Open AccessInvestigation on Collapse Risk of Subsea Tunnel Based on Data Mining: A Collapse Risk Recognition Model
Author(s) -
Xin Li,
Yiguo Xue,
Huimin Gong,
Binghua Zhou,
Guangkun Li
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/440/5/052022
Subject(s) - subsea , excavation , geotechnical engineering , tunnel construction , rock mass classification , engineering , geology , forensic engineering
Due to the special geological conditions, the collapse of the subsea tunnel occurs frequently. To control the collapse risk of the subsea tunnel, this paper selected seven indicators including over-span ratio, buried depth, groundwater condition, rock mass integrity, rock mass grade, support method and construction level. The weight of the seven indicators is calculated by entropy method, among the results, the support method has the highest weight, and the construction level has the lowest weight. Finally, the evaluation model is established to evaluate the collapse risk of the subsea tunnel engineering in China, and the results obtained via the evaluation model are basically consistent with the excavation situation. The proposed evaluation model is demonstrated as an innovative method for the collapse risk evaluation of the subsea tunnel engineerings.