Risk Assessment of Tunnel Construction Based on Improved Cloud Model

Abstract

Objective and scientific risk assessment is of great significance for tunnel construction. The intrinsic link between risk level and influencing factors are poorly understood, and our ability to assess the risks of tunnel construction remains limited. In this study, we improved the normal cloud model to combine fuzziness and randomness into risk assessment to make the result more accurate. First, we constructed the risk index system for tunnel construction; second, we calculated the weight of the risk index by using the AHP method. Then we determined the improved cloud model eigenvalue through investigation and analysis and put the risk index data into a forward cloud generator to obtain the fuzzy comprehensive evaluation matrix. Following this, we combined weights with the matrix to receive the membership degree of different risk levels. Finally, the final risk level was obtained by analyzing the purposely designed membership radar chart. We applied this assessment model to evaluate the construction risk of the Tiger Mountain tunnel in section ZK3+280–ZK3+300. The study shows that the improved cloud model delivers a more scientific and reasonable risk assessment by using the fuzzy random theory, which introduces a new concept for risk assessment in tunnel construction.