·s−21.161.02
雷诺数$ {Re}_{\theta }=\;\overline{u}_{{\infty }}\theta /{\nu } $2 0601 550
), ArticleFig(id=1215337923487126126, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212069459276197917, language=CN, label=表1, caption=

波流边界层参数,WCA1 [34]

, figureFileSmall=null, figureFileBig=null, tableContent=
纯流工况CA波流工况WCA1
摩阻流速 $ {u}_{*} $ /(mm·s−18.668.89
底摩擦力 $ {\tau }_{{\mathrm{b}}} $ /($ {{10}^{-3}} $ Pa)75.079.1
边界层动量厚度 $ \theta $/mm11.68.1
外层流速 $ \overline{u}_{{\infty }} $ /(mm·s−1205196
黏度系数${\nu } $ /(mm·s−21.161.02
雷诺数$ {Re}_{\theta }=\;\overline{u}_{{\infty }}\theta /{\nu } $2 0601 550
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波浪运动在底边界层的湍流结构数值研究
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张炫 1, 2 , 郑金海 1 , 张弛 1
海洋学报 | 论文 2023,45(12): 13-24
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海洋学报 | 论文 2023, 45(12): 13-24
波浪运动在底边界层的湍流结构数值研究
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张炫1, 2 , 郑金海1, 张弛1
作者信息
  • 1 河海大学 港口海岸与近海工程学院,江苏 南京 210098
  • 2 大连理工大学 海岸和近海工程国家重点实验室,辽宁 大连 116024
  • 张炫(1990—),女,江苏省南京市人,副研究员,主要从事海岸水动力、波流相互作用、湍流边界层理论研究。E-mail:

Numerical investigation on the turbulent structures in the bottom boundary layers under the effects of waves
Xuan Zhang1, 2 , Jinhai Zheng1, Chi Zhang1
Affiliations
  • 1College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China
  • 2State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
出版时间: 2023-12-31 doi: 10.12284/hyxb2023161
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本文基于$ k $-$ \varepsilon $ 模型研究了波流边界层内湍流结构特征。研究结果表明,时均流速分布数值解与实验结果高度吻合。一个波周期内湍流结构特征(如:涡量、湍动能、湍动能耗散率等)呈周期性变化规律,波浪作用引起涡量、湍动能及湍动能耗散率均在减速阶段减小,在波谷处达到最低值,而后在加速阶段增大,并在波峰处达到最大值。近壁面处湍流结构变化幅值较大(湍动能耗散率变化可达53%),远离壁面处变化幅值较平均值较小(仅3%)。波流边界层厚度在减速阶段增加,在加速阶段减小。本文所建立的数值模型克服了现有模型因采用“高雷诺数方法”引起的近壁区精度不高问题,可较好地描述波浪作用下湍流结构演变过程的物理机制,为河口海岸地区泥沙运动、岸滩演变及海洋可再生能源的开发利用提供一些指导意义。

波流相互作用  /  底部边界层  /  湍流  /  计算流体力学  /  k-ε模型

This paper investigates the characteristics of turbulent structures in combined wave-current boundary layers based on the standard $ k $-$ \varepsilon $ model. Good agreements were found between the numerical results and experimental data of the time-averaged mean velocity profiles. Periodic variations of turbulence parameters within a wave cycle (i.e. vorticity magnitudes, TKE and TKE dissipation rates etc.) were observed. The vorticity magnitudes, TKE and TKE dissipation rates all decrease during the deceleration phase, reach their minimum values during the wave trough, increase during the acceleration phase and reach their maximum values during the wave crest. The variations of turbulent structures are very high in the near-wall regions (53% for TKE dissipation rates), and are quite low in the outer regions (3% for TKE dissipation rates). The wave-current boundary layer thickness increases (decreases) during the deceleration phase (acceleration phase). The model developed in this study has solved the existing issue of low accuracy in the near-bed region by previous models based on the “high Reynolds number methods”. The present model performs well in describing the physical process of turbulence variations under the effects of wave-current interaction. This can provide some guidance for the sediment transport in coastal areas, beach erosion prediction and developments of marine renewable energy.

