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The prediction of fine sediment distribution in gravel-bed rivers using a combination of DEM and FNN

Rutschmann P. | Bui M.D. Faculty of Mechanical Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi, 100000, Viet Nam|

Water (Switzerland) Số 6, năm 2020 (Tập 12, trang -)

ISSN: 20734441

ISSN: 20734441

DOI: 10.3390/W12061515

Tài liệu thuộc danh mục: ISI, Scopus

Article

English

Từ khóa: Aquatic ecosystems; Feedforward neural networks; Finite difference method; Grain size and shape; Gravel; Rivers; Settling tanks; Affected factors; Coarse bed material; Conventional approach; Extracting information; Grain size distribution; Gravel-bed rivers; Porosity variations; Sediment exchanges; Sediments; artificial neural network; digital elevation model; discrete element method; fine grained sediment; grain size; gravel; infiltration; morphodynamics; porosity; void ratio
Tóm tắt tiếng anh
Large amounts of fine sediment infiltration into void spaces of coarse bed material have the ability to alter the morphodynamics of rivers and their aquatic ecosystems. Modelling the mechanisms of fine sediment infiltration in gravel-bed is therefore of high significance. We proposed a framework for calculating the sediment exchange in two layers. On the basis of the conventional approaches, we derived a two-layer fine sediment sorting, which considers the transportation of fine sediment in the form of infiltration into the void spaces of the gravel-bed. The relationship between the fine sediment exchange and the affected factors was obtained by using the discrete element method (DEM) in combination with feedforward neural networks (FNN). The DEM model was validated and applied for gravel-bed flumes with different sizes of fine sediments. Further, we developed algorithms for extracting information in terms of gravel-bed packing, grain size distribution, and porosity variation. On the basis of the DEM results with this extracted information, we developed an FNN model for fine sediment sorting. Analyzing the calculated results and comparing them with the available measurements showed that our framework can successfully simulate the exchange of fine sediment in gravel-bed rivers. � 2020 by the authors.

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