A prioritization RVS methodology for the seismic risk assessment of RC school buildings. (December 2020)

• Record Type: Journal Article
• Authors: Ruggieri, Sergio; Perrone, Daniele; Leone, Marianovella; Uva, Giuseppina; Aiello, Maria Antonietta
• Is Part Of: International journal of disaster risk reduction. Volume 51(2020)
• Publication Date: 2020-12
• Subjects: Seismic vulnerability -- Rapid visual screening -- School buildings -- RC buildings; Emergency management -- Periodicals; Risk management -- Periodicals; Disaster relief -- Periodicals; Hazard mitigation -- Periodicals; 363.34
• DOI: 10.1016/j.ijdrr.2020.101807
• Languages: English
• ISSNs: 2212-4209

Abstract

Abstract: The seismic vulnerability assessment of critical facilities, such as hospital and school buildings, is of paramount importance to avoid the collapse in ordinary conditions and to guarantee their immediate functionality in the post-earthquake emergency. Due to the high number of school buildings, and to the need to perform the assessment in a short time, a simple methodology for ranking the more vulnerable buildings through a seismic risk index is highly desirable. In this study, a Rapid Visual Screening (RVS) methodology is proposed. The method aims to prioritize the buildings prone to higher seismic risk and to assist decision-makers in the implementation of seismic risk reduction strategies. The methodology allows to assess the seismic risk of reinforced concrete (RC) school buildings through the compilation of a factsheet. The main sources of structural and non-structural vulnerability are considered in the survey form. The influence of the hazard and exposure are also accounted for in the calculation of the safety index through simplified parameters. The proposed RVS method can be quickly applied to a large number of buildings to identify those that require more accurate analyses. The proposed methodology has been applied to a sample of typical school buildings in Apulian Region, Southern Italy. The results obtained using the proposed RVS method were compared with those of more advanced numerical analyses in order to assess its effectiveness.