wave-current interaction  /  bottom boundary layer  /  turbulence  /  CFD  /  k-ε model
张炫, 郑金海, 张弛. 波浪运动在底边界层的湍流结构数值研究. 海洋学报, 2023 , 45 (12) : 13 -24 . DOI: 10.12284/hyxb2023161
Xuan Zhang, Jinhai Zheng, Chi Zhang. Numerical investigation on the turbulent structures in the bottom boundary layers under the effects of waves[J]. Haiyang Xuebao, 2023 , 45 (12) : 13 -24 . DOI: 10.12284/hyxb2023161
实际海岸水动力环境主要由波浪和水流两大环境要素组成,波浪和水流之间非线性相互作用直接控制着近海区域流场的运动学和动力学特征。精准描述波流相互作用下波浪运动和水流运动, 对于波浪发电装置及各类海工建筑物水动力荷载计算、海底管道铺设设计以及泥沙运移和污染物扩散轨迹预报等均具有十分重要意义。因此,波流相互作用一直是海岸工程师关注的热点问题之一。由于波浪和水流之间相互作用不是简单的线性叠加,而整个流场又存在着多种不同尺度,国内外学者对波流相互作用这一复杂的非线性科学问题展开了大量研究。
迄今为止,学者们主要通过解析法、数值模拟以及物模实验对波流相互作用机制进行研究。为了求解流速分布和底摩擦力,学者们对Navier-Stokes(N–S)方程进行数值求解。随着湍流理论的发展,波流相互作用取得了很多进展。
早期的学者们重点探讨底部边界层内运动学和动力学机制,采用代数方法建立垂向一维波流边界层湍流模型,发现波浪对湍流影响最基本表现形式是底摩擦力的增加以及流速分布曲线的变化。因这部分模型不涉及紊动输运方程,故称“零方程模型”。自Lundgren[1]首次提出波流涡黏系数概念后,众多学者们采用不同涡黏系数分布公式封闭紊流模型,建立流速梯度和雷诺应力之间关系,求解得到波流边界层内流速分布、底摩阻系数和底摩擦力。一部分学者提出时不变涡黏系数模型[111];另一部分则提出了随时间变化涡黏系数模型[12]。Umeyama[13]采用普朗特混合长度理论对波流相互作用进行了研究,计算得到波流作用下流速分布。Fredsøe[14]利用动量方程对波流底部边界层进行研究。由于该理论假设外层流场变化时间尺度远远超过波浪边界层内旋涡消失时间尺度,该理论不适用于短周期波浪条件。Soulsby等[15]综合所有代数模型,通过对大量数据进行拟合得出了波流共同作用下底摩擦力数学表达式。Holmedal等[16]对该模型进行推广,使其适用于随机波和湍流共同作用情况。
随着湍流理论的发展,学者们采用数值模拟方法对N–S方程进行求解,主要可分为雷诺平均模型(RANS)、大涡模拟(LES)以及直接数值模拟(DNS)3大类。其中,RANS模型又被分为“单方程模型”、“两方程模型”和“雷诺应力模型”。“单方程模型”和“两方程模型”均依赖于涡黏系数概念,而“雷诺应力模型”(RSM)则对雷诺应力输运方程(Reynolds-Stress Transport Equations)进行直接数值求解,有效克服了涡黏模型局限性,更加适用于高度各向异性流和三维流动。Davies等[17]采用“单方程紊流模型”,该紊动封闭格式较之“零方程模型”精度更高。Son和André[18]采用“两方程紊流模型”研究粗糙壁面下流场,并对此模型进行修改、推广,得到适用于沙纹床面的波流模型。吴永胜等[19]、孙红等[20]、张卓等[21]根据RANS方程,采用不同简化条件,推导了波流相互作用下流动方程,结合不同紊动格式得到了全水深范围内波流同向和波流逆向情况下时均流速剖面。Holmedal等[22]采用k-ε湍流模型,研究波流作用下底部边界层内流场,发现湍流的存在增加了底摩阻系数和湍动能。Teles等[23]分别采用“两方程紊流模型”对波流作用下流场进行数值模拟研究,得到了时均流速分布,通过和Klopman[24]实验结果进行对比,发现了两者具有较好的一致性,但底部边界层内模拟精度存在不足。Zhang等[25]对比了不同紊流模型对计算精度的影响,并证实了k-ε模型的有效性。Zhang等[26]通过数值模拟研究了浅水波和破碎波作用下湍流边界层特征。陈丹丹和林鹏智[27]求解基于RANS方程,通过k-ω紊流模型进行紊流封闭,用VOF方法捕捉自由面,计算得到水流条件与底床粗糙度对全水深范围内流场结构的影响。郑金海等[28]改进了波流边界层控制方程中波浪压强梯度垂向变化关系式,结合两方程湍流模型,建立了可以模拟边界层内外全水深流速剖面的数学模型。张弛等[29]研究了加速度不对称波浪对底部边界层的影响,建立加速度不对称波浪作用下底部边界层数学模型。伍志元等[30]将海浪模型SWAN和区域海洋模型ROMS进行耦合,建立了SWAN-ROMS波流双向实时耦合模型。李诚等[31]建立了同时考虑波致雷诺应力和时均水平压强梯度影响的二阶波浪边界层数学模型,并探讨了浅化波浪边界层流速分布特性及其影响机制。吴丹和张弛[32]基于k-ω两方程紊流模型模拟了粗糙底床上方随机波浪边界层流速、床面剪切应力和紊动能量分布。大涡模拟方法直接计算大尺度湍涡,而对小尺度涡则采用亚格子尺度模型(SubGrid-Scale 模型,简称SGS模型)进行模拟。由于对计算能力的要求很高,大部分波流相互作用模型并不采用该方法进行研究。采用该方法的主要集中于对沙纹床面波流相互作用流场研究[33]。直接数值模拟方法则不采用任何湍流模型,故而可求解得到不同尺度湍流运动。由于其计算成本较高,目前在波流相互作用领域内鲜有报道。
