2008Structures Congress 2008Requires access

Which Ground Motion Intensity Measure Is Most Appropriate for Conditioning Demand Models for Bridge Portfolios?

Jamie E. Padgett, Bryant G. Nielson, Reginald DesRoches

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Abstract

Probabilistic seismic demand analyses are central to performance-based evaluation of structures and seismic risk assessments. The anticipated structural response and demand under earthquake loading is often characterized using a tool known as a probabilistic seismic demand model (PSDM). However, the degree of uncertainty in the model is dependent on the ground motion intensity measure (IM) used for conditioning the response (e.g. peak ground acceleration, spectral acceleration). Vulnerability assessments of general classes; or portfolios of structures, are becoming more essential because of their use in risk assessment packages such as HAZUS-MH, and hence the need for identification of optimal IMs increases. Appropriate intensity measures for general classes of bridges are evaluated as a part of this study, and the conditions under which various conclusions are valid. The influence of characteristics of the demand analysis on selecting an IM is assessed, such as the use of synthetic or recorded ground motions. The results are intended to offer guidance for appropriate intensity measure selection for probabilistic seismic demand models of bridge portfolios, which will considerably enhance future structural performance evaluations and regional risk assessments for transportation networks.

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Probabilistic seismic demand analyses are central to performance-based evaluation of structures and seismic risk assessments. The anticipated structural response and demand under earthquake loading is often characterized using a tool known as a probabilistic seismic demand model (PSDM). However, the degree of uncertainty in the model is dependent on the ground motion intensity measure (IM) used for conditioning the response (e.g. peak ground acceleration, spectral acceleration). Vulnerability assessments of general classes; or portfolios of structures, are becoming more essential because of their use in risk assessment packages such as HAZUS-MH, and hence the need for identification of optimal IMs increases. Appropriate intensity measures for general classes of bridges are evaluated as a part of this study, and the conditions under which various conclusions are valid. The influence of characteristics of the demand analysis on selecting an IM is assessed, such as the use of synthetic or recorded ground motions. The results are intended to offer guidance for appropriate intensity measure selection for probabilistic seismic demand models of bridge portfolios, which will considerably enhance future structural performance evaluations and regional risk assessments for transportation networks.

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Available abstract

Probabilistic seismic demand analyses are central to performance-based evaluation of structures and seismic risk assessments. The anticipated structural response and demand under earthquake loading is often characterized using a tool known as a probabilistic seismic demand model (PSDM). However, the degree of uncertainty in the model is dependent on the ground motion intensity measure (IM) used for conditioning the response (e.g. peak ground acceleration, spectral acceleration). Vulnerability assessments of general classes; or portfolios of structures, are becoming more essential because of their use in risk assessment packages such as HAZUS-MH, and hence the need for identification of optimal IMs increases. Appropriate intensity measures for general classes of bridges are evaluated as a part of this study, and the conditions under which various conclusions are valid. The influence of characteristics of the demand analysis on selecting an IM is assessed, such as the use of synthetic or recorded ground motions. The results are intended to offer guidance for appropriate intensity measure selection for probabilistic seismic demand models of bridge portfolios, which will considerably enhance future structural performance evaluations and regional risk assessments for transportation networks.

Key concepts: Spectral acceleration, Probabilistic logic, Measure (data warehouse), Computer science, Bridge (graph theory), Acceleration, Incremental Dynamic Analysis, Vulnerability (computing)

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