Premium
An optimum metamodel for safety control of operational subway tunnel during underpass shield tunneling
Author(s) -
Zhang Junru,
Huang Guang,
Gou Xinming
Publication year - 2018
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2195
Subject(s) - particle swarm optimization , engineering , support vector machine , quantum tunnelling , settlement (finance) , range (aeronautics) , computer science , artificial intelligence , algorithm , aerospace engineering , physics , world wide web , payment , optoelectronics
Summary The settlement is regarded as an important index in underground engineering. When tunneling under across the operational subway tunnel, settlement of the operational tunnel should be monitored. To control the tunneling‐induced movement of the operational subway tunnel, the operation parameters of mechanized‐tunneling, namely, face and grout pressures, should be kept in a specific range. A hybrid approach is proposed utilizing uniform design method, and radial basis function neural network to develop the relation of settlement and related influential factors. Such connection is used as a tuning module for tunneling boring machine (TBM). Furthermore, implementing total station robot and soft computing method of support vector machine (SVM), a forecast model for settlement of the rail is established. The prediction tool SVM is improved by using the particle swarm optimization. Parameters c and g from the SVM and γ in the kernel function of the SVM are optimized using the particle swarm optimization. An illustrative case in Changsha Metro Line 3 constructing under the Metro Line 1 tunnel validates the prediction model. The feasibility of the metamodel is demonstrated by means of the example.