众多学者对波流相互作用下流场进行了物理模型实验。从研究内容上看,主要呈现出3个研究方向:(1)湍流对波浪的影响,主要包括波长、波高、波能谱的影响;(2)波浪对湍流对数流速分布和边界层厚度的影响;(3)波流共同作用下底部剪切应力的增加现象。Kemp和Simons[3435]使用激光多普勒流速仪(LDA)对波流共同作用下流场进行了系统性研究,发现当波流同向(反向)时,流速在靠近自由液面处减小(增加),在底部增加(减小)。Klopman[25]的LDV实验研究发现和Kemp和Simons[3435]结论一致,并在此基础上探究了波浪非对称性对流场运动学的影响;研究表明随机波对时均流速分布影响比线性波影响小。Lodahl等[36]在大型振荡水槽中进行实验,使用LDA得到流速数据并发现时均流速在波流共同作用下呈现对数分布,该发现和Kemp和Simons[3435]结论一致。Umeyama[13]使用LDA测量流速并计算雷诺应力,结果表明波浪作用下时均流速和对数流速分布有差别,且该差别和波高、波周期有关。Umeyama[37]采用粒子图像测速仪(PIV)和粒子追踪测速(PTV)技术得到瞬时流速场和粒子运动轨迹。研究发现在纯波浪作用下,流场呈现周期性的由旋涡构成的环流;在波流共同作用下,该环流形状被破坏。Singh和Debnath[38]使用超声多普勒流速仪(ADV)对波流共同作用下湍流特征进行研究,发现波浪作用下时均流速变化和前人结论一致。该项研究首次在波流相互作用研究领域中提出象限分析概念,但其在纯水流作用下象限分析结果和经典湍流边界层内雷诺应力象限分析结果并不吻合,故其实验数据分析可靠性不高。Xie等[39]通过物模实验探究了极端风浪条件下边界层结构特征,研究发现相位提前小于20°。
综上所述,已有研究主要通过解析方法和数值模拟研究得到波流共同作用下底摩擦力和时均流速分布,并通过物模实验对模型进行验证,发现了波浪作用下湍流边界层内运动学和动力学变化。然而,现有模型主要采用了“高雷诺数方法”,因此在近壁区往往精度不高,且对波流边界层中湍流结构特征缺乏系统研究。已有湍流理论研究表明,泥沙悬浮过程和湍流结构联系紧密。湍流结构通过控制底部剪应力脉动值,进而控制颗粒跃移和掺混,从而影响底床演变。因此,准确模拟波流相互作用下边界层内湍流结构时间、空间分布特征对近岸泥沙输运及岸滩演变机制研究均具有重要科学意义。为此,本文旨在通过对波流相互作用进行数值模拟,系统性探究波浪作用下边界层内湍流结构特征演变过程。
由于本文不涉及能量计算,故控制方程如下,包括连续性方程(式(1))及Navier-Stokes方程(简称N–S方程,见式(2)至式(4)):
$ \frac{\partial u}{\partial x}+\frac{\partial v}{\partial y}+\frac{\partial w}{\partial z}=0 \text{,} $
$ \begin{split} & \frac{\partial \left(\rho u\right)}{\partial t}+\rho u\frac{\partial u}{\partial x}+\rho v\frac{\partial u}{\partial y}+\rho w\frac{\partial u}{\partial z}\\& \quad= -\frac{\partial p}{\partial x}+\nu \left(\frac{{\partial }^{2}u}{\partial {x}^{2}}+\frac{{\partial }^{2}u}{\partial {y}^{2}}+\frac{{\partial }^{2}u}{\partial {z}^{2}}\right)+{f}_{x}\text{,}\end{split}$
$ \begin{split} & \frac{\partial \left(\rho v\right)}{\partial t}+\rho u\frac{\partial v}{\partial x}+\rho v\frac{\partial v}{\partial y}+\rho w\frac{\partial v}{\partial z}\\& \quad = -\frac{\partial p}{\partial y}+\nu \left(\frac{{\partial }^{2}v}{\partial {x}^{2}}+\frac{{\partial }^{2}v}{\partial {y}^{2}}+\frac{{\partial }^{2}v}{\partial {z}^{2}}\right)+{f}_{y} \text{,}\end{split}$
