River-Lake Protection and Regulation

Numerical Simulation of Grab Dredging on Flow Field and Sdiment Suspension Pattern in Construction Area

  • LONG Rui , 1, 2 ,
  • JIN Zhong-wu 1, 2 ,
  • Tomoaki NAKAMURA 3 ,
  • Yonghwan CHO 3 ,
  • Norimi MIZUTANI 3
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  • 1 River Department,Changjiang River Scientific Research Institute,Wuhan 430010,China
  • 2 Key Laboratory of Ministry of Water Resources on River and Lake Regulation and Flood Control in the Middle and Lower Reaches of the Changjiang River, Changjiang River Scientific Research Institute, Wuhan 430010, China
  • 3 Nagoya University,Nagoya 464-8603,Japan

Received date: 2024-03-11

  Revised date: 2024-07-19

  Online published: 2024-12-27

Abstract

[Objectives] The sedimentation of rivers and lakes poses a persistent challenge to water resource management. Dredging, while effective for removing excess sediment and restoring channel capacity, often triggers the resuspension of contaminated bed material, leading to secondary pollution and ecological disturbance. Among various dredging techniques, grab-type dredging is widely used for its adaptability to diverse bed conditions, but its impact on local flow fields and sediment dynamics remains underexplored. This study addresses this gap by employing a full-scale two-dimensional numerical simulation using the FS3M (Fluid-Structure-Sediment-Seabed Interaction Model) to investigate the hydrodynamic and sediment suspension responses during grab bucket descent. The aim is to identify descent strategies that minimize sediment resuspension and contribute to more environmentally friendly dredging operations. [Methods] The simulation framework integrates Large Eddy Simulation (LES) for turbulent flow, a Volume of Fluid (VOF) method for water-sediment interface tracking, and a sediment transport module (STM) for modeling both suspended and bedload sediment processes. A 23 m3 environmentally friendly grab bucket is modeled descending in a symmetric two-dimensional domain that includes a 3-meter-thick sand bed. Multiple descent cases are considered: a baseline with constant velocity (1.0 m/s) and six modified cases where the grab decelerates at different heights (1.0 m, 3.0 m, 5.0 m) above the bed, with secondary descent speeds of either 0.33 m/s or 0.50 m/s. Bed deformation, flow velocity, and sediment concentration distributions are monitored over time to assess each strategy’s environmental performance. [Results] Simulation results show that the grab bucket generates significant flow disturbances during its descent, especially near the sediment bed, causing bed erosion and sediment entrainment. In the baseline scenario, rapid descent leads to high flow velocities at the bed surface and the formation of vortices that promote sediment resuspension and diffusion. In contrast, cases involving velocity reduction prior to bed contact exhibit a marked decrease in sediment disturbance. Specifically: 1)Lowering the descent speed reduces the near-bed flow velocity and suppresses the entrainment of suspended sediment. 2)Starting the deceleration at 3.0 meters above the bed (Case D3) with a reduced speed of 0.33 m/s achieves the best balance between operational efficiency and environmental performance. 3)Cases with deceleration starting at 5.0 meters do not significantly improve sediment control compared to the 3.0-meter point, suggesting diminishing returns for earlier deceleration. 4)The presence of a movable bed significantly alters flow patterns compared to fixed-bed simulations, emphasizing the importance of accounting for sediment feedback in modeling. [Conclusions] This study demonstrates that modifying the descent speed of a grab bucket is an effective way to reduce sediment resuspension during dredging operations. Key conclusions are as follows: 1)Environmental Impact Mitigation: Gradually reducing the grab’s descent speed before it reaches the sediment bed effectively decreases near-bed turbulence and sediment entrainment, thereby mitigating secondary pollution. 2)Recommended Strategy: Decelerating to one-third of the initial speed (0.33 m/s) starting at 3.0 m above the bed is the optimal descent profile among the cases studied, achieving substantial reduction in suspended sediment without compromising operational feasibility. 3)Modeling Advances: The integration of fluid, structural, and sediment dynamics through the FS3M model provides a powerful tool for analyzing complex interactions in dredging scenarios, capturing realistic behavior that conventional monitoring methods cannot resolve. 4)Future Work: Further studies should extend the modeling to include sediment excavation and lifting processes, and explore dynamic descent control strategies based on real-time sediment feedback.

