Performance-based decision-making of buildings under seismic hazard considering long-term loss, sustainability, and resilience

Abstract

It is of vital importance to incorporate sustainability and resilience in the performance-based decision-making of civil infrastructure under seismic hazard. However, a performance-based engineering framework utilizing component-level approach, integrating seismic loss, sustainability, and resilience in a multi-criteria decision-making (MCDM) is not yet extensively developed particularly for retrofit selection in a long-term perspective. This paper introduces a framework utilizing performance-based approach to couple seismic loss, sustainability, and resilience in decision-making framework for selection of different retrofit alternatives. A component-based probabilistic approach is developed for the seismic loss, sustainability, and resilience assessment in a long-term perspective. The resulting social, economic, and environmental consequences are converted to expected annual consequences (EACs) by considering the full range of seismic hazards, and are utilized as a multi-criterion in the technique for order preference by similarity to ideal solution (TOPSIS). The proposed long-term performance-based multi-criteria decision-making (PB-MCDM) framework considers five consequences, which include cost, casualties, equivalent carbon emissions, embodied energy, and repair time. Based on the illustrative example, it may be concluded that incorporating seismic sustainability and resilience in PB-MCDM approach in a long-term perspective can provide ideal solutions and better decision-making against retrofit alternatives.

Keywords:

• Decision-making
• earthquakes
• long-term consequences
• performance-based
• reinforced concrete buildings
• resilience and sustainability
• retrofit
• risk

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study has been supported by the Chinese National Engineering Research Centre (CNERC) for Steel Construction (Hong Kong Branch) at the Hong Kong Polytechnic University (Project No. P0013864; Programme Code: BBV9), National Natural Science Foundation of China (grant no. 51808476), and the Research Grant Council of Hong Kong (PolyU 15219819). The first author acknowledges funding provided by the Research Grants Council (RGC) of Hong Kong under the Hong Kong PhD Fellowship Scheme (HKPFS) of 2018.