下穿地表水塘浅埋隧洞综合超前预报与防控措施研究
Research on Comprehensive Advanced Forecasting and Prevention Measures for Shallow Buried Tunnels Underneath Surface Water Ponds
曹绍龙 1张楠 2孟松涧2
作者信息
- 1. 中国水利水电第七工程局有限公司,四川 成都 610213
- 2. 山东大学岩土与结构工程中心,山东 济南 250061
- 折叠
摘要
下穿地表水塘浅埋隧洞是一项复杂且高风险的工程,地质条件对施工安全和工程质量影响巨大.施工前深入了解地质情况,制定有效的安全防控措施至关重要.研究以磨盘山隧洞为依托,探讨了下穿地表水塘浅埋隧洞工程中的地质风险与安全防控措施.针对该难题,基于地质分析、地震波法、瞬变电磁预报方法和钻孔探测等方法,构建了下穿地表水塘浅埋隧洞的综合超前预报体系,并对下穿地表水塘隧洞区段的不良地质进行了探测与综合分析预警.结果表明:建立的下穿地表水塘浅埋隧洞的综合超前预报体系能够有效地判识隧道前方不良地质情况,得出的预警结果能够有效地指导现场施工,为现场安全防控措施的制定提供了依据,保障了磨盘山隧洞的高效安全掘进.
Abstract
The shallow buried tunnel through surface water ponds is a complex and high-risk project,and geological conditions have a huge impact on construction safety and engineering quality.It is crucial to thoroughly understand the geological conditions before construction and develop effective safety prevention and control measures.Based on the Mopanshan Tunnel,this study explores the geological risks and safety prevention and control measures in the shallow buried tunnel project that passes through surface water ponds.Based on geological analysis,seismic wave method,transient electromagnetic prediction method,and drilling detection,a comprehensive advance prediction system for shallow buried tunnels passing through surface water ponds was constructed to address this challenge.Adverse geology in the section of the tunnel passing through surface water ponds was detected and comprehensively analyzed for early warning.The results indicate that the comprehensive advance prediction system established for shallow buried tunnels passing through surface water ponds can effectively identify adverse geological conditions ahead of the tunnel,and the warning results obtained can effectively guide on-site construction.It provides a basis for the formulation of on-site safety prevention and control measures,ensuring the efficient and safe excavation of Mopanshan Tunnel.
关键词
地表水塘/引水隧洞/综合超前预报/安全防控Key words
surface water pond/water diversion tunnel/comprehensive advance forecasting/security prevention and control引用本文复制引用
基金项目
山东省自然科学基金项目(ZR2022QD014)
出版年
2024
国家科技期刊平台
NSTL
万方数据