Simplified Framework for Blast-Risk-Based Cost-Benefit Analysis for Reinforced Concrete-Block Buildings

JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES(2016)

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摘要
Probabilistic risk assessment (PRA) is essential for evaluating different options for blast risk management. However, depending on the risk management approach being considered, a rigorous blast PRA study can be quite demanding. To expedite this process, a simplified PRA framework is proposed for reinforced concrete-block shear wall buildings, in order to determine design basis threat (DBT) fragility curves based on revised damage limit states most suitable for risk assessment. The current definitions of damage states by North American standards for blast resistant design involve global response limitssuch as the support rotations of a structural elementthat are relatively simple to calculate. However, such damage state descriptors can be insufficient for the cost-benefit analysis required to evaluate different risk mitigation options. As such, building on recent advances in the area of performance-based seismic design of concrete-block shear wall buildings, this study proposes revised damage states that can be associated with more useful metrics, including repair technique and building downtime. To illustrate the proposed methodology, a hypothetical shear wall building is analyzed under different DBT levels. The DBT fragility curves are obtained through Monte Carlo sampling of the random variables describing the shear wall system and are used to identify the locations that are most suitable for the erection of barriers for blast protection. The proposed PRA framework can be used to identify target performance requirements, formulated in terms of stakeholders' tolerable probability of failure and consequent risk management, for different classes of buildings under a range of DBTs. (C) 2015 American Society of Civil Engineers.
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关键词
Blast performance,Concrete block,Damage state descriptor,Probabilistic risk assessment,Reinforced masonry,Shear wall,Site planning,Risk,Uncertainty
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