ABSTRACT
The concept of seismic resilience is fast developing in recent years, which plays the important role for a performance assessment especially with the infrastructures. The condition of bridges plays a key role with respect to the functionality of transportation networks, which must be good of seismic resilience to guarantee the efficient flow of people and services. In many studies, the performance-based techniques are adopted to predefined standards of performance during earthquakes, the resilience can be considered as a performance indicator that quantifies the residual functionality along with the effort of the society in responding to a seismic event.
A large number of earthquake damage show that near-fault pulse-like ground motions are different from far field ground motions. The former contain large velocity pulse, thus it can produce great destructive power to structures. The complexity responses of structures shocked by near-fault ground motions can be realized in other studies. To take into account the inherent uncertainties in the seismic hazard and response of the structures, the probabilistic approach should be adopted.
Nowadays, several probabilistic seismic analysis progress have been achieved in performance-based earthquake engineering framework, many of them focusing on seismic demand analysis and fragility assessment works, and some of them promoting the probabilistic treatment of resilience.
This paper focuses on the probabilistic seismic resilience estimate method for bridges possible shocked in extreme earthquakes. Probabilistic seismic demand and fragility analyses are two key elements of the seismic resilience assessment to be used. Based on the total probability theorem, the expected functionality of the bridge after an extreme event can be estimated.
The definition of seismic resilience is ‘the ability of social units (e.g., organizations and communities) to mitigate hazards, contain the effects of disasters when they occur, and carry out recovery activities in ways that minimize social disruption and mitigate the effects of future earthquakes’. However, resilience is a multifaceted concept, which covers too broadly social and technical aspects to be defined as a single analytical definition. Based on the total probability theorem, the expected functionality of the structure at each time instant t after an earthquake can be estimated. If a collection of events with a limited range of IMs is of interest, the following equation can be used to compute the expected functionality: () Q ¯ ( t ) = ∑ i n I M P ( I M = i ) ∑ j n D S P ( D S = j | I M = i ) Q j ( t ) https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781315207681/cd556cd4-4dcf-4efe-8e29-56fc67b8bfbd/content/eq144.tif"/>
With respect to the widely using of composite brides, a two-span steel-concrete composite bridge is taken as a case study, whose 3D finite element model is established by OpenSees software. 3-D finite element model of bridge. https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781315207681/cd556cd4-4dcf-4efe-8e29-56fc67b8bfbd/content/fig74_1.tif"/>
A subset ground motion records based on PEER strong ground motion database of 60 near-fault (NF) pulse-like and 60 far-field (FF) have been selected. The group of NF records are formed with closest site-to-source distances (R) less than 20 km and moment magnitudes (MW) greater than 6.0. The ratio of PGV and PGA is greater than 0.2 for making sure the ground motions including obvious velocity pulse. Through directly observing, the ground motions records in NF group should have double sides velocity pulse.
231On the opposite rules, the FF ground motion records are selected with matching the PGA and MW of the NF records. The selected NF ground motions records come from 5 strong earthquakes.
The total of 120 nonlinear analyses data provides the parameters of the conditional probability distribution of the D given IM. Through significance testing of regression coefficients, the logarithmic standard deviation and coefficients of determination R2 can be used to test the goodness of fit.
The functionality recovery functions from ATC-13 (ATC-13, 1985) have been adapted to compute resilience. These recovery profiles have been computed on the basis of experts surveys, and are presented in the form of the mean time required to reach 30%, 60%, and 100% of the normal functionality of the structure. A probabilistic seismic hazard analysis has been performed on the site of the location of the bridge based on the United States Geological Survey (USGS) hazard curves (USGS, 2015). The probabilities of occurrence of each investigated IM have been assessed from hazard curves assuming a life of 100 years for the bridge. Two profiles presented in the figures account for the different damage caused by near-fault and far-field earthquakes.
The resilience of bridge can be determined using equation (5), and the resilience indexes of bridge are shown in table 1. It can be found that the resilience of bridge shocked by far-field earthquakes with 0.98 is larger than near-fault earthquakes with 0.89. The expected resilience index of bridge.
Near-fault
Far-field
Expected resilience index
0.89
0.98
The results show that this type bridges are good of seismic resilience and the near-fault earthquakes have sigindicant effect on their performance. It can be easily seen that the damage caused by near-fault earthquakes is more difficult to be recovered.
