S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Energy Systems Engineering (에너지시스템공학부) Theses (Ph.D. / Sc.D._에너지시스템공학부)
Development of an assessment technique for subsidence risk in mining areas using strength reduction method
강도감소법을 이용한 광산지역 지반침하 위험지수 산정기법 개발
- 공과대학 에너지시스템공학부
- Issue Date
- 서울대학교 대학원
- Mining subsidence; Risk assessment; Numerical simulation; FLAC2D; Strength reduction method; Regression analysis
- 학위논문 (박사)-- 서울대학교 대학원 : 에너지시스템공학부, 2016. 8. 전석원.
- Mine development leads to inevitable environmental consequences resulting in so called ‘mine hazards’, which occur extensively over a long period of time across a large area. They can cause serious social and economic troubles both during operation and after closing of a mine. In particular, ground subsidence needs to be carefully managed because it is difficult to predict the location, scale, and time of its occurrence. Mine subsidence prediction methods have been developed by many researchers for the past several decades. Those methods usually focus on predicting the ground movement over mined cavities having well-defined geometry. However, more interests are taken in ‘risk assessment of mine subsidence’ and ‘potential locations of high risk of subsidence’ rather than the ground movement itself in most mine development and reclamation projects. This is because of that the need for monitoring and reclamation of ground subsidence is highly dependent on the surface utility and other circumstances. The overall assessment of mine subsidence risk is of great importance in most cases.
The aim of this study is to develop a risk assessment method of ground subsidence in mining areas considering the effect of mined cavities and rock mass conditions. The strength reduction technique which is often used in the slope stability analysis was employed to calculate the factor of safety on ground subsidence in mining areas. Then a relationship between the risk of subsidence and the factor of safety was obtained. FLAC2D was used to implement the strength reduction technique considering five variables, i.e. the depth, width, height, angle of cavity and rock mass condition, in the analysis. A numerical prediction model for subsidence was derived from regression analysis. In addition, new techniques were suggested to estimate the influence area of subsidence at the ground surface and to evaluate the interaction among multiple cavities. Finally, in order to validate the developed approach in this study, risk assessment analysis was performed on actual mine sites. Most subsidence traces surveyed in the mining sites well matched the subsidence risk contour map which was obtained in the prediction model analysis.