Two-Phase CFD Modeling of Sediment Plumes for Dredge Disposal in Stagnant Water
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Dredge spoil is commonly disposed in estuarine and coastal waters through submerged pipelines from a barge in the form of concentrated mixture of sediment and water. The discharge resembles a downward dense turbulent plume under the negative buoyancy of the sediment particles. Sediment discharge can increase the turbidity and suspended solid level of coastal water, causing damage the marine ecosystem. It is important to understand the mixing of a sediment plume with the ambient water in order to properly assess the environmental impact of disposal operation. This chapter presents a computational fluid dynamics (CFD) model of a sediment plume in a non-stratified stagnant ambient using the two-phase Eulerian approach. The axisymmetric two-phase continuity and momentum equations are solved with the drag force term accounting for the interaction between phases. The standard k-ε model is used for turbulence closure for sediment-water mixture. The radial turbulent dispersion of particles is modeled by a drift velocity term related to the concentration gradient of the particle phase. The model prediction is validated against experiments of a companion work and independent experimental data, with a wide range of particle sizes (68–1500 μm) and plume sediment volume fraction (maximum of 60%). The model predicted cross-sectional distribution of sediment concentration, plume fluid velocity and the slip velocity of particle to fluid can be well described by Gaussian profiles. The reduction of plume spreading rate with increasing particle size and settling velocity is also well predicted by the model. The CFD model results shed light on the development of a simple integral model for predicting the mixing of sediment plumes.
KeywordsSediment plumes CFD Eulerian two-phase model Volume fraction Sediment disposal
This research was supported by the National Research Foundation Singapore through the Singapore-MIT Alliance for Research and Technology’s Center for Environmental Sensing and Modeling interdisciplinary research program. The first author was partly supported by a research grant from the Institute for Advanced Study of the Hong Kong University of Science and Technology.
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