Cite this article

LONG Rui , JIN Zhong-wu , Tomoaki NAKAMURA , Yonghwan CHO , Norimi MIZUTANI . Numerical Simulation of Grab Dredging on Flow Field and Sdiment Suspension Pattern in Construction Area[J]. Journal of Changjiang River Scientific Research Institute, 2025 , 42(7) : 18 -23 . DOI: 10.11988/ckyyb.20240233

开放科学(资源服务)标识码(OSID):

0 引言

淤积问题一直是河湖治理中的重难点,而疏浚是解决河湖淤积最直接有效的方式。疏浚过程在缓解河床抬高问题的同时,也会给河床带来极大的扰动,导致床底淤泥向水中释放常年累积的污染物质。目前,我国对河流、湖泊以及水库的污染整治力度正在逐年加大,促使以底泥释放产生的内源污染的治理成为河湖富营养化治理和生态修复的工作焦点[1-4]
疏浚作业时,底泥沉积物颗粒从河床底部释放到水体中,形成再悬浮颗粒,沉积物特征(粒径、重度、矿物特征、粘附力、有机质含量)、现场条件(水深、外露面积、水流和波浪、以及是否有障碍物)、操作方法(生产率、挖泥机切割的厚度、挖泥设备的种类、操作方法及操作人员的技能)等决定了再悬浮颗粒的物理特性[5-8]。在某些极端情况下,疏浚活动产生的再悬浮颗粒物可随水流扩散并再次沉降,继而引发严重的生态劣化,如底栖生物群落的彻底灭绝[9-10],或鱼类种群的显著减少[11-13]
抓斗疏浚因抓斗体积较小、挖掘深度较大、可探至硬土床底等特点,被广泛运用于各类疏浚工程。然而,目前针对抓斗疏浚过程中再悬浮颗粒运动规律的研究鲜有报道,龙瑞等[14]使用Nakamura等[15]开发的Three-dimensional fluid-structure-sediment-seabed interaction model(FS3M模型)对抓斗的下降过程进行了二维和三维数值模拟,分析了抓斗下降过程中流场的变化规律。但由于疏浚作业时挟带大量泥沙的水体会快速扰动,现有监测技术难以精准捕捉抓斗周围水沙运动的时空变化规律,致使抓斗作业产生的悬沙运动规律迄今尚缺乏系统研究。
本研究采用FS3M模型对疏浚作业时抓斗下行过程进行了二维数值模拟,讨论分析了抓斗下行过程的流速分布及悬沙运动规律,研究成果可为环保疏浚工艺提供参考。

1 计算模型

FS3M模型由大涡模拟(Large Eddy Simulation,LES)和4个模块组成。本研究使用了其中的VOF(Volume of Fluid)模块和STM(Sediment Transport Module)。VOF模块构建详见文献[14]。
STM的控制方程由沉积物质量守恒方程、床面沉积物输运率和悬浮沉积物输运方程组成。
泥沙的质量守恒方程为
z s t + 1 1 - m q x x + q y y + p N + q z b S = 0  
式中: z s为基准面以上的河床表面高度; q为单位宽度、单位时间的床面沉积物运移速率矢量 q x q y T;pN为沉积物上升相关函数; q z b S为底面沉降导致的 z向悬浮沉积物迁移通量。
床面沉积物运移速率矢量q的表达式为
q i = 1 6 π d 50 P E F v b i  
式中: v b为泥沙颗粒在床面运动中的平均迁移速度矢量; P E F为沉积物颗粒在床面表层的负荷运动,表达式为
P E F = 0   ,   τ * τ * c   ; 6 π μ d τ * - τ * c ,   τ * > τ * c  
式中:μd为泥沙颗粒的动摩擦系数; τ *为Shields参数, τ * = v f 2 / s - 1 g d 50; τ * c为临界Shields参数; v f表达式为
$\begin{array}{l} \frac{v_{\text {surf }}}{v_{f}}=2 \int_{0}^{z^{+}} 1 /\left\{1+\left\{1+4 \kappa^{\prime 2}\left(z^{+}+\Delta z^{+}\right)^{2} \cdot\right.\right. \\ \left.\left.\left[1-\exp \left(-\left(z^{+}+\Delta z^{+}\right) / A\right)\right]^{2}\right\}^{1 / 2}\right\} \mathrm{d} z^{+} \end{array}$
式中: κ '为Kármán系数;A为Van Driest衰减函数;vsurf为距离底部 z +距离的流速;Δz+的表达式为
Δ z + = 0.9 k s + - k s + e x p - k s + / 6   , 4.535 < k s + < 2   000  
式中: k s +为Reynolds数, k s +=ksvf/vw,ks为等效沙粒粗糙度。其他未作说明参量公式请参照文献[15]。

