公开(公告)号：US20240135069A1

公开(公告)日：2024-04-25

申请号：US18172082

申请日：2023-02-21

申请人： Qingdao University of Technology

发明人： Yongjun ZHANG ,  Fei LIU ,  Huangshuai XIA ,  Bin GONG ,  Sijia LIU ,  Yingming WU ,  Qingsong WANG ,  Hongzhi LIU ,  Ruiquan LU ,  Mingdong YAN ,  Lijun ZHANG ,  Xiaoming GUAN ,  Pingan WANG ,  Shuguang LI ,  Dengfeng YANG ,  Weiguo ZHANG

IPC分类号： G06F30/23 ,  G01V99/00

CPC分类号： G06F30/23 ,  G01V99/005 ,  G06F2111/10

摘要： The present disclosure provides a risk assessment method of water inrush in tunnels constructed in water-rich grounds. The method includes the following steps: simulating a tunnel excavation process by finite element software MIDAS GTS NX and fluid-structure interaction; according to a research method of control variables, analyzing effects of a groundwater level, an elastic modulus and advanced pipe shed grouting on the stability of surrounding rock, and improving an algorithm of a radial basis function (RBF) neural network using a Grey Relation Analysis (GRA)-based Partitioning Around Medoid (PAM) clustering algorithm to assess risks of water inrush occurring in Qingdao area.