A Study on the Optimization Algorithm for Correlation Analysis of the Underground Utility Structure Density in Urban Areas and Recorded Ground Subsidence

Choi,  Changho, Kim,  Jin-Young, Baek,  Sung-Ha and Kang,  Jae Mo

doi:10.7843/kgs.2021.37.10.77

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2021 Vol.37, Issue 10 Preview Page

A Study on the Optimization Algorithm for Correlation Analysis of the Underground Utility Structure Density in Urban Areas and Recorded Ground Subsidence 도심지 지중매설물 밀집도와 이력지반함몰의 상관성 분석을 위한 최적화 알고리즘에 관한 연구

31 October 2021. pp. 77-87

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Abstract

도심지에서 발생하는 지반함몰의 위험도를 분석하고 예측 및 예방하기 위한 연구가 다양하게 진행되었다. 기존의 연구 중에 지하매설물의 밀도(즉, 대상 공간 주변 지중에 설치된 매설물의 공간적인 물량)와 지반함몰 발생의 상관성을 활용한 위험도 분석 연구는 미비하다. 본 논문에서는 GIS기반 공간정보 데이터를 활용하여 지하에 설치되어 있는 매설물의 선형밀도(line density)를 분석하고, 이를 이력지반함몰 발생 현황과 연계하는 연구를 수행하였다. 분석 대상 지역에 대하여 2010～2015년 사이에 발생한 29개 이력지반함몰과 6종 지하매설물 선형밀도의 상관관계를 극대화하기 위한 최적화 알고리즘을 개발하였고, 보편적인 분석을 위해 정규선형밀도의 개념을 제안하였다. 분석 대상 지역의 정규선형밀도를 5개 등급(1등급 최저, 5등급 최고)으로 구분하였으며, 최적화 알고리즘을 적용할 경우 이력지반함몰 위치에서 정규선형밀도가 4등급 이상인 경우가 약 80%이상으로 나타났다. 제안된 최적화 알고리즘을 활용하여 지하매설물의 밀집도 분석 결과를 지반함몰 위험도 분석에 적용할 수 있을 것으로 판단된다.

Several studies have been conducted to analyze, predict, and prevent the risk of ground subsidence occurring in urban areas. Nevertheless, there is insufficient research effort on risk analysis that utilizes the correlation between the density of underground structures (i.e., the spatial quantity of buried objects installed in the ground around the interested area) and the occurrence of ground subsidence. In this paper, a study was conducted to analyze the line density of underground structures using GIS-based spatial information data, and to link this with the recorded ground subsidences. An optimization algorithm was developed to maximize the correlation between the line density of 29 recorded ground subsidences and 6 types of underground structures that occurred between 2010 and 2015 for the analysis area. The concept of normalized line density was also proposed for the analysis. The normalized line density of the analysis area was divided into five grades (Grade 1: lowest, Grade 5: highest). When the optimization algorithm was applied, the case where the normalized line density was Grade 4 or higher at the location of the recorded ground subsidences was about > 80%. It is thought that the density analysis result of underground facilities can be applied to the ground subsidence risk analysis by using the proposed optimization algorithm.

Keywords

Ground subsidence

Optimization

Sinkhole

Underground structure

Utility pipeline density

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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 : 37
No :10
Pages :77-87
Received Date :2021. 09. 27
Accepted Date : 2021. 10. 07
DOI :https://doi.org/10.7843/kgs.2021.37.10.77

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

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