2 计算条件

本计算参考Kanazawa等[16]的研究模拟工况,以23 m3级的环保型抓斗为计算对象,外侧设置防污围栏。计算区域宽11 m,高21 m,沿水深方向由上至下依次为空气层(高5 m)、水体层(高13 m)、沉积沙层(厚度3 m),如图1所示,考虑到抓斗结构具有对称性,为节省计算量,此处只针对x≥0的部分进行数值模拟,抓斗底部距沉积沙层9 m处开始下行;沉积沙层相关参数:中值粒径0.1 mm,空隙率0.4,粒子的密度2.7×103 kg/m3,临界Shields数0.05,静止摩擦角32.2°,动摩擦角27.0°,水下休止角32.0°。为简化计算条件,防污围栏设置为静止且不透水的闭边界。
图1 计算范围

Fig.1 Computational domain

依据预设的抓斗下行方式组合计算条件如表1所示,其中,方案D0,抓斗以速度1.0 m/s的初始速度下行,至沉积沙层上方0.1 m处停止运动,该位置定义为抓斗触底,此设置旨在避免因抓斗下方空间太小流速过大导致计算结果发散。方案D1—D6为抓斗开始以速度1.0 m/s下行,至沉积沙层上方1.0、3.0、5.0 m处再以速度0.33、0.5 m/s(二次下行速度)下行至抓斗触底。
表1 计算条件

Table 1 Computational cases

方案 初始下降速度/
(m·s-1)
变速高
度/m
二次下降速度/
(m·s-1)
下降停止
高度/m
D0 1.0 0.1
D1 1.0 1.0 0.33 0.1
D2 1.0 1.0 0.50 0.1
D3 1.0 3.0 0.33 0.1
D4 1.0 3.0 0.50 0.1
D5 1.0 5.0 0.33 0.1
D6 1.0 5.0 0.50 0.1

3 计算结果

3.1 流场特性

图2为方案D0抓斗下行至沉积沙层上方2.9 m(t=6.1 s)、沉积沙层上方1.1 m(t=7.9 s)、抓斗触底(t=8.9 s)、抓斗触底后1 s(t=9.9 s)、抓斗触底后10 s(t=18.9 s)的流速分布,其中,绿色区域表示抓斗,棕色区域表示沉积沙层,浅蓝色线表示水面线(下同)。
图2 初始方案D0的流速分布

Fig.2 Flow velocity distribution of Case D0

图2可以看出,抓斗匀速下行拖曳水体运动,在抓斗设备上方和外侧近区抓斗拉动水体形成强度相对较大的逆时针回流,而在其下方水体受压后由抓斗与沉积沙层之间流出,抓斗触底(t=8.9 s)时水流流速与挟沙能力最大,此时挟沙水流向斜上方运动进入外侧回流区,回流区强度与尺度达到最大,随抓斗下方沙坑尺度增大,挟沙水流流速减小,水流挟沙能力减小,外侧回流强度减小。
为分析沉积沙层对水流特性的影响,针对方案D0无沉积沙层条件下抓斗下行计算区域的水流流场数值模拟,有无沉积沙层特征时刻抓斗附近流速分布如图3所示。由图3可知,当抓斗下行至接近底部时,抓斗设备下方水体由抓斗与沉积沙层之间流出。在抓斗触底前0.5 s(t=8.4 s),有沉积沙层情况的抓斗下方出流流速与无沉积沙层情况一致,此时抓斗下方沉积沙未启动;在抓斗触底时(t=8.9 s),有沉积沙层情况的出流水体挟沙,且出流流速与挟沙能力达到最大,抓斗下方沉积沙层形成倒驼峰凹陷,出流断面增大,出流流速较无沉积沙层情况小;在抓斗触底后0.5 s(t=9.4 s),有沉积沙层情况的抓斗下方倒驼峰凹陷尺度进一步扩大,抓斗下方出流流速减小,而无沉积沙层情况的抓斗下方出流断面未变化,故此时有沉积沙层情况的抓斗下方出流流速仍较无沉积沙层小。
图3 方案D0特征时刻抓斗附近流速分布(左为无沉积沙层,右为有沉积沙层)

