Multi-Disciplinary Resilience Modeling for Developing Mitigation Policies in Seismic-prone Communities: Application to Salt Lake City, Utah
Citation:
Milad Roohi, Tu Nguyen, John van de Lindt, Martin Shields, Harvey Cutler, Hwayoung Jeon, Multi-Disciplinary Resilience Modeling for Developing Mitigation Policies in Seismic-prone Communities: Application to Salt Lake City, Utah, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, 2023.Download Item:

Abstract:
This paper presents a multi-disciplinary resilience modeling methodology to assess the vulnerability of the built environment and economic systems. This methodology can assist decision-makers with developing effective mitigation policies to improve the seismic resilience of communities. Two complementary modeling strategies are developed to examine the impacts of scenario earthquakes from engineering and economic perspectives. The engineering model is developed using a probabilistic fragility-based modeling approach and is analyzed using Monte Carlo simulations subject to seismic multi-hazard. The model accounts for shake and liquefaction and quantifies the physical damage to commercial and residential buildings at the land parcel level. The outcome of the analysis is subsequently used as input to a damage-to-functionality model to estimate the functionality of individual buildings. The economic model consists of a spatial computable general equilibrium (SCGE) model that aggregates commercial buildings into sectors for retail, manufacturing, services, etc., and aggregates residential buildings into a wide range of household groups. The SCGE model employs buildings' functionality estimates to estimate the economic losses. The outcomes of this integrated modeling consist of engineering and economic impact metrics that can be used to develop mitigation policies to help a community achieve its resilience goals. An illustrative case study of Salt Lake City, UT, is presented to demonstrate the proposed methodology.
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