Subway station construction using combined shield and shallow tunnelling method: Case study of Gaojiayuan station in Beijing

2018 ◽  
Vol 82 ◽  
pp. 627-635 ◽  
Author(s):  
Liqiang Cao ◽  
Qian Fang ◽  
Dingli Zhang ◽  
Tielin Chen
Keyword(s):  
Subway Station

scholarly journals Case study on the seismic response of a subway station combined with a flyover

2021 ◽  
Author(s):  
Qi Wang ◽  
Ping Geng ◽  
Xiangyu Guo ◽  
Xinqiang Wang ◽  
Peisong Li ◽  
...  
Keyword(s):  
Seismic Response ◽  
Subway Station

Integrated geophysical detection of water inrush from foundation pit near the river: a case study of Nanjing subway station

2021 ◽  
Vol 80 (20) ◽  
Author(s):  
Maoxin Su ◽  
Yimin Liu ◽  
Yiguo Xue ◽  
Lichao Nie ◽  
Peng Wang ◽  
...  
Keyword(s):  
Water Inrush ◽  
Subway Station ◽  
Foundation Pit

scholarly journals Development of a 3D Underground Cadastral System with Indoor Mapping for As-Built BIM: The Case Study of Gangnam Subway Station in Korea

Sensors ◽  
2015 ◽  
Vol 15 (12) ◽  
pp. 30870-30893 ◽  
Author(s):  
Sangmin Kim ◽  
Jeonghyun Kim ◽  
Jaehoon Jung ◽  
Joon Heo
Keyword(s):  
Subway Station ◽  
Cadastral System

scholarly journals A Queuing Network Based Optimization Model for Calculating Capacity of Subway Station

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Hanchuan Pan ◽  
Zhigang Liu
Keyword(s):  
Optimization Model ◽  
Subway Station ◽  
Queuing Model ◽  
Selection Probability ◽  
Evaluation Indexes ◽  
State Dependent ◽  
Decision Variables ◽  
Proposed Model ◽  
Shanghai Metro

Capacity of subway station is an important factor to ensure the safety and improve the transportation efficiency. In this paper, based on the M/G/C/C state-dependent queuing model, a probabilistic selection optimization model is proposed to assess the capacity of the station. The goal of the model is to maximize the output rate of the station, and the decision variables of the model are the selection results of the passengers. Finally, this paper takes a subway station of Shanghai Metro as a case study and calculates the optimal selection probability. The proposed model could be used to analyze the average waiting time, congestion probability, and other evaluation indexes; at the same time, it verifies the validity and practicability of the model.

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