A Study of Ground Subsidence Risk Grade Analysis Based on Correlation Between the Underground Utility Structure Density and Recorded Ground Subsidence

Changho Choi; Jin-Young Kim; Jae Mo Kang

doi:10.7843/kgs.2022.38.9.69

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2022 Vol.38, Issue 9 Preview Page

A Study of Ground Subsidence Risk Grade Analysis Based on Correlation Between the Underground Utility Structure Density and Recorded Ground Subsidence 지중매설물 밀집도와 이력지반함몰의 상관성 분석을 통한 위험도 등급 분석 기법에 관한 연구

30 September 2022. pp. 69-77

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Abstract

Several studies have been conducted to analyze the risk of ground subsidence occurring in urban areas. Recently, the correlation between the density of underground utilities (i.e., the quantity of buried utilities in the analysis area) and the recorded ground subsidence has been explored to analyze such risk through. Choi et al. (2021) proposed an algorithm to optimize the correlation between the ground subsidence and normalized linear density of underground pipelines. In this study, the optimization algorithm was modified for analysis based on the risk grade. The analysis results using the modified optimization algorithm were compared with the correlation analysis results between the density of underground utilities and recorded ground subsidence presented by Choi et al. (2021). Compared with Choi et al. (2021), three analysis results showed equal or higher accuracy in the correlation analysis with recorded ground subsidence according to risk grade. In particular, for R100, it was divided into five grades and compared with the ratio of the recorded ground subsidence that occurred in grades 4 or higher. As a result, Choi et al. (2021) showed that 86% of recorded ground subsidence occurred in grades 4 or higher, whereas this study showed 93%. It was confirmed that the accuracy of the modified optimization algorithm was improved. The modified optimization algorithm can be applied to develop a ground subsidence risk map for each grade in an urban area, which can be used as basic data for decision-making for underground utility maintenance.

Keywords

Ground subsidence

Optimization

Risk grade

Sinkhole

Utility pipeline density

도심지에서 발생하는 지반함몰의 위험도를 분석하기 위한 연구가 다양하게 진행되었다. 최근에는 지하매설물의 밀도(즉, 해석 공간의 지중에 설치되어있는 시설물의 물량)와 지반함몰 발생의 상관성을 통해 해당 지역의 위험도 등급을 분석하는 연구가 다수 진행되었다. Choi et al.(2021)은 지하매설물의 정규선형밀도 개념을 바탕으로 지반함몰과 정규선형밀도의 상관성을 최적화하기 위한 알고리즘을 제안하였다. 본 연구에서는 위험도 등급을 기준으로 분석할 수 있도록 최적화 알고리즘을 보완하였다. 보완된 알고리즘을 활용한 해석결과를 Choi et al.(2021)에서 제시한 지하매설물 설치 밀도와 이력지반함몰의 상관성 해석결과와 비교하였다. 3개의 해석결과는 Choi et al.(2021)과 비교하여 위험도 등급에 따른 이력지반함몰과의 상관성 분석에서 동등 이상의 정확도를 나타냈다. 특히, R100의 경우 5개 등급으로 구분하여 4등급 이상에서 발생한 이력지반함몰의 비율을 비교한 결과 Choi et al.(2021)는 86%, 본 연구는 93%의 이력지반함몰이 정규선형밀도 4등급 이상의 지역에서 발생하여 제안된 최적화 알고리즘의 정확도가 향상됨을 확인하였다. 본 연구를 통해 제안된 등급 기준 최적화 알고리즘은 도심지에서 지반함몰 위험도 지도를 제시된 등급별로 분석하고, 지하매설물 유지보수 투자를 위한 의사결정 기초자료로 활용될 수 있을 것으로 판단된다.

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Information

Publisher :The Korean Geotechnical Society
Publisher(Ko) :한국지반공학회
Journal Title :Journal of the Korean Geotechnical Society
Journal Title(Ko) :한국지반공학회 논문집
Volume : 38
No :9
Pages :69-77
Received Date : 2022-08-25
Revised Date : 2022-08-30
Accepted Date : 2022-08-30
DOI :https://doi.org/10.7843/kgs.2022.38.9.69

Journal of the Korean Geotechnical Society ISSN:1229-2427(Print) 2288-646X(Online) 한국지반공학회 논문집

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