Estimation of Tunnel Convergence Using Statistical Analysis

Measured convergence data of a tunnel were investigated by means of statistical and regression analysis, where the rock mass were mainly composed of andesite and granite. The rock mass around tunnel were classified by RMR method into five different ratings, and then convergence data which belong to individual ratings were statistically processed to find out the appropriate regression equations. Exponential equations were better coincided with measured data than logarithmic equations. As the number of rock mass rating was increased, the magnitude and standard deviation of convergence were increased. Final convergence data were also investigated to study the relevance with both maximum displacement rate and early measured convergence. Some brief results of their relevance are presented. For instance, the regression coefficient between final convergence and maximum displacement rate was turned out to be 0.87 for this studied tunnel.

통계처리를 활용한 터널 내공변위의 분석에 관한 연구

백악기 경상계 안산암과 불국사 화강암류가 주로 분포하는 지반에서 시공된 터널의 내공변위 계측자료를 분석하였다. 터널 주변 암반을 RMR법에 의한 다섯 가지 암반등급으로 구분하고 각 등급에 포함된 계측자료들을 통계처리하여 암반등급별 내공변위의 회귀분석을 실시하였다. 연구 결과. 로그함수보다는 지수함수의 상관계수 가 더 크며, 연약한 암반등급일수록 내공변위의 크기와 표준편차가 크게 나타났다. 또한, 최종내공변위에 대한 최대변위속도 및 초기내공변위의 관계를 도출하였으며, 이 중에서 최종내공변위와 최대변위속도의 상관계수는 0.87로 나타나 이들은 비교적 높은 상관성을 가지는 것으로 확인되었다