Fuzzy methods for prediction of seismic resilience of bridges

Communities are exposed to natural catastrophes, such as tsunamis, earthquakes, hurricanes, etc. Therefore, building and making resilient communities could lead to the reduction of the disastrous negative impacts and enable fast recovery. In this paper, novel seismic recovery functions and a metric for seismic resilience assessment have been proposed employing the concepts from fuzzy sets theory. The basic resilience parameters have been defined by fuzzy knowledge representation theory, the recovery process of bridges has been modeled in terms of fuzzy functions and the concepts from fuzzy measure theory have been used to determine resilience metrics. In addition, the presented model is integrated into a decision-making process for disaster preparedness of communities. Moreover, the model has been simulated in Java. A bridge in Santa Barbara has been investigated for this case study. The proposed method has revealed that fuzzy set theory has been a more efficient tool for estimating the relationship between bridge damage and functionality since the collected data has been established based on expert's judgments. The conclusion has been drawn that improving the disaster preparedness of communities would enhance the resilience of the bridge. The proposed model could be adapted for seismic resilience assessment of other infrastructure components such as tunnels, highway segments and in the case of bridges under multiple hazards.