Study on coupling evolution of collapse risk of deep underground tunnel from perspective of catastrophe

doi:10.16265/j.cnki.issn1003-3033.2023.05.1494

Abstract

Abstract:

In order to effectively prevent the collapse accidents in the construction of deep underground tunnels, firstly, based on the trajectory intersection theory, the risk factors of tunnel collapse were divided into two categories: people and objects, and the risk index system was analyzed and established. Then, the improved variable weight AHP was used to determine the comprehensive weight of each index, established the risk coupling mutation model, calculated the coupling degree, and analyzed the evolution path of tunnel collapse risk under the influence of human and physical risk factors. At the same time, the influence of random disturbance factors on tunnel collapse risk was considered, and the traditional cusp model was supplemented and improved. Finally, the effectiveness of the risk coupling catastrophe model was verified by an application example of the tailrace pipe maintenance gate chamber on the right bank of Baihetan hydropower station. The results show that the coupling degree of the collapse risk in the tail inspection room is 0.856 2, which is in the strength coupling range, and there is a strong coupling effect among the factors. In addition, when the value range of the random disturbance factor is (-1.287 8, -0.427 2), it will lead to the continuous breeding of potential risks out of control and outbreak, increasing the probability of collapse accidents.

Key words: catastrophe theory, collapse accidents in construction of deep underground tunnels, risk coupling, variable analytic hierarchy process(AHP), risk evolution

JIANG Xin, WANG Jingwen, WANG Yaowei, YANG Shangqu, YAO Chengming, JIN Lianghai. Study on coupling evolution of collapse risk of deep underground tunnel from perspective of catastrophe[J]. China Safety Science Journal, 2023, 33(5): 103-111.

Figures/Tables 10

Fig.1

Fig.2

Tab.1

Tab.2

Four types of common catastrophe models

突变类型	状态变量	控制变量	势函数	归一公式
折叠型	1	1	$V (x) = x 3 + p x$	$X p = p 12$
尖点型	1	2	$V (x) = x 4 + p x 2 + q x$	$X p, X q = q 13$
燕尾型	1	3	$V (x) = x 5 + p x 3 + q x 2 + r x$	$X p, X q, X r = r 14$
蝴蝶型	1	4	$V (x) = x 6 + p x 4 + q x 3 + r x 2 + s x$	$X p, X q, X r, X s = s 15$

Tab.2

Tab.3

Tab.4

Fig.3

Fig.4

Fig.5

Tab.5

Safety state area division of tunnel construction system

u和v的风险耦合度范围	范围	安全区域划分
u>0	Δ>0	稳定
u<0;v<- $- 827 u 3 12$ , v> $- 827 u 3 12$	Δ>0	稳定
u<0;v=± $- 827 u 3 12$	Δ=0	临界稳定
u<0;- $- 827 u 3 12$ <v< $- 827 u 3 12$	Δ<0	不稳定

Tab.5

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风险等级	风险描述	分值
Ⅰ	可忽略风险,不会出现系统失效,允许发生	[90,100]
Ⅱ	可接受风险,系统失效概率极低,允许在一定条件下发生	[70,90)
Ⅲ	一般风险,系统失效率比较低,不愿意发生	[50,70)
Ⅳ	较高风险,系统失效的可能性增大,不可接受	[30,50)
Ⅴ	高风险,系统失效的概率非常高,完全不能接受	[0,30)

y	10	20	30	40	50	55	60	65
z	0.898 8	0.927 1	0.944 5	0.951 2	0.957 2	0.967 3	0.971 6	0.975 7
y	70	75	80	85	90	95	98	100
z	0.982 9	0.986 2	0.989 2	0.992 1	0.994 9	0.997 5	0.999 0	1.000 0

底层指标	常权权重	变权权重	变权综合权重	权重变化值/%	得分值
D₂₄₁	0.179 5	0.417 5	0.134 3	-25.17	15.2
D₂₄₃	0.084 7	0.324 1	0.104 3	23.07	25.0
D₂₄₂	0.039 2	0.146 4	0.047 1	20.12	24.4
D₂₄₄	0.018 3	0.112 0	0.036 1	96.92	40.0
D₂₂₃	0.151 9	0.717 1	0.168 1	10.67	35.8
D₂₂₁	0.053 9	0.149 2	0.035 0	-35.08	21.0
D₂₂₂	0.028 6	0.133 7	0.031 3	9.43	35.4
D₂₃₂	0.089 5	0.551 7	0.092 6	3.50	43.0
D₂₃₁	0.047 0	0.249 6	0.041 9	-10.94	37.0
D₂₃₄	0.020 0	0.121 1	0.020 3	1.57	42.2
D₂₃₃	0.011 3	0.077 5	0.013 0	15.05	47.8
D₁₂₃	0.049 3	0.497 7	0.044 0	-10.79	35.6
D₁₂₄	0.023 3	0.250 8	0.022 2	-4.77	38.0
D₁₂₂	0.012 5	0.137 3	0.012 1	-3.27	38.6
D₁₂₁	0.008 4	0.114 3	0.010 1	20.79	48.2
D₂₁₁	0.050 3	0.827 8	0.055 5	10.37	64.4
D₂₁₂	0.016 8	0.172 2	0.011 6	-31.11	40.2
D₁₁₃	0.043 5	0.766 3	0.037 5	-13.79	35.0
D₁₁₁	0.032 6	0.767 9	0.033 3	2.38	75.2
D₁₁₆	0.014 1	0.574 3	0.012 6	-10.74	62.6
D₁₁₄	0.005 4	0.233 7	0.011 4	110.34	85.4
D₁₁₂	0.010 9	0.232 1	0.010 1	-7.15	68.2
D₁₁₇	0.006 2	0.332 3	0.007 3	17.49	82.4
D₁₁₅	0.001 6	0.093 4	0.002 0	26.62	88.8