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

Fuzzy analytic hierarchy process (fuzzy-AHP) synthetic evaluation models were applied to address the uncertainties in tunnel health evaluation. These uncertainties occur because of a lack of specific information, missing data, misleading or conflicting information due to the complex nature of geo-materials, and even the ambiguity in the concept of tunnel health. This fuzzy-AHP synthetic evaluation model merges 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 operators were defined to yield the fuzzy synthetic evaluation indexes (FSEIs) for monitoring factors and the fuzzy-AHP evaluation procedure applied to the models was demonstrated. In order to verify the feasibility and efficiency of the models and the procedure, a case study on Nanjing Yangtze River Tunnel was presented. The calculated FSEIs were compared with the rating scales to determine the corresponding action strategies. 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 segments with poor health conditions can then be identified for administrative maintenance or repair. The investigations presented indicate that the proposed fuzzy-AHP models characterize the fuzziness of tunnel health and will be useful for clarifying the tunnel health evaluation uncertainties to both designers and administrators. These evaluations will result in enhancing the knowledge of designers and aid them for the optimization of the design of similar tunnels.