Author(s): Xuefang Li; Shancong Xue; Shuyue Yu; Guilhem Dellinger; Vasileios Kitsikoudis; Pierre Archambeau; Michel Pirotton; Sebastien Erpicum; Benjamin Dewals
Linked Author(s): Benjamin J. Dewals, Sébastien Erpicum
Keywords: No Keywords
Abstract: Experimental data from laboratory scale models are a valuable complement to field data for validating computational models used for flood risk management. Laboratory studies of urban flooding often use geometrically distorted scale models (i. e., different horizontal and vertical scale factors) due to the multi-scale nature of these specific flows. The geometric distortion of an urban flooding model alters the flow aspect ratio, that is, the ratio of flow depth to channel width, significantly. The possible biases induced by this geometric distortion have not been investigated extensively for this type of flows. To address this gap, Li et al. (2021) combined experimental and numerical modeling to systematically assess the influence of the distortion ratio, that is, the ratio of horizontal to vertical scale factors, on upscaled flow depths and discharge partition between streets. When the distortion ratio increases up to a value of about 5, the upscaled flow depths at the model inlets decrease monotonously and the flow discharge in the branch that conveys the largest portion of the flow is greatly enhanced. For equal flow depths at the model outlets and depending on the configuration, the distortion effect induces a variation of the upstream flow depth approximately from ~4% to ~17% and a change in outlet discharge partition up to 24 percentage points. However, with increasing distortion ratio, the 3D characteristics of the flow in the model tend to be augmented, which may lead to a bias between the experimental and 2D numerical results. Therefore, this study extends the study of Li et al. (2021) by modelling a small synthetic urban district with a 3D numerical model, to further investigate the effect of model geometric distortion on 3D turbulent flow structures and flow energy losses in urban flooding. The outcomes indicate the direction and magnitude of the bias induced by geometric distortion for a broad range of flow cases, which is valuable for offsetting these effects in practical laboratory studies of urban flooding.
Year: 2024