인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
The construction of cross passages using the tunnel boring machine (TBM) method represents an emerging construction technique with numerous advantages. However, owing to the scarcity of application instances, the safety control methodologies and the regulatory patterns concerning environmental impacts remain inconclusive. In this study, a cross passage excavated using the TBM method-the first of its kind in the Tianjin area-was investigated. We identified the key risk control measures for the construction and analysed the TBM operating parameters, monitored ground and building settlements, and monitored mainline tunnel deformations and mechanical responses, revealing the ground and tunnel structure deformation patterns. The following conclusions are drawn. (1) The ground surrounding the cross-passage break-out opening was stabilised by performing secondary grouting and small-range freezing, and the break-in opening was excavated using a completely enclosed steel sleeve. These measures prevented water and sand inflows during the excavation of the break-out and break-in openings in the silt and silty sand strata. (2) The torsional moment of the cutter disc was large during the break-out phase. Break-out mainline tunnel displacement monitoring data indicated that the thrust had a significant effect on the mainline tunnel during the break-out phase. (3) The TBM tunnelling caused ground loss. The ground settlement exhibited a U-shaped distribution along the cross-passage axis, with the maximum settlement being 10 mm. (4) During the break-out phase, the deformation of the break-out mainline tunnel exhibited a duck-egg-shaped distribution. The clearance convergence of the break-out mainline tunnel was within ± 4, and the clearance convergence of the break-in mainline tunnel was controlled within ± 1 mm.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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