$ \begin{split} & \frac{\partial \left(\rho w\right)}{\partial t}+\rho u\frac{\partial w}{\partial x}+\rho v\frac{\partial w}{\partial y}+\rho w\frac{\partial w}{\partial z}\\& \quad= -\frac{\partial p}{\partial z}+\nu \left(\frac{{\partial }^{2}w}{\partial {x}^{2}}+\frac{{\partial }^{2}w}{\partial {y}^{2}}+\frac{{\partial }^{2}w}{\partial {z}^{2}}\right)+{f}_{z} \text{,}\end{split}$
式中,$ p $代表静压力;$ x $$ y $$ z $表示流向、垂向、展向;$ u $$ v $$ w $表示相应的流速;$ \rho $代表水的密度;$ \nu $表示运动黏度;$ {{f}}_{{x}} $$ {{f}}_{{y}} $$ {{f}}_{{z}} $代表各方向的体积力。
本文中,通过雷诺方程组对黏性底层以外区域进行数值模拟:
$ \frac{\partial \left\langle{{u}_{i}}\right\rangle}{\partial {x}_{i}}=0\text{,} $
$ \begin{split} \frac{\partial \rho \left\langle{{u}_{i}}\right\rangle}{\partial t}+\rho \frac{\partial \left\langle{{u}_{i}}\right\rangle\langle{{u}_{j}}\rangle}{\partial {x}_{j}}=\,& -\frac{\partial \left\langle{p}\right\rangle}{\partial {x}_{i}}+\frac{\partial }{\partial {x}_{j}}\left(\mu \frac{\partial \langle{{u}_{i}}\rangle}{\partial {x}_{j}}+\mu \frac{\partial \langle{{u}_{j}}\rangle}{\partial {x}_{i}}\right)+\\& \frac{\partial \left(-\rho \left\langle{{{u}_{i}}^{{'}}{{u}_{j}}^{{'}}}\right\rangle\right)}{\partial {x}_{j}}+{\rho g}_{i}\text{,}\\[-1pt]\end{split}$
式中, $ \left\langle{{{u}}_{{i}}}\right\rangle $代表时均流速 ($ i $ = 1, 2, 3); $ {{{u}}_{{i}}}{{{'}}} $表示流速脉动值 ($ i $ = 1, 2, 3); $ \langle{{p}}\rangle $表示压力值;$ \mathrm{\mu } $代表动力黏度; $ {g} $表示重力加速度。
本文采用标准k-ε模型对雷诺应力进行模拟,该模型基于下式:
$ \frac{\partial \rho k}{\partial t}+\frac{\partial \rho k\langle{{u}_{j}}\rangle}{\partial {x}_{j}}=\frac{\partial }{\partial {x}_{j}}\left[\left(\mu +\frac{{\mu }_{t}}{{\sigma }_{k}}\right)\frac{\partial k}{\partial {x}_{j}}\right]+{\mu }_{t}{S}^{2}-\rho \varepsilon \text{,} $
$ \begin{split} \frac{\partial \rho \varepsilon }{\partial t}+\frac{\partial \rho \varepsilon \langle{{u}_{j}}\rangle}{\partial {x}_{j}}=\,& \frac{\partial }{\partial {x}_{j}}\left[\left(\mu +\frac{{\mu }_{t}}{{\sigma }_{\varepsilon }}\right)\frac{\partial \varepsilon }{\partial {x}_{j}}\right]+\\& \frac{\varepsilon }{k}\left({C}_{1\varepsilon }{\mu }_{t}{S}^{2}-\rho {C}_{2\varepsilon }\varepsilon \right)\text{,}\end{split}$
$ S=2\sqrt{{S}_{ij}{S}_{ij}} \text{,} $
$ {\mu }_{t}=\rho {C}_{\mu }\frac{{k}^{2}}{\varepsilon } \text{,} $
式中,$ k $代表湍动能TKE;$ \varepsilon $代表TKE耗散;$ \mathrm{\sigma}_k、\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{\sigma}_{\mathrm{\varepsilon}}、 C_{\mathrm{\mu}}、\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }\mathrm{ }C_{1\mathrm{\varepsilon}}、C_{2\mathrm{\varepsilon}} $表示方程封闭系数:${C}_{1\varepsilon }=1.44 $${C}_{2\varepsilon }=1.92 $${C}_{\mu }=0.09 $${{\sigma }_{k}=1.0} $$\sigma _{\varepsilon }=1.3 $
