A new quantitative method for risk assessment of water inrush in karst tunnels based on variable weight function and improved cloud model

2020 ◽  
Vol 95 ◽  
pp. 103136 ◽  
Author(s):  
Chunjin Lin ◽  
Meng Zhang ◽  
Zongqing Zhou ◽  
Liping Li ◽  
Shaoshuai Shi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Weight Function ◽  
Quantitative Method ◽  
Cloud Model ◽  
Water Inrush ◽  
Variable Weight

scholarly journals A Normal Cloud Model-Based Method for Risk Assessment of Water Inrush and Its Application in a Super-Long Tunnel Constructed by a Tunnel Boring Machine in the Arid Area of Northwest China

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 644 ◽  
Author(s):  
Xin Wang ◽  
Kebin Shi ◽  
Quan Shi ◽  
Hanwei Dong ◽  
Ming Chen
Keyword(s):  
Risk Assessment ◽  
Cloud Model ◽  
Water Inrush ◽  
Ideal Point ◽  
Tunnel Boring Machine ◽  
Northwest China ◽  
Arid Area ◽  
Dynamic Monitoring ◽  
Tunnel Boring ◽  
The Impact

Tunnel water inrush is complex, fuzzy, and random, and it is affected by many factors, such as hydrology, geology, and construction. However, few papers have considered the impact of dynamic monitoring on water inrush in previous research. In this study, considering geological, hydrological, and construction factors, as well as dynamic monitoring, a new multi-index evaluation method is proposed to analyze the risk of tunnel water inrush based on the normal cloud model. A new weight algorithm combining analytic hierarchy process and entropy method is used to calculate the index weight. The certainty degree of each evaluation index belonging to the corresponding cloud can be obtained by the cloud model theory. The final level of tunnel water inrush is determined via the synthetic certainty degree. The proposed method is applied to analyze the risk of water inrush in the SS (Shuang-san) tunnel constructed by a tunnel boring machine in the arid area of Northwest China. The evaluation results are not only basically identical to the results calculated by the ideal point and gray relation projection methods, but also agree well with the actual excavation results. This demonstrates that this new risk assessment method of water inrush has high accuracy and feasibility. Simultaneously, it also provides a new research idea to analyze the probability of tunnel water inrush and can provide a reference for related projects.

Risk assessment of floor water inrush in coal mines based on MFIM-TOPSIS variable weight model

2021 ◽  
Vol 28 (8) ◽  
pp. 2360-2374
Author(s):  
Guan-da Zhang ◽  
Yi-guo Xue ◽  
Cheng-hao Bai ◽  
Mao-xin Su ◽  
Kai Zhang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Water Inrush ◽  
Coal Mines ◽  
Variable Weight ◽  
Floor Water Inrush ◽  
Weight Model

scholarly journals Risk Assessment of New Energy Vehicle Supply Chain Based on Variable Weight Theory and Cloud Model: A Case Study in China

2020 ◽  
Vol 12 (8) ◽  
pp. 3150
Author(s):  
Qingyou Yan ◽  
Meijuan Zhang ◽  
Wei Li ◽  
Guangyu Qin
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Cloud Model ◽  
Three Dimensions ◽  
Constant Weight ◽  
Variable Weight ◽  
New Energy ◽  
Intelligent Technology ◽  
New Energy Vehicle ◽  
New Energy Vehicles

In order to protect the environment and reduce energy consumption, new energy vehicles have begun to be vigorously promoted in various countries. In recent years, the rise of intelligent technology has had a great impact on the supply chain of new energy vehicles, which, coupled with the complexity of the supply chain itself, puts it at great risk. Therefore, it is quite indispensable to evaluate the risk of the new energy vehicle supply chain. This paper assesses the risks faced by China’s new energy vehicle supply chain in this period of technological transformation. First of all, this paper establishes an evaluation criteria system of 16 sub-criterion related to three dimensions: the market risk, operational risk, and the environmental risk. Then, variable weight theory is proposed to modify the constant weight obtained by the fuzzy analytic hierarchy process (FAHP). Finally, a risk assessment of China’s new energy vehicle supply chain is carried out by combining the variable weight and the cloud model. This method can effectively explain the randomness of matters, and avoid the influence of value abnormality on the criteria system. The results show that China’s new energy vehicle supply chain is at a high level. Through the identification of risk factors, mainly referring to the low clustering risk, technical level risk and information transparency risk, this paper can provide a risk prevention reference for corresponding enterprises.

scholarly journals Risk assessment of water inrush in tunnel through water-rich fault based on AHP-Cloud model

2020 ◽  
Vol 11 (1) ◽  
pp. 301-317 ◽  
Author(s):  
Yaxiong Peng ◽  
Li Wu ◽  
Qingjun Zuo ◽  
Chunhui Chen ◽  
Yong Hao
Keyword(s):  
Risk Assessment ◽  
Cloud Model ◽  
Water Inrush

Risk assessment of water inrush in karst tunnels excavation based on normal cloud model

2018 ◽  
Vol 78 (5) ◽  
pp. 3783-3798 ◽  
Author(s):  
Xintong Wang ◽  
Shucai Li ◽  
Zhenhao Xu ◽  
Jie Hu ◽  
Dongdong Pan ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Cloud Model ◽  
Water Inrush

scholarly journals Quantitative Risk Assessment for Deep Tunnel Failure Based on Normal Cloud Model: A Case Study at the ASHELE Copper Mine, China

2021 ◽  
Vol 11 (11) ◽  
pp. 5208
Author(s):  
Jianpo Liu ◽  
Hongxu Shi ◽  
Ren Wang ◽  
Yingtao Si ◽  
Dengcheng Wei ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Large Scale ◽  
Cloud Model ◽  
Quantitative Risk Assessment ◽  
Geological Condition ◽  
Deep Tunnel ◽  
Entropy Weight ◽  
Copper Mine ◽  
Evaluation Indexes ◽  
Metal Mines

The spatial and temporal distribution of tunnel failure is very complex due to geologic heterogeneity and variability in both mining processes and tunnel arrangement in deep metal mines. In this paper, the quantitative risk assessment for deep tunnel failure was performed using a normal cloud model at the Ashele copper mine, China. This was completed by considering the evaluation indexes of geological condition, mining process, and microseismic data. A weighted distribution of evaluation indexes was determined by implementation of an entropy weight method to reveal the primary parameters controlling tunnel failure. Additionally, the damage levels of the tunnel were quantitatively assigned by computing the degree of membership that different damage levels had, based on the expectation normalization method. The methods of maximum membership principle, comprehensive evaluation value, and fuzzy entropy were considered to determine the tunnel damage levels and risk of occurrence. The application of this method at the Ashele copper mine demonstrates that it meets the requirement of risk assessment for deep tunnel failure and can provide a basis for large-scale regional tunnel failure control in deep metal mines.

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