Infoscience

Conference paper

Proposed methodology for earthquake-induced loss assessment of instrumented steel frame buildings: building-specific and city-scale approaches

The performance-based earthquake engineering framework utilizes probabilistic seismic demand models to obtain accurate estimates of building engineering demand parameters. These parameters are utilized to estimate earthquake-induced losses in terms of probabilistic repair costs, life-safety impact, and loss of function due to damage to a wide variety of building structural and non-structural components and content. Although nonlinear response history analysis is a reliable tool to develop probabilistic seismic demand models, it typically requires a considerable time investment in developing detailed building numerical model representations. In that respect, the challenge of city-scale damage assessment still remains. This paper proposes a simplified methodology that rapidly assesses the story-based engineering demand parameters (e.g., peak story drift ratios, residual story drift ratios, peak absolute floor accelerations) along the height of a steel frame building in the aftermath of an earthquake. The proposed methodology can be employed at a city-scale in order to facilitate rapid earthquake-induced loss assessment of steel frame buildings in terms of structural damage and monetary losses within a region. Therefore, buildings within an urban area that are potentially damaged after an earthquake event or scenario can be easily identified without a detailed engineering inspection. To illustrate the methodology for rapid earthquake-induced loss assessment at the city-scale we employ data from instrumented steel frame buildings in urban California that experienced the 1994 Northridge earthquake. Maps that highlight the expected structural and nonstructural damage as well as the expected earthquake-induced monetary losses are developed. The maps are developed with the geographical information system for steel frame buildings located in Los Angeles.

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