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Risk Assessment of Tunnel Collapse Based on Multi-factor Selection and Grey Clustering Vector Projection Method
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Jian-ming ZHANGa, b, Ke-bin SHIa, b, Hong-ze SHANa, Ren-yi SHIa, Tao FUa, Zhi-peng LUa
Water Resources and Power | 2023, 41(5) : 121 - 125
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Water Resources and Power | 2023, 41(5): 121-125
WATER CONSERVANCY AND HYDROPOWER ENGINEERING
Risk Assessment of Tunnel Collapse Based on Multi-factor Selection and Grey Clustering Vector Projection Method
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Jian-ming ZHANGa, b, Ke-bin SHIa, b, Hong-ze SHANa, Ren-yi SHIa, Tao FUa, Zhi-peng LUa
Affiliations
  • a.College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
  • b.Xinjiang Key Laboratory of Water Conservancy Engineering Safety and Water Disaster Prevention, Xinjiang Agricultural University, Urumqi 830052, China
Published: 2023-05-25 doi: 10.20040/j.cnki.1000-7709.2023.20221465
Outline
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The risk assessment of collapse of tunnel involves many fuzzy factors and the evaluation method is complex, which makes the evaluation system constitute a gray system and the applicability of the evaluation method is not high. It is difficult to accurately assess the risk level of tunnel landslides. Using the basic idea of gray system and vector projection principle, a set of tunnel collapse risk evaluation model based on gray vector projection method is proposed. Based on the comprehensive analysis of the influencing factors of tunnel collapse under complex stratigraphic conditions, the group analytic hierarchy process (GAHP), which takes into account the degree of difference in the views of decision makers, is used to reduce the dimensionality of the pre-selected evaluation index system. Then, according to the comprehensive decision weight coefficient, 13 preferred evaluation indicators that can fully reflect the different, representative and highly differentiated evaluation indicators of the collapse mechanism are selected to establish a tunnel collapse risk optimal evaluation index system. In addition, grey group clustering (GGC) and anti-entropy weight (AEW) are introduced to determine subjective and objective single-level sorting weights, respectively. The improved combination weighting method of game theory (ICWGT) is used to obtain the optimal comprehensive weight distribution coefficient to determine the total ranking weight of the indicator. Finally, according to this model, the risk of collapse of five groups of tunnels was evaluated by the model. The results show that the risk assessment level of tunnel collapse is highly consistent with the actual excavation. The reliability and accuracy of the model are verified.

tunnel collapse  /  risk assessment  /  grey relational projection  /  metric selection  /  grey group clustering  /  improved game theory combination weighting method
Jian-ming ZHANG, Ke-bin SHI, Hong-ze SHAN, Ren-yi SHI, Tao FU, Zhi-peng LU. Risk Assessment of Tunnel Collapse Based on Multi-factor Selection and Grey Clustering Vector Projection Method[J]. Water Resources and Power, 2023 , 41 (5) : 121 -125 . DOI: 10.20040/j.cnki.1000-7709.2023.20221465
Year 2023 volume 41 Issue 5
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Article Info
doi: 10.20040/j.cnki.1000-7709.2023.20221465
  • Receive Date:2022-07-13
  • Online Date:2026-01-28
  • Published:2023-05-25
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History
  • Received:2022-07-13
  • Revised:2022-08-10
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Affiliations
    a.College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
    b.Xinjiang Key Laboratory of Water Conservancy Engineering Safety and Water Disaster Prevention, Xinjiang Agricultural University, Urumqi 830052, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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