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Downtime estimation of building structures using fuzzy logic

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Abstract Residential buildings are designed to withstand earthquake damage because it causes the buildings to be inhabitable for a period of time, called the downtime. This paper introduces a method… Click to show full abstract

Abstract Residential buildings are designed to withstand earthquake damage because it causes the buildings to be inhabitable for a period of time, called the downtime. This paper introduces a method to predict the downtime of buildings using a Fuzzy logic hierarchical scheme. Downtime is divided into three components: downtime due to the actual damage (DT1); downtime due to irrational delays (DT2); and downtime due to utilities disruption (DT3). DT1 is evaluated by relating the damageability of the building's components to pre-defined repair times. A rapid visual screening is proposed to acquire information about the analyzed building. This information is used through a hierarchical scheme to evaluate the building vulnerability, which is combined with a given earthquake intensity to obtain the building damageability. DT2 and DT3 are estimated using the REDiā„¢ Guidelines. DT2 considers irrational components through a specific sequence, which defines the order of components repair, while DT3 depends on the site seismic hazard and on the infrastructure vulnerability. The proposed method allows to estimate downtime combining the three components above, identifying three recovery states: re-occupancy; functional recovery; and full recovery. A case study illustrating the applicability of the methodology is provided in the paper. The downtime analysis is applied to buildings with low and medium damage levels. Results from the case study show that total repair time is higher in the medium damage case, as it is expected. In both evaluations, the downtime is influenced more by irrational components and it is different in the three recovery states.

Keywords: recovery; using fuzzy; damage; building; downtime; fuzzy logic

Journal Title: International Journal of Disaster Risk Reduction
Year Published: 2019

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