Abstract
To address the problems of high overflow rate of pipe network inspection well and low drainage efficiency, a rainwater control optimization design approach based on a self-organizing feature map neural network model (SOFM) was proposed in this paper. These problems are caused by low precision parameter design in various rainwater control measures such as the diameter of the rainwater pipe network and the green roof area ratio. This system is to be combined with the newly built rainwater pipe control optimization design project of China International Airport in Daxing District of Beijing, China. Through the optimization adjustment of the pipe network parameters such as the diameter of the rainwater pipe network, the slope of the pipeline, and the green infrastructure (GI) parameters such as the sinking green area and the green roof area, reasonable control of airport rainfall and the construction of sustainable drainage systems can be achieved. This research indicates that compared with the result of the drainage design under the initial value of the parameter, the green roof model and the conceptual model of the mesoscale sustainable drainage system, in the case of a hundred-year torrential rainstorm, the overflow rate of pipe network inspection wells has reduced by 36% to 67.5%, the efficiency of drainage has increased by 26.3% to 61.7%, which achieves the requirements for reasonable control of airport rainwater and building a sponge airport and a sustainable drainage system.
Highlights
As an important functional area of the city, this type of airport has the characteristics of a wide area, complex land and high flood control standards
Compared with the result of the drainage design under the initial value of the parameter, the green roof model and the conceptual model of the mesoscale sustainable drainage system, in the case of a hundred-year torrential rainstorm, the efficiency of drainage has increased by 26.3% to 61.7%, the root mean square error (RMSE) of overflow has decreased by 31% to 52.2%, the drainage efficiency of the pipe network has effectively improved, thereby achieving a better control of rainwater, effectively avoiding the occurrence of flood disasters
The conceptual model of the mesoscale sustainable drainage system is to decompose the catchment into multiple independent small catchments, and the airport is composed of six separate catchments [11]
Summary
As an important functional area of the city, this type of airport has the characteristics of a wide area, complex land and high flood control standards. J proposed a Monte Carlo simulation (MCS)-based probabilistic method and applied it to the western district of Tehran to improve the drainage capacity of urban drainage systems. This method is combined with the SWMM simulation model and the evolutionary search algorithm to find the best recovery measures in the blocking scenario [4]. J proposed an elastic-based repair method for improving urban drainage systems and applied it to the Rainwater Drainage System (TSDS) in western Tehran, which integrates a multi-objective evolutionary algorithm (MOEA) and an EPA-SWMM simulation model; this was done to find cost-effective recovery measures during structural failures of key elements in the network [7]. By decomposing the catchment into a group of independent small catchments, as the depth of rainfall increases, these small catchments begin to interconnect to achieve effective drainage [11]
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