为探究湍流模型对研究结果的影响,基于标准$ k $-$ \omega $模型对雷诺应力进行模拟对比实验:
$ \frac{\partial \rho k}{\partial t}+\frac{\partial \rho k\langle{{u}_{j}}\rangle}{\partial {x}_{j}}=\rho P-{\beta }^{*}\rho \omega k+\frac{\partial }{\partial {x}_{j}}\left[\left(\mu +{\sigma }^{*}\frac{\rho k}{\omega }\right)\frac{\partial k}{\partial {x}_{j}}\right]\text{,} $
$ \frac{\partial \rho \omega }{\partial t}+\frac{\partial \rho \omega \langle{{u}_{j}}\rangle}{\partial {x}_{j}}=\frac{\alpha \omega }{k}\rho P-\beta \rho {\omega }^{2}+\frac{\partial }{\partial {x}_{j}}\left[\left(\mu +\sigma \frac{\rho k}{\omega }\right)\frac{\partial \omega }{\partial {x}_{j}}\right]\text{,} $
$ P={\tau }_{ij}\frac{\partial {u}_{i}}{\partial {x}_{j}} \text{,} $
式中,方程封闭系数为$ \alpha =\dfrac{5}{9};\;\beta =\dfrac{3}{40};\; {\beta }^{\mathrm{*}}=0.0; \;\sigma = {\sigma }^{\mathrm{*}}=0.5 $
低雷诺数模型基于下式对近壁区进行模拟(Wolfshtein[40]):
$ {\mu }_{t,\;{\mathrm{low}}-{{Re_{y}}}}=\rho {C}_{\mu }{l}_{\mu }\sqrt{k} \text{,} $
$ {l}_{\mu }=y{{C}_{l}}^{*}(1-{{\mathrm{e}}}^{-{Re}_{y}/{A}_{\mu }}) \text{,} $
$ {Re}_{y}=\frac{\mathrm{\rho }{{y}}_{w}\sqrt{k}}{\mathrm{\mu }} \text{,} $
式中,$ {{y}}_{w} $表示近壁面第一个网格距离壁面高度;$ {{l}}_{\mathrm{\mu }} $代表长度尺度(Chen 和Patel[41]);$ {{{C}}_{{l}}}^{\mathrm{*}} $$ {A}_{\mathrm{\mu }} $为常数,$ {{{C}}_{{l}}}^{\mathrm{*}}=k{{{C}}_{\mathrm{\mu }}}^{-0.75} $; $ {A}_{\mathrm{\mu }}=70 $
本模型基于Stoke二阶波浪理论造波:
$ \begin{split}\eta=\, & A\;\mathrm{cos}\left(kx-\sigma t\right)+\left(\frac{\text{π}H^2}{8L}\right)\frac{\left[2+\mathrm{cos}{\mathrm{h}}\left(2kh\right)\mathrm{cos}{\mathrm{h}}\left(kh\right)\right]}{\mathrm{sin}{\mathrm{h}}^3\left(kh\right)} \times \\ & \mathrm{cos}\left(2kx-2\sigma t\right)\text{,}\\[-10pt]\end{split} $
$ \sigma =\frac{2\text{π}}{T} \text{,} $
式中,$\eta $ 代表自由液面;$ A $代表波幅;$ k $表示波数;$ L $代表波长;$ {h} $表示水深。
自由重力波的流速分量表示如下:
$ \begin{split} u=\,&\frac{\text{π} H}{T}\frac{{\mathrm{cos}}{\mathrm{h}}(ky+kh)}{{\mathrm{sin}}{\mathrm{h}}\left(kh\right)}{{\mathrm{cos}}}\left(kx-\sigma t\right)+\frac{3}{4}\frac{{\text{π} }^{2}H}{T}\frac{H}{L}\times\\& \frac{{\mathrm{cos}}{\mathrm{h}}(2ky+2kh)}{{{\mathrm{sin}}{\mathrm{h}}}^{4}\left(kh\right)}{{\mathrm{cos}}}\left(2kx-2\sigma t\right) \text{,}\end{split}$
