摘要
以长春地铁2号线东延三道村东站为例,分别采用数值模拟法、动态曲线比拟法、频率分析法和BP神经网络法对车站未来百年可能出现的最高水位进行了预测。用4种方法对地下水位埋深预测结果分别为2.0 m、2.31 m、2.05 m和2.13 m。结合孔隙水压力监测结果显示,该站孔隙水压力不存在折减的情况,综合确定最终抗浮水位埋深2.0 m,抗浮水位标高257.2 m。
This paper takes Sandaocundong Station of East Extension Line of Changchun Metro Line 2 as an example,using such methods as numerical simulation method,dynamic curve analogy method,frequency analysis method and BP neural network method to predict the possible maximum water level in the next century.The prediction results of groundwater depth from four methods are 2.0m,2.31 m,2.05 m and 2.13 m respectively.The monitoring of pore water pressure shows that there is no reduction of pore water pressure in this station.The final buried depth of up-floating water level is 2.0 m and the up-floating water level is 257.2 m.
作者
王宇博
WANG Yubo(Beijing Urban Construction Exploration&Surveying Design Research Institute CO,Ltd.,Beijing 100101,China;Beijing Key Laboratory of Geotechnical Engineering for Deep Foundation Pit of Urban Rail Transit,Beijing 100101,China)
出处
《西北地质》
CAS
CSCD
北大核心
2020年第4期207-215,共9页
Northwestern Geology
基金
北京城建勘测设计研究院有限责任公司科研开发计划项目“长春地区浅层地下水特性与工程处理措施研究”(2019内研02)。
关键词
抗浮水位
GMS
BP神经网络
地下水位预测
up-floating water level
GMS
BP neural network
prediction of underground water level