Numerical analysis of synthetic granulate deposition in a physical model study

• Published in: International journal of sediment research Vol. 29; no. 1; pp. 110 - 117
• Main Authors: HARB, Gabriele, HAUN, Stefan, SCHNEIDER, Josef, OLSEN, Nils Reidar B.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2014; Institute of Hydraulic Engineering and Water Resources Management, Graz University of Technology, 8010 Graz,Austria%Department of Hydraulic and Environmental Engineering, The Norwegian University of Science and Technology,Trondheim, Norway%Institute of Hydraulic Engineering and Water Resources Management, Graz University of Technology,8010 Graz, Austria
• Subjects: Numerical modeling; Physical modeling; RANS-equations; Reservoir management; Sediment; 三维数值模型; 合成; 对流扩散方程; 数值分析; 数值模拟; 晶粒尺寸; 物理模型; 颗粒沉降; Numerical modeling; Reservoir management; Physical modeling; RANS-equations; Sediment
• ISSN: 1001-6279
• DOI: 10.1016/S1001-6279(14)60026-3

The current study focuses on the application of a three-dimensional numerical model for the prediction of morphological bed changes. The sediment deposition in a reservoir during a 10-year-flood was investigated and the results of the simulation were validated with data derived from a physical model study. Because of the small grain sizes in the prototype, synthetic granulate was used in the physical model. The numerical computation domain was a reproduction of the physical model, including the grain sizes and the density of the particles, in order to ensure comparability. The CFD code SSIIM, which solves the RANS-equations in three-dimensions, was used for the simulations. The sediment transport in SSIIM is divided into suspended sediment transport, computed by solving the convection-diffusion equation, and bed-load transport, calculated by an empirical formula. The results of the numerical simulation correspond well to the results of the physical model study. The simulated location and the pattern of the sediment deposition in the reservoir are an accurate representation of the observed distribution in the physical model.