Fig.3 Flow velocity distribution near grab bucket at characteristic time instant in Case D0(Left: No sand deposition zone,Right: Sand deposition zone)

3.2 悬沙分布特征

图4图5分别为方案D0、方案D5抓斗下行过程中特征时刻悬沙浓度c的分布。由图4可以看出,抓斗底部在沉积沙层上方1.1 m时(t=7.9 s),抓斗与沉积沙层之间水流开始挟沙,少许沉积沙起动上扬;至抓斗触底(t=8.9 s),水流挟沙能力达到最大,大量沉积沙向斜上方扬起,与外侧水体掺混,抓斗下方沉积沙层上形成倒驼峰凹陷;至抓斗触底后10 s(t=18.9 s),抓斗下方倒驼峰凹陷尺度达到最大,水流流速降至最低,水流丧失挟沙能力,受抓斗外侧逆时针回流区影响,进入水体的悬沙进一步向斜上方扩散;至抓斗触底后51.1 s(t=60 s),悬沙还在持续向上方水体扩散直至整个计算区域。方案D5较方案D0,抓斗至沉积沙层上方5 m时,抓斗下行速度由1 m减小为0.33 m/s。较方案D0,方案D5相应时刻水流流速、水流挟沙能力减小,抓斗下方倒驼峰凹陷尺度、沉积沙上扬悬沙扩散范围等亦减小,表明抓斗下行速度对沉积沙上扬及悬沙扩散特征影响较大。
图4 方案D0悬沙浓度c分布情况

Fig.4 Distribution of suspended sediment concentration c for Case D0

图5 方案D5悬沙浓度c分布情况

Fig.5 Distribution of suspended sediment concentration c for Case D5

图6图7为不同抓斗下行方式下悬沙量随时间的变化过程与沉积沙层形态。
图6 悬沙体积比较

Fig.6 Comparison of the suspended sediment volume

图7 沉积沙层断面形态

Fig.7 Cross-section morphology of depositional sand layers

计算区域内悬沙量在抓抓斗下行停止一段趋于稳定。在同一高度下对抓斗下行实施减速,下行速度减幅越大(速度值越小),悬沙量与沉积沙层倒驼峰凹陷尺度越小,如方案D1与D2(方案D3与D4、D5与D6),对抓斗实施减速高度均为1 m,抓斗下行速度依次减至0.33、0.5 m/s,方案D1悬沙量与沉积沙层倒驼峰凹陷尺度小于D2。不同高度下对抓斗下行实施减速,减速幅度一致,随减速高度的增大,悬沙量与沉积沙层倒驼峰凹陷尺度呈减小趋势,如方案D1与D3、D5(方案D2与D4、D6),对抓斗实施减速高度发依次为1、3、5 m,方案D3、D5较D1减速高度增大,悬沙量与沉积沙层倒驼峰凹陷尺度减小。由以上分析可知,方案D3、D5的悬沙量与沉积沙层倒驼峰凹陷尺度较小,可作为较优的抓斗下行方式。

4 结论

本文采用二维数学模型模拟了疏浚抓斗下行至触底抓斗行进区域水流流速分布与悬沙分布变化过程,分析了水流挟沙运动、悬沙分布规律特性。主要结论如下:
(1)疏浚抓斗下行拖曳水体,抓斗设备外侧水体被拉动形成逆时针回流区,下方水体受压由抓斗与沉积沙层流出进入外侧回流区。抓斗触底后,出流流速与外部回流区的强度尺度达到最大,随后出流流速与回流强度逐渐减小。
(2)疏浚抓斗下行至一定高度,抓斗下方出流挟沙至外侧回流区扩散开来,抓斗触底后一定时间,抓斗下方倒驼峰凹陷尺度达到最大,出流丧失挟沙能力,但进入外侧回流区的悬沙仍持续向上方扩散直至整个计算区域。
(3)不同抓斗下行方式下,抓斗在同一高度减速,速度减幅越大,水体悬沙量与沉积沙层倒驼峰凹陷尺度越小;抓斗不在一高度减速,抓斗减速起始高度越大,水体悬沙量与沉积沙层倒驼峰凹陷尺度越小。经分析比较,抓斗下行方案D3与D5可作为较优的抓斗下行方式。
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