Investigation on Collapse Risk of Subsea Tunnel Based on Data Mining: A Collapse Risk Recognition Model

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.