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Title: Performance-based probabilistic framework for seismic risk, resilience, and sustainability assessment of reinforced concrete structures
Authors: Anwar, GA 
Dong, Y 
Zhai, C
Issue Date: May-2020
Source: Advances in structural engineering, May 2020, v. 23, no. 7, p. 1454-1472
Abstract: Recent earthquakes have highlighted additional losses due to the lack of resilience of damaged structures. Environmental impact, as performance indicator, has also received increased attention within performance-based earthquake engineering. In this article, a combined probabilistic framework is proposed to assess seismic risk, sustainability, and resilience of a non-ductile reinforced concrete frame structure. The framework utilizes three-dimensional inelastic fiber-based numerical modeling approach to develop limit states associated with performance levels. The decision variables (i.e. repair cost, downtime, and equivalent carbon emissions) are quantified at both component level and system level and are compared considering seismic risk, sustainability, and resilience. In addition, the proposed approach considers uncertainties in the building performance and consequence functions of structural and non-structural components. Fast-track and slow-track schemes are utilized as a repair strategy and probabilistic resilience is quantified given the investigated time period. The proposed approach can aid the development of the next generation of performance-based engineering incorporating both resilience and sustainability.
Keywords: Equivalent carbon emissions
Loss estimation
Performance-based engineering
Reinforced concrete buildings
Resilience
Sustainability
Publisher: SAGE Publications
Journal: Advances in structural engineering 
ISSN: 1369-4332
EISSN: 2048-4011
DOI: 10.1177/1369433219895363
Rights: This is the accepted version of the publication Anwar GA, Dong Y, Zhai C. Performance-based probabilistic framework for seismic risk, resilience, and sustainability assessment of reinforced concrete structures. Advances in Structural Engineering. 2020;23(7):1454-1472. Copyright © The Author(s) 2019. DOI: 10.1177/1369433219895363
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