Abstract
Water inrush is one of the most frequent and harmful geological disasters in tunnel construction. In order to effectively prevent and control the occurrence of water inrush, an early warning method based on fine risk evaluation and hierarchical advanced forecast is proposed. Water inrush is a complex dynamic coupling factors system, the relationship between influencing factors and water inrush is strongly nonlinear. Therefore, the efficacy coefficient model, which has the advantages of standardization, conciseness, and freedom from subjective factors, is improved nonlinearly. The fine risk evaluation theory and method based on the improved efficacy coefficient model consisted of two parts: one is static evaluation used in design stage, and the other is dynamic evaluation applied in the construction stage. The index weights are determined scientifically and reasonably by Analytical Hierarchy Process (AHP) and the entropy method. According to the fine risk evaluation results, combined with the advantages and disadvantages of various forecasting methods, a multistep hierarchical detection method of disaster resources for water inrush is proposed to identify the occurrence characteristics and failure level of disaster sources. The theory has been successfully applied to the #3 inclined well of Yuelongmen Tunnel in Cheng-Lan Railway. The evaluation results had good agreement with the actual excavation data, which indicates that the model is of high credibility and feasibility. The method could improve the prediction accuracy of water inrush and explore geometric characteristics and filling of disaster-causing structures. It is of great significance for avoiding water inrush and guiding the rapid and safe tunnel construction.
Highlights
According to the national strategy layout of “One Belt and One Road”, more and more tunnels will be built in the western mountain areas of China with developed karst, rich groundwater and surface water, and extremely complex geological conditions
In order to realize the accurate prediction of water inrush risk in karst tunnels, a new risk evaluation theory and method based on improved efficacy coefficient model was proposed
By comparing the results evaluated by the improved efficacy coefficient method with those of fuzzy mathematics, attribute mathematics, and extension theory, the results showed that good application effects had been achieved (Table 9)
Summary
According to the national strategy layout of “One Belt and One Road”, more and more tunnels will be built in the western mountain areas of China with developed karst, rich groundwater and surface water, and extremely complex geological conditions. A number of scholars have carried out research on water and mud inrush Their focus of early warning was mainly on risk evaluation and advanced prediction. Geosciences 2019, 9, 392 method of water inrush risk based on the attribute synthetic model in karst tunnels. Advanced geological prediction is a common method to realize the early warning of water inrush. In light of the above problems, an early warning method based on fine risk evaluation and hierarchical advanced forecast was established. The improved efficacy coefficient model was introduced into the fine risk evaluation of water inrush in a tunnel. According to the evaluation results and characteristics of various forecasting methods, the multi-step hierarchical advanced prediction method was established to realize fine exploration and decision-making for disaster-causing structures
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