Modelling and simulation of smart city drainage system based on digital twin five-dimensional models

Y Yuanjing Zhao (State Key Laboratory of Flexible Electronics (LoFE), Institute of Advanced Materials (IAM), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), School of Materials Science and Engineering) M Min Yang

Abstract

The construction of smart cities has entered a new stage of industrial development in light of the industrial revolution. The aim is to create digital twin cities that integrate the dual systems of physical and digital bodies. The drainage system of a city forms the foundation and core of its digital twin, hence the need for a construction and simulation study proposed in this research. The study is based on the five-dimensional model of the digital twin. First, the research aims to develop a five-dimensional digital twin model that incorporates twin data and connections, building upon a three-dimensional model to improve its applicability. Second, the research looks to create a digital twin drainage system model using a lightweight framework, employing a dynamic scheduling algorithm and model-view-controller to facilitate intelligent scheduling of the drainage system and enable real-time data collection and transmission. The experimental outcomes indicate that in normal conditions, the overflow loss of the mathematical twin drainage system was 30m 3 /s, 34m 3 /s, and 25m 3 /s under the conventional fixed-priority scheduling algorithm and dynamic scheduling digital twin drainage system algorithm, respectively. Due to the ratio of the improved overflow loss to the pre improved overflow loss being called the improvement ratio, the improvement ratios generated by the mathematical twin drainage system in different situations were 48.67%, 48.1%, and 48.57%, respectively, which significantly enhanced the performance and durability of the urban drainage system. The model effectively transforms and enhances the current urban drainage system by increasing the efficiency of scheduling pumping station clusters. It also offers valuable reference for the implementation of digital twin concept and technology.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 21, Issue 7
Published July 09, 2026
Pages e0352787
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (2)

Y

Yuanjing Zhao

State Key Laboratory of Flexible Electronics (LoFE), Institute of Advanced Materials (IAM), Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM), School of Materials Science and Engineering

M

Min Yang