Fuzzy Analytic Hierarchy Process Synthetic Evaluation Models for the Health Monitoring of Shield Tunnels

Many uncertainties remain in tunnel health evaluation due to a lack of specific information, data scarcity, misleading or conflicting information due to the complex nature of geo-materials, and even the ambiguity in the concept of tunnel health. This article addresses the fuzzy analytic hierarchy process (AHP) synthetic evaluation models, which merge different types of data from multiple sensors to map them into the health rating scores of shield tunnels. A piecewise distribution was chosen for membership functions, and an exponential scale was introduced for a better characterization of the scales for weight sets. A series of fuzzy operation symbols, namely fuzzy operators, were defined to yield the fuzzy synthetic evaluation indexes (FSEIs) for monitoring factors. The fuzzy-AHP evaluation procedure applied to the models was demonstrated. Moreover, a case study on Nanjing Yangtze River Tunnel was presented to verify the feasibility and efficiency of the models and the procedure. The fuzzy-AHP health evaluations for monitoring factors, segments, rings, and the whole tunnel were implemented in succession using the models and following the procedure. The calculated FSEIs were compared with the rating scales to determine the corresponding action strategies. The segments with poor health conditions can then be identified for administrative maintenance or repairing measures. Such evaluation results will enhance the knowledge of designers and aid them for optimization when they are designing similar tunnels. The investigations indicate that the proposed fuzzy-AHP models characterize the fuzziness of tunnel health well and will be useful for clarifying the tunnel health evaluation uncertainties to both designers and administrators.