$ \begin{split} v=\,& \frac{\text{π} H}{T}\frac{{\mathrm{sin}}{\mathrm{h}}(ky+kh)}{{\mathrm{sin}}{\mathrm{h}}\left(kh\right)}{{\mathrm{sin}}}\left(kx-\sigma t\right)+\frac{3}{4}\frac{{\text{π} }^{2}H}{T}\frac{H}{L}\times\\& \frac{{\mathrm{sin}}{\mathrm{h}}(2ky+2kh)}{{{\mathrm{sin}}{\mathrm{h}}}^{4}\left(kh\right)}{{\mathrm{sin}}}\left(2kx-2\sigma t\right) .\end{split}$
通过在靠近出口处动量方程中增加消波源实现消波:
$ S1= -C\left(\frac{1}{2}\rho \left|V\right|V\right)f\left(y\right)f\left(x\right) \text{,} $
$ {r}_{z}=\frac{z-{z}_{fs}}{{z}_{b}-{z}_{fs}}\text{,} $
$ {r}_{x}=\frac{x-{x}_{s}}{{x}_{e}-{x}_{s}}\text{,} $
$ f\left(y\right)= 1-{r}_{y}\text{,} $
$ f\left(x\right)={\left({r}_{x}\right)}^{2}\text{,} $
式中,$ {{x}}_{{s}} $$ {{x}}_{{e}} $表示消波区域起点和终点;$ {{z}}_{{f}{s}} $$ {{z}}_{{b}} $代表自由液面和水槽底部;$ V $表示垂直流速;$ C $表示消波系数。
本文采用VOF模型,通过求解单组动量方程并追踪每种流体在整个计算域中体积分数来捕捉水槽中自由液面。通过求解第二相(即水)体积分数的连续性方程,实现水与空气界面的追踪。为避免“显式”算法对当前时间步体积分数值的依赖,采用“隐式”格式求解相体积分数方程。
采用四边形网格(图1),网格大小为50 000,网格在水平方向离散呈均匀分布。已有研究表明,在波浪特定物理过程模拟中(如波浪破碎),长宽比接近1.0有利于提高模拟精度。由于本研究不涉及波浪破碎,且边界层精细化模拟需要较高长宽比,因此,使用较大网格长宽比。经测试,采用四边形网格划分收敛效果较好;若采用1.0长宽比,边界层内湍流结构难以捕捉。在床层附近(第一个网格$ {{y}}^{+} $≈ 0.3)采用“低雷诺数模型”精细化划分网格,避免了前人模型因采用“壁面函数法”(如Teles等[23] )无法完全求解底部边界层的缺陷。由于该位置处于黏性底层,湍流模型在该处并不适用。因此,采用Wolfstein[40]模型对黏性底层进行数值模拟。与湍流模型($ k $-$ \varepsilon $ 模型)相比,Wolfstein[40]模型对湍流黏度模拟更适用于黏性底层。基于此模型对底部边界层模拟的计算精度将在3.1小节中进行进一步阐述。自由表面附近加密网格,进而避免波浪在自由表面处的数值耗散。
采用压力入口和压力出口边界条件,以便产生稳定湍流流动。压力入口设置包括入口流速、湍流参数、自由液面和底部参数设置。压力出口设置与入口边界条件类似;光滑底部采用无滑移壁面条件,不涉及任何粗糙度;计算域顶部边界采用滑移壁面,剪应力为0。
本模型基于瞬态型压力求解器数值求解方程。在空间离散方面,模型采用二阶精度,具有较高分辨率。采用隐式体积分数格式与动量和压力一起迭代求解相位连续性方程。残差目标设定为10−5为收敛标准,且每个时间步长内均实现收敛。时间步长选择0.001 s,具有较高精度和计算速度。对于压力插值方法,PREssure STaggering Option ( PRESTO ! )算法已被推荐用于所有VOF计算。在时间离散方面,模型采用二阶隐式瞬态格式,具有较高精度。
采用Kemp和Simons [34] 在实验室中进行的波流同向实验WCA1工况为算例:$ {T} $ = 1.006 s,$ {H} $ = 20.7 mm,$ {h} $ = 200 mm。通过在水槽中生成稳定湍流后进行数值造波,且波浪随湍流同向传播。
Kemp和Simons [34]实验采用波流水槽进行:长14.5 m,宽0.457 m,深0.69 m。波浪由造波板产生,通过使用循环系统造流。水槽入口处通过钢制闸阀控制来流流量,出口处由3个阀门调节流量,使得水深控制在恒定值$ {h} $ = 200 mm。WCA1工况采用光滑壁面条件,因此壁面粗糙度为0。速度由激光测速仪(LDA)进行测量,波高通过电阻式浪高仪测量。边界层流态相关参数详见表1。由表1雷诺数可知,纯流工况CA处于湍流流态区域,波流工况WCA1处于湍流流态区域。
图2展示了底摩擦系数随粗糙系数变化关系图。图中,红色实线代表Kajiura[42]模型预测值,蓝色实线代表Swart[43]模型预测值,紫色实线代表Sleath[44]模型预测值,黑色散点表示实验测量值。由图可见,Kajiura[42]模型预测更接近实验测量值。Swart[43]模型预测值在粗糙系数较小时与实验值相比误差较大。Sleath[44]模型仅在粗糙系数趋于无穷大时成立,因此,其适用性有限。
