摘要
岩质高陡边坡的稳定性问题是水电工程关注的重点。如何有效识别控制高陡边坡稳定的关键因素,并对此进行针对性的支护设计与施工,以确保边坡的稳定,一直是难以有效解决的问题。基于此,以长河坝水电站进水口高陡边坡为依托,对水电工程岩质高陡边坡的设计与施工进行深入探讨,结合前期勘察结果分析了控制边坡稳定的关键因素,即J3、J7裂隙与其他结构面组合所引起的破坏,并依据地理位置分区设计了相应的开挖支护方案;伴随边坡施工,分部位分高程进行了岩体结构复核,发现边坡主要的破坏模式为滑塌(移)破坏、倾倒拉裂破坏、多条裂隙切割导致的岩体松动破碎所引起的破坏。以岩体等级为基础进行了边坡重分区,并以此进行了支护设计修正。讨论了控制边坡稳定的最关键因素即顺坡向J3裂隙,对比了前后期设计的差异及作用。监测数据分析表明,信息化施工对边坡稳定控制有效,边坡没有出现工程问题,已处于稳定状态。以期为类似工程提供参考。
The stability of high and steep rocky slopes is crucial in hydropower projects.It is difficult to identify the key factors that affect the slope stability so that the specific support design and construction are implemented.By using the high and steep slope near the Changheba Hydropower Station water intake location as an example,combined with the geologic investigation,the key factors such as the combination damage of fissures J3,J7 and other structural planes of controlling the slope stability were analyzed,and the corresponding excavation support plan was proposed based on the geographical position partition.The rock mass was reviewed by different parts and different elevations during the construction,The main slope failure modes were slumping(sliding),dumping and tension,the loosing and broken rock mass cutting by different cracks.The slope was partitioned on the basis of the rock mass rating,which guided the supporting design of correction.The most key factor to control the slope stability was discussed,which was the J3 cracks.The differences and effectiveness were compared between the previous design and the corrective design.The analysis of the monitoring data suggested that the informationized construction had an obvious effect on controlling the slope stability,and no engineering problems were found from then on and the slope was stable at present.
出处
《工程科学与技术》
EI
CAS
CSCD
北大核心
2017年第4期10-17,共8页
Advanced Engineering Sciences
基金
国家重点基础研究发展规划资助项目(2010CB732005
2015CB057903)
国家重点研发计划资助项目(2016YFC0600702)
关键词
信息化施工
岩体复核
岩质边坡
长河坝水电站
监测分析
informationized construction
review of rock mass
rocky slope
the Changheba Hydropower Station
monitoring analysis