摘要
为解决淤泥地层城际铁路盾构隧道下穿既有结构引起其沉降过大问题,以珠机城际铁路盾构隧道下穿四孔箱涵为工程背景,采用参照规范、数值模拟和现场监测的方法,研究淤泥地层盾构隧道下穿箱涵引起的沉降。建立三维数值模型分析加固前箱涵结构及周围土体的沉降值,并以此为依据提出加固方案;对加固后的沉降,建立新的数值模型;将现场监测数据与加固后数值计算值进行对比分析。结果表明:箱涵最大沉降模拟值由加固前的-45 mm减小为加固后的-1. 5 mm,加固后现场监测值为-3. 1 mm;地表最大沉降模拟值由加固前的-51 mm减小为加固后的-7 mm,加固后现场监测值为-10. 1 mm;加固后数值模拟值与现场监测值二者的影响规律以及引起的沉降值基本一致,说明加固方案起到很好的加固效果以及所构建数值模型有合理可行性,可为今后类似工程提供借鉴。
To solve the problem of excessive settlement caused by shield tunnel of intercity railway underlying existing structure in silt stratum,in the background of shield tunnel underlying four-hole culvert on Zhuji Intercity Railway,the settlement caused by shield tunnel underlying four-hole culvert was analyzed after consulting related standards,carrying out numerical simulation and monitoring.A three-dimensional numerical model was built for analysis of the settlement value of the culvert structure and the surrounding soil before reinforcement.A strengthening scheme was designed and used.A new numerical model was built for analysis of the settlement after reinforcement.A comparison was made between the field monitoring data after reinforcement and the data obtained by using the new model.The results show that the maximum settlement value of culvert is reduced from-45 mm to-1.5 mm,the field monitoring value after reinforcement is-3.1 mm,and the maximum settlement value of surface is reduced from-51 mm to-7 mm,the field monitoring value after reinforcement is-10.1 mm,and that the reinforcement schemehas a good strengthening effect and the two numerical models have great effectiveness and it provides reference for future similar.
作者
朱垚锋
田书广
倪金鹏
范国相
ZHU Yaofeng;TIAN Shuguang;NI Jinpeng;FAN Guoxiang(China Railway 16th Bureau Group Co.,Ltd.,Beijing 100018,China;Beijing Metro Engineering Construction Co.,Ltd.,China Railway 16thBureau Group Co.,Ltd.,Beijing 101100,China)
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2018年第11期116-121,共6页
China Safety Science Journal
基金
国家自然科学基金资助(51504016)
关键词
盾构隧道
下穿
沉降分析
数值模拟
现场监测
加固方案
shield tunnel
passing through
settlement analysis
numerical simulation
monitoring
reinforcement scheme