A multi-objective community-level sesimic retrofit optimization combining social vulnerability with an engineering framework for community resiliency
Date
2015
Authors
Jennings, Elaina N., author
van de Lindt, John W., advisor
Atadero, Rebecca, committee member
Mahmoud, Hussam, committee member
Peek, Lori, committee member
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Abstract
This dissertation presents a multi-objective optimization framework for community resiliency by providing decision maker(s) at the local, state, or other government level(s) with an optimal seismic retrofit plan for their community's woodframe building stock. A genetic algorithm was selected to perform the optimization due to its robustness in multi-objective problem solving. In the present framework, the algorithm provides a set of optimal community-level retrofit plans for the woodframe building inventory based on the socio-demographic characteristics of the focal community, Los Angeles, California. The woodframe building inventory was modeled using 37 archetypes designed to several historical and state-of-the-art seismic design provisions and methodologies. The performance of the archetypes was quantified in an extensive numerical study using nonlinear time history analysis. Experimental testing was conducted at full scale on a three-story soft-story woodframe building. The experimental testing investigated the seismic performance of several retrofit strategies for use in the framework, and the results were used in development of a metric correlating inter-story drift limits with damage states used in the framework. A performance-based retrofit design is presented in detail, and the experimental testing results of four retrofits are provided as well. The algorithm uses each archetype's seismic performance to identify the set of optimal community-level retrofit plans to enhance resiliency by minimizing four objectives: initial cost, economic loss, number of morbidities, and recovery time. In the model, initial cost sums the cost of each new retrofit, economic loss incorporates direct and indirect costs; the number of morbidities includes injuries, fatalities, and persons diagnosed with post-traumatic stress disorder (PTSD); and a recovery time is estimated and may be used to represent the loss in quality of life for the affected population. The framework was calibrated to the estimated losses from the 1994 Northridge earthquake. An application of the framework is presented using Los Angeles County as the community. Two forecasted populations are also examined using the census data for Daly City, California and East Los Angeles to further exemplify the framework. Analyses were conducted at six seismic intensities. In all illustrative examples, the total financial loss (e.g., initial cost + economic loss) was higher for the initial population (i.e. un-retrofitted community). When combining this financial savings with the reduced number of morbidities, it is clear that the higher initial cost associated with retrofitting the woodframe building stock greatly outweighs the risks and losses associated with not retrofitting. The results also demonstrated how retrofitting the existing woodframe building stock greatly reduces estimated losses, especially for very large earthquakes. The resulting losses were further investigated to demonstrate the important role that the mental health of the population plays in a community's economy and recovery following disastrous events such as earthquakes. Overall, the results clearly demonstrate the necessity in including social vulnerability when assessing or designing for community-level resiliency for a seismic hazard.
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Subject
earthquake engineering
social vulnerability
community resiliency
soft-story
retrofit