International Journal of Environmental Research and Public Health · 2019 · 13 citations · 21 references
Natural ResourcesCivil EngineeringWater Resources ManagementFlood HydrologyHydrologic ModelingWater Resources EngineeringFlood Inundation ModelingHydraulic ModelingRainfall-runoff ModelingDam DesignFlood ModelingPhysical Model TestingRain SplashingRainfall Intensity DistributionRainfall Intensity EffectsRainfall Intensity PredictionSplash
Flood discharge atomization is a serious challenge that threatens the daily lives of the residents around the dam area as well as the safety of the water conservancy project. This research aims to improve the prediction accuracy of the stochastic splash model. A physical model test with four types of flip bucket is conducted to obtain the hydraulic parameters of the impinging outer edge of the water jet, the relationship of the splashing droplet diameter with its corresponding velocity, and the spatial distribution of the downstream nappe wind. The factors mentioned above are introduced to formulate the empirical model. The rule obtained from the numerical analyses is compared with the results of the physical model test and the prototype observations, which yields a solid agreement. The numerical results indicate that the powerhouse is no longer in the heavy rain area when adopting the flip bucket whose curved surface is attached to the left wall. The rainfall intensity of the powerhouse is significantly weaker than that of other types under the designed condition, so we choose it as the recommended bucket type. Meanwhile, we compare the rainfall intensity distribution of the original bucket and the recommended bucket under different discharge which rates ranging from 150.71 to 1094.9 m³/s. It is found that the powerhouse and the owner camp are no longer in the heavy rain area under all of the working conditions. Finally, it is shown that the atomization influence during the flood discharge can be reduced by using the recommended bucket.
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Farnaz Fotovatikhah, Manuel Herrera, Shahaboddin Shamshirband et al. · Engineering Applications of Computational Fluid Mechanics · 2018 · 348 citations · Full text