Hybrid modelling study for urban drainage systems simulation based on data-driven and mechanism-driven methods
This paper proposes a high-precision simulation method for urban drainage pipe net-work based on a hybrid mechanism-driven and data-driven approach.The method utilizes the one-dimensional Saint Venant equations and artificial neural networks to respectively depict the water transmission process in the drainage system and the errors in the mechanism equation simulation.To evaluate the model performance,a certain drainage sub-area of a city's drainage system is mod-elled as the simulation object.Hybrid-driven model testing is conducted through both actual real system monitoring and mathematical experiments,and compared with a pure mechanism-driven model.The results show that under actual rainfall,the accuracy of flow and water level simulation of the hybrid-driven model is 26.5％higher than that of the pure mechanism model;under mathe-matical experimental scenarios,the accuracy of flow and water level simulation is improved by 59.0％and 6.1％respectively,stability is improved by 54.5％and 2.6％,while the simulation time only increases by 1.1％.The proposed hybrid-driven simulation model has improved the accu-racy and stability of the simulation to a certain extent,which can better support the operation and management of urban drainage systems.
NETL
NSTL
万方数据