图3a图3b给出了WCA1工况线性和半对数坐标下时均流速剖面图。图中,红色实线代表$ k $-$\varepsilon $模型数值结果,黑色实线代表$ k $-$ \omega $模型数值结果,绿色散点表示实验结果。由图可知,近壁面处由于$ k $-$\varepsilon $模型倾向于低估流场中涡的产生,其计算结果不如$ k $-$ \omega $模型数值结果。外层区域由于远离边界,$ k $-$\varepsilon $湍流模型计算结果优于$ k $-$ \omega $模型数值结果。研究结果表明,基于$ k $-$\varepsilon $湍流模型得出的计算结果与Kemp和Simons[34]实验数据在整个水深范围内均吻合较好,最大相对误差在3%以内。因此,本文将使用$ k $-$\varepsilon $湍流模型对波流相互作用进行数值研究及结果讨论。
图4展示了光滑床面附近波致流速(以18°相位间隔),计算结果总体与实验数据吻合,在减速阶段边界层流速的数值结果与实验数据相对误差略大,最大相对误差为8%。
图5给出了全水深范围内以18°为时间间隔的相位平均流速分布。通过将瞬时流速时间序列按波周期划分为不同的序列段,每个序列段则包含一个完整波形,通过对不同序列段相同相位的瞬时流速进行平均,得到相位平均流速。由于相位平均流速是波浪同相位流速进行平均,因此与时间平均相反,相位平均值随相位发生变化。数值结果与Kemp和Simons[34]实验数据结果高度一致,在近壁面处0.4 mm范围内均存在回流现象并导致强剪切层的产生。此区域常伴有Kelvin-Helmholtz 漩涡。
图6a图6b给出了波流作用下自由液面高程和底部剪应力的时间序列。由图可见,自由液面高程与底部剪应力之间存在相位提前现象,底部剪应力峰值发生在波峰之前,且相位差为36°,与前人研究结果吻合较好。
为探究数值模型计算收敛性,本文对网格尺寸和时间步长进行了敏感性测试。图7a显示了网格尺寸大小对模拟结果的影响。由图可见,粗网格(200 000)和细网格(50 000)计算条件下时均流速剖面图结果一致。由于计算成本较高,本文将网格单元数限制在20万,不再讨论更精细的网格。图7b显示了时间步长对计算结果的影响。由图可知,时间步长的减小对计算结果并无明显影响,故计算结果已收敛。
由上述比较可知,网格大小为50 000、时间步长为0.001 s的数值模型可对波流边界层进行有效计算。因此,本文第4节将基于该计算条件对WCA1工况条件下波流边界层内湍流结构特征进行进一步阐述、分析。
湍流理论中经典概念湍涡涡度是描述流体质点在旋转过程中旋转程度的重要参数:
$ \mathrm{\omega }\left(z\right)=\frac{1}{2}\left(\frac{\partial {u}}{\partial {y}}-\frac{\partial {v}}{\partial {x}}\right) \text{,} $
式中,$ {x} $$ {y} $$ {z} $ 分别代表流向、展向、垂向方向;$ {u} $$ {v} $$ {w} $代表相应的流速。
图8给出了WCA1工况条件下不同相位时期涡量分布图,图8b图8d分别给出了近底部区域涡度分布。从图中可以看出,涡量大小在减速阶段减小,在加速阶段增大。在减速阶段,涡量大小随距底部距离增加而增加,达到最大值,后在上部区域内逐渐减小。减速阶段涡度分布极值点随相位角不断上升,并在波谷时提升到最高处。当整体流动进入加速阶段时,涡度分布极值点随相位角不断下降,并在波峰处下降到最低处。上述研究结果表明,湍流边界层内马蹄形漩涡强度在靠近床面处随距底部距离先增大后减小。在加速(减速)阶段,湍流涡旋强度增大(减小)。波浪边界层厚度在加速期减小,并在减速期增加。
图9给出了不同高度处一个波周期内涡量大小的历时变化曲线。研究结果表明,在不同位置,涡量大小均随相位角呈周期性变化,在减速阶段减小,在波谷达到最小值;该值随后在加速阶段增加,并在波峰到达时达到最大值。由图可知,近壁面处涡度变化幅值较大(可达45%),远离壁面处涡度变化幅值较平均值较小(5%)。
湍涡涡度在一个波周期内分布特征可由边界层理论解释。当波流处于减速阶段,波浪作用导致边界层被压缩,边界层内马蹄型涡旋被压缩。由边界层理论可知,漩涡被压缩引起涡度减小。相反,当波流处于加速阶段,波浪抬升作用导致边界层被拉伸,边界层内马蹄型涡旋被拉伸,从而引起涡度增大。
湍涡涡度的周期性变化反映了波浪作用对湍流马蹄型涡旋的影响。当波流处于加速阶段,边界层底部较强漩涡由于波浪作用被抬升、抛射至更高处,引起当地湍流漩涡涡度增强。相反,当波流处于减速阶段,外层漩涡被波浪带至较低处,引起当地湍涡强度降低。
湍流理论中,湍动能表示通过湍流漩涡产生的湍流能量(热能和机械能总和),直接决定了边界层内能量输送和动量传递。本文中湍动能由定义式计算:
$ {\mathrm{TKE}}=\frac{1}{2}\left( \overline{{{u}^{'}}^{2}}+ \overline{{{v}^{'}}^{2}}+ \overline{{w{'}}^{2}}\right) \text{,} $
式中,$ {u}^{{'}} $表示流向流速脉动值;$ {v}^{{'}} $表示展向流速脉动值;$ {w}^{{'}} $表示垂向流速脉动值。
图10给出了不同位置一个波浪周期内湍动能历时变化曲线。研究结果表明,湍动能随波峰、波谷均产生周期性变化:在减速期湍动能减小,在波谷处达到最低值,并在加速期不断增加。由图10a可知,对于远离壁面处的流场,湍动能变化幅值较小(2%);由图10b可知,对于近壁区,幅值变化较大(49%)。
