A Study on Factors Influencing Ground Subsidence and a Risk Analysis Method Using the Attributes of Sewer Pipes

Author:

Lee Sungyeol1ORCID,Kang Jaemo1,Kim Jinyoung1

Affiliation:

1. Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Republic of Korea

Abstract

In recent years, we have witnessed an increase in road subsidence accidents in urban areas, threatening the safety of citizens. Various road facilities, such as water and sewage pipes, and telecommunication facilities are buried under roads, and the aging of these facilities is one of the factors causing road subsidence. In particular, old sewer pipes are a primary cause of road subsidence. However, most maintenance work on such facilities is carried out based on how long ago they were buried underground, without considering the risk of road subsidence caused by them. Therefore, this study aims to present a reliable method to assess road subsidence risk that considers various sewer pipe specifications and the environment surrounding them. To derive the factors influencing subsidence, sewer pipes near the target region, where road subsidence occurs the most, were extracted to analyze the correlation between road subsidence, pipe integrity, and the surrounding environment. An effective analysis method was selected by comparing logistic regression analysis and AHP (Analytic Hierarchy Process) analysis, and a weighted road subsidence risk assessment method was proposed by evaluating the importance of factors affecting ground subsidence. Its applicability was examined by comparing actual road subsidence data and analyzing risk in a pilot study area to validate the reliability of the proposed methodology. The results showed that it was possible to make reliable predictions of road subsidence risk areas.

Funder

Ministry of Science

ICT

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference28 articles.

1. Development of Machine Learning Model to predict the ground subsidence risk grade according to the Characteristics of underground facility;Lee;J. Korean Geo-Environ. Soc.,2022

2. Seoul Seokchon-dong Cavity Cause Investigation Committee (2014). Cause Analysis of Cavity at Seokchon Underground Roadway and Road Cavity, Seoul Seokchon-dong Cavity Cause Investigation Committee.

3. Subsidence occurrence and countermeasure by sewer;Kim;Water J.,2014

4. (2015). Sewer Pipeline Standard Inspection Manual, Ministry of Environment.

5. A Study on Simulation of Cavity and Relaxation Zone Using Finite Element Method;You;J. Korean Geosynth. Soc.,2017

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