계층 분석적 의사결정과 암반 공학 시스템에 의한 저심도 암반터널에서의 암반거동 유형 정량화 방법론
Methodology to Quantify Rock Behavior in Shallow Rock Tunnels by Analytic Hierarchy Process and Rock Engineering Systems
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초록
저심도 터널 굴착시 예상되는 암반 거동을 정량적으로 파악하기 위해 계층 분석적 의사결정 방법과 암반 공학 시스템 방법을 적용하여 암반 거동 지수를 산정하였다. 복잡하고 조직화되지 않은 암반 거동을 효과적으로 결정하기 위해 쌍대 비교 매트릭스를 이용하는 계층 분석적 의사결정 방법과 상호 영향 매트릭스를 이용하는 암반 공학 시스템 방법을 적용하였고, 전문가 의견의 불확실성을 극복하고자 퍼지 델파이 방법을 적용하였다. 저심도 암반 터널 굴착 시 예상되는 암반 거동 유형으로 소성 변형, 낙반과 낙석을 제시하였다. 각각의 암반 거동 유형을 결정하기 위해 일축압축강도, 암질 지수와 절리 조건을 포함하는 암반 내생적 매개변수, 응력, 지하수와 지진 조건을 포함하는 암반 외생적 매개변수와 굴착 매개변수를 고려하였다. 이를 서울 지하철 ○호선 ○공구 설계에 적용하여 예상되는 암반 거동 유형을 정량적인 암반 거동 지수로 제시하였다.
Abstract
For the quantitative identification of rock behavior in shallow tunnels, we recommend using the rock behavior index (RBI) by the analytic hierarchy process (AHP) and the Rock Engineering Systems (RES). AHP and RES can aid engineers in effectively determining complex and un-structured rock behavior utilizing a structured pair-wise comparison matrix and an interaction matrix, respectively. Rock behavior types are categorized as rock fall, cave-in, and plastic deformation. Seven parameters influencing rock behavior for shallow depth rock tunnel are determined: uniaxial compressive strength, rock quality designation (RQD), joint surface condition, stress, ground water, earthquake, and tunnel span. They are classified into rock mass intrinsic, rock mass extrinsic, and design parameters. An advantage of this procedure is its ability to obtain each parameter’s weight. We applied the proposed method to the basic design of Seoul Metro Line ○ and quantified the rock behavior into RBI on rock fall, cave-in, and plastic deformation. The study results demonstrate that AHP and RES can give engineers quantitative information on rock behavior.
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