湍动能在一个波周期内分布特征可由波浪对湍流结构影响解释。当波流处于加速期阶段,由于波面抬升导致底部水流被抬升至更高位置。由于底部水流流速梯度更大,湍动能更强,因此湍动能在波浪作用下增加,使得更多能量从平均动能转化为湍流脉动动能。加速阶段底部剪应力的增加也导致湍动能增大:由于加速阶段期间底部剪应力增大,湍动能产生项增大,因此湍动能增加。相反,当波流处于减速期阶段,波面下降导致外层流体被压缩至更低处。由于外层流体流速梯度较小,湍动能更小,因此湍动能在波浪作用下减小。减速阶段底部剪应力的减小也加剧了湍动能的降低:由于减速阶段底部剪应力减小,湍动能产生降低,因此湍动能减小。
湍动能的周期性分布特征反映了波浪作用对湍流掺混的影响。由于波浪作用,湍涡涡度在加速阶段增大,减速阶段减小。当波流处于加速阶段,马蹄型漩涡引发湍流掺混、能量输送及动量传递均更为强烈,因而湍动能增加。当波流处于减速阶段,马蹄型漩涡引起的湍流掺混、能量输送及动量传递均减弱,因此湍动能减小。
湍流理论中,湍动能耗散率表示湍流运动能量耗散为热能的能量,是湍流能量传输过程中损耗的一种表示:
$ \varepsilon=2\nu \overline{{s}_{ij}{s}_{ij}} \text{,} $
式中,$ {s}_{ij}=\dfrac{1}{2}\left(\dfrac{\partial {u}_{i}^{{'}}}{\partial {x}_{j}}+\dfrac{\partial {u}_{j}^{{'}}}{\partial {x}_{i}}\right) $ 代表湍流变形率 ($ i={1,\;2},\;3 $$ j={1,\;2},\;3 $)。
图11给出了距床面不同位置处一个波浪周期内湍动能耗散率的历时变化曲线。研究结果表明,湍动能耗散均随波峰、波谷产生周期性变化。对于近壁区,湍动能耗散率变化幅值较大(达53%);对于远离壁面处的流场,变化幅值较低(3%)。由于较小的涡具有更强的耗散率,该研究结果表明湍流漩涡尺寸在减速阶段增加,在加速阶段减小。
湍动能耗散率在一个波周期内分布情况可由底部剪应力的周期性变化解释。在加速期阶段,由于底部剪应力增加导致摩擦阻力增大,黏性阻力的作用引起更多湍动能被耗散至热能;在减速期阶段,由于底部剪应力减小导致摩擦阻力降低,从而引起较少湍动能被耗散。由于底部剪应力产生的湍动能随波浪作用迅速耗散,因此,湍动能也随波浪呈周期性变化规律,与4.2节结果一致。
由湍流边界层经典理论可知(Schlichting[45]),涡旋尺寸与湍动能耗散率成反比,即:大尺度漩涡产生湍动能,并传递至小尺度漩涡,直至更小尺度漩涡耗散为热能。由于湍动能耗散率在加速阶段增大、减速阶段减小,因此,湍流Kolmogorov尺度在加速阶段减小、减速阶段增大。
本文基于CFD方法模拟了波浪与湍流之间相互作用,在模型中通过采用“低雷诺数方法”对近壁区进行了精细化模拟。湍流模型采用标准$ k $-$ \varepsilon $模型,基于Stokes波理论数值造波;多相流模拟采用VOF模型。时均流速剖面计算结果与实验数据吻合较好。底部剪应力相对于自由液面高程的相位提前与现有理论高度吻合,表明模型可以较好地复演波流相互作用下边界层内流场分布特征。通过分析波浪作用下湍流结构变化规律,发现了湍流结构的周期性分布特征。在加速(减速)阶段,波流边界层内湍流涡旋强度增加(减小)。涡量垂直分布表明:在减速阶段,涡度在床面附近增加,随着距离底部距离增加而减小。湍流结构特征(涡度大小、湍动能和湍动能耗散率)随波峰和波谷呈周期性变化:在减速阶段减小,随波谷达到最低值;后在加速阶段不断增大,并随波峰达到最高值。近壁面处湍流结构变化幅值较大(湍动能变化可达49%),远离壁面处变化幅值较平均值较小(仅2%)。上述研究结论适用于波流共同作用下的湍流结构特征,并可推广至任意平均流速条件。
  • 国家自然科学基金项目(51909074);大连理工大学海岸和近海工程国家重点实验室开放基金项目(LP2105);中国博士后科学基金项目(2019M661713);中央高校自由探索项目(B210202024)。
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2023年第45卷第12期
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doi: 10.12284/hyxb2023161
  • 接收时间:2023-05-15
  • 首发时间:2025-12-28
  • 出版时间:2023-12-31
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  • 收稿日期:2023-05-15
  • 修回日期:2023-08-03
基金
国家自然科学基金项目(51909074);大连理工大学海岸和近海工程国家重点实验室开放基金项目(LP2105);中国博士后科学基金项目(2019M661713);中央高校自由探索项目(B210202024)。
作者信息
    1 河海大学 港口海岸与近海工程学院,江苏 南京 210098
    2 大连理工大学 海岸和近海工程国家重点实验室,辽宁 大连 116024
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