Leakage Diffusion Modeling of Key Nodes of Gas Pipeline Network Based on Leakage Concentration

Author:

Li Hao-Peng1,Chen Liang-Chao12,Dou Zhan1ORCID,Min Yi-Meng1,Wang Qian-Lin1,Yang Jian-Feng1,Zhang Jian-Wen1

Affiliation:

1. Department of Safety Engineering, College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China

2. High-Tech Research Institute, Beijing University of Chemical Technology, Beijing 100029, China

Abstract

In order to achieve the prediction and early warning of city gas pipe network leakage accidents, as well as to provide rapid and precise support for emergency response to such accidents, this study focuses on a Gaussian diffusion model applied to a large urban gas pipeline network. Specifically, it investigates the gas gate wells, which are key nodes in the pipeline network, to develop a leakage model. The objective is to analyze the variation in internal gas concentration in the gate wells and determine the range of danger posed by external gas diffusion from the gate wells. In addition, Fluent simulation is utilized to compare the accuracy of the model’s calculations. The findings of this study indicate that the gas concentration inside the gate well, as predicted by the model fitting results and Fluent simulation, exhibit a high level of agreement, with coefficient of determination (R2) values exceeding 0.99. Moreover, when predicting the hazardous distance of gas leakage outside the gate well, the model’s results show an average relative error of 0.15 compared to the Fluent simulation results. This demonstrates that the model is highly accurate and meets the practical application requirements.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

National Key Research and Development Program of China

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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