Typical Portal Structure for Single Track High Speed Railway Tunnel in Rugged Mountainous Area with High and Abrupt Slope

2014 ◽  
Vol 716-717 ◽  
pp. 342-346
Author(s):  
Xiao Jun Zhou ◽  
Bo Jiang ◽  
Yue Feng Zhou ◽  
Yu Yu

On the basis of different landform and multifarious topography in rugged mountainous area in southwest China, typical tunnel portals for single track tunnels in a new high speed railway line have been presented in the paper. The portal comprises headwall, shed tunnel, bridge abutment and its support. Portal with headwall is suitable for tunnel to resist front earth pressure on high and abrupt slope. Shed tunnel is placed in front of headwall so as to prevent rockfall; its outward part is built into a flared one. Meanwhile, the installation of bridge and its abutment are also included in the portal according to landform in the paper.

2013 ◽  
Vol 353-356 ◽  
pp. 1759-1765
Author(s):  
Ying Xue Wang ◽  
Bo Gao ◽  
Yu Min Wen ◽  
Lun Gui Li

when high-speed train passing through tunnel, the micro-pressure wave noise will be created at tunnel exit, which worsening the living environmental condition along the railway line. Building hood at tunnel entrance is an effective method for solving this problem. In this paper, using numeral simulation method, the efficiency of single opening tunnel hood relieving micro-pressure wave noise was researched, the sensitive of hood opening parameter, such as opening ratio, ratio of length and width, was analyzed. In the end, the tunnel hood optimizing parameters was drawn out, which will play an important guiding role for high-speed railway tunnel hood design.


2020 ◽  
Vol 79 (5) ◽  
pp. 2201-2212
Author(s):  
Shunhua Zhou ◽  
Zhiyao Tian ◽  
Honggui Di ◽  
Peijun Guo ◽  
Longlong Fu

Author(s):  
Linggang Kong ◽  
Shuo Li ◽  
Xinlong Chen ◽  
Hongyan Qin

Vehicle on-board equipment is the most important train control equipment in high-speed railways. Due to the low efficiency and accuracy of manual detection, in this paper, we propose an intellectualized fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) network. Firstly, we collect the fault information sheets that are recorded by electrical personnel, using frequency weighting factor and principal component analysis (PCA) to realize the data extraction and dimension reduction; Then, in order to improve the fault diagnosis rate of the model, using genetic algorithm (GA) to optimize the parameters of the ANFIS network; Finally, using the fault data of a high-speed railway line in 2019 to test the model, the optimized ANFIS model can achieve 96% fault diagnosis rate for vehicle on-board equipments, which indicating the method is effective and accurate.


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