The settling dynamics of flocculating mud-sand mixtures: Part 1—Empirical algorithm development
The settling dynamics of flocculating mud-sand mixtures: Part 1—Empirical algorithm development
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DOI：
10.1007/s10236-011-0394-7
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发表时间：
2011-03
期刊：
影响因子：
2.3
通讯作者：
A. Manning;J. Baugh;J. Spearman;Emma L. Pidduck;R. Whitehouse
中科院分区：
文献类型：
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作者：
A. Manning;J. Baugh;J. Spearman;Emma L. Pidduck;R. Whitehouse
欧洲的河口通常被认为要么主要是泥质的，要么主要是桑迪的。在一些河口，粘性和非粘性组分可能会分离。然而，最近的实验室测试显示，来自许多沿海地区的泥和沙可以表现出一定程度的絮凝作用。对于想要准确预测悬浮沉积物的运输路线和命运的河口管理团体来说，清楚地了解近岸区域沉积物的动态行为是特别重要的。为了实现这一目标，数值计算机模拟通常是选择的工具。为了使用这些模型的任何程度的信心，用户必须能够提供一个合理的空间和时间的质量沉降通量的数学描述模型。然而，大多数絮凝模型代表纯泥悬浮液。本文通过一系列的算法，综合各种数据，对不同粒径的混合泥沙悬浮体的沉降特性进行了评价。这些算法统称为混合泥沙沉降速度（MSSV）经验模型，可以估算混合悬浮物的质量沉降通量。MSSV完全基于实验观察所证明的沉降和质量分布模式，而不是纯物理理论。算法结构的选择是基于大絮凝体的概念-较大的聚集体结构-和较小的微絮凝体，代表大絮凝体的组成颗粒。絮凝体数据生成使用环形水槽模拟和絮凝体的性能测量使用基于视频的LabSFERAND仪器。推导出的算法是有效的悬浮泥沙浓度和湍流剪切应力值范围内的0.2-5 g l-1和0.06-0.9 Pa，分别。然而，MSSV算法主要是使用添马舰河口泥浆和细硅砂的人工混合物推导出来的，这意味着所提出的算法在性质上是针对特定地点的，在应用中并不完全通用。在质量沉降通量（MSF）的准确性方面：在较低的通量范围（195-777 mg m−2s−1），大多数MSSV的预测值都在观测值的百分之几以内，而对于观测到的最大的MSF（1.3-21 g m−2s−1），MSSV表现出与数据的密切拟合。即使对于观测到的最高MSF 33 g m−2s−1（由75 M：25 S混合悬浮液产生），MSSV也仅低估了18%的通量。MSSV算法表明了一种趋势，即砂含量的上升，以及随后的泥浆减少，有利于微絮凝物作为主要的通量贡献者。参数比较测试表明，通过将单一沉积物假设应用于混合沉积物环境，纯泥浆算法在每个浓度下的预测值低于25%，并且不能很好地处理桑迪泥浆沉积物。缓慢的恒定沉降速度（0.5和1 mm s−1）参数严重低于预测的MSF（有时仅为观测通量的13%），而最快的恒定沉降速率（5 mm s−1）参数则超出预测多达246%。固定的沉速参数会使MSF的估计产生较大的平均误差。浓度幂律和货车Leussen（1994）方法通常低于预测值25- 37%，平均误差和标准差极高。通过假设每种悬浮液都是纯沙子，在稀悬浮液中高估了超过400%的质量沉降通量，在5 g l−1的浓度下降低到约100%。一个会...
European estuaries tend to be regarded as being either predominantly muddy or sandy. In some estuaries, the cohesive and non-cohesive fractions can become segregated. However, recent laboratory tests have revealed that mud and sand from many coastal locations can exhibit some degree of flocculation. A clear understanding of the dynamic behaviour of sediments in the nearshore region is of particular importance for estuarine management groups who want to be able to accurately predict the transportation routes and fate of the suspended sediments. To achieve this goal, numerical computer simulations are usually the chosen tools. In order to use these models with any degree of confidence, the user must be able to provide the model with a reasonable mathematical description of spatial and temporal mass settling fluxes. However, the majority of flocculation models represent purely muddy suspensions. This paper assesses the settling characteristics of flocculating mixed-sediment suspensions through the synthesis of data, which was presented as a series of algorithms. Collectively, the algorithms were referred to as the mixed-sediment settling velocity (MSSV) empirical model and could estimate the mass settling flux of mixed suspensions. The MSSV was based entirely on the settling and mass distribution patterns demonstrated by experimental observations, as opposed to pure physical theory. The selection of the algorithm structure was based on the concept of macroflocs—the larger aggregate structures—and smaller microflocs, representing constituent particles of the macroflocs. The floc data was generated using annular flume simulations and the floc properties measured using the video-based LabSFLOC instrumentation. The derived algorithms are valid for suspended sediment concentrations and turbulent shear stress values ranging between 0.2–5 g l−1and 0.06–0.9 Pa, respectively. However, the MSSV algorithms were principally derived using manufactured mixtures of Tamar Estuary mud and a fine silica sand, which means that the algorithms presented are site-specific in nature, and not fully universal in application. In terms of mass settling flux (MSF) accuracy: at the lower flux range (195–777 mg m−2s−1) most MSSV predictions were within a few percent of the observations, whilst for the largest observed MSFs (1.3–21 g m−2s−1), the MSSV demonstrated a close fit with the data. Even for the highest observed MSF of 33 g m−2s−1(produced by a 75M:25S mixed suspension), the MSSV only under-estimated the flux by 18%. The MSSV algorithms indicated a trend whereby a rise in sand content, and a subsequent decrease in mud, favours the microflocs as the dominant flux contributor. Parameter comparison testing indicated that by applying a single-sediment assumption to a mixed-sediment environment, pure mud algorithms under-predicted at each concentration by as much as 25% and did not handle sandy mud sediments particularly well. Slow constant settling velocity (0.5 and 1 mm s−1) parameters severely under-predicted MSF (at times down to only 13% of the observed flux), whilst the fastest constant fall rate (5 mm s−1) parameter over-predicted by as much as 246%. Fixed settling velocity parameters produced quite large mean errors in MSF estimation. A concentration Power Law and van Leussen (1994) approaches generally under-predicted by 25–37%, with extremely high mean errors and standard deviations. By assuming every suspension scenario was pure sand, over-estimated the mass settling flux by over 400% at dilute suspensions, reducing to about 100% at a concentration of 5 g l−1. One would …