Principal component analysis for a seismic usability model of unreinforced masonry buildings. Issue 96 (May 2017)

• Record Type: Journal Article
• Authors: Zucconi, Maria; Sorrentino, Luigi; Ferlito, Rachele
• Is Part Of: Soil dynamics and earthquake engineering. Issue 96(2017)
• Page Start: 64
• Page End: 75
• Publication Date: 2017-05
• Subjects: MCS Mercalli-Cancani-Sieberg -- AeDES Agibilità e Danno nell'Emergenza Sismica (Usability and Damage during a Seismic Emergency) -- PCA Principal Component Analysis; Seismic vulnerability -- Vulnerability classes -- Rapid visual screening -- Building parameters -- Usability probability matrices; Soil dynamics -- Periodicals; Earthquake engineering -- Periodicals; Sols -- Dynamique -- Périodiques; Génie parasismique -- Périodiques; 624.176205
• DOI: 10.1016/j.soildyn.2017.02.014
• Languages: English
• ISSNs: 0267-7261

Abstract

Abstract: This paper develops a model to forecast unreinforced masonry buildings' usability, i.e. the condition of a building being habitable or occupiable after a seismic event. The model is based on scores given to seven building parameters that are usually easy to survey: building position within the structural aggregate, number of storeys above ground, construction timespan, structural class, presence of strengthening interventions, roof type, and pre-existing damage to structural elements. Usability coefficients are calibrated for each category of each parameter, by varying macroseismic intensity and regressing data from the 2009 L'Aquila earthquake in central Italy. The parameters contribute to the creation of a synthetic index, according to weights or loading computed through principal component analysis. Usability probability matrices are determined and they can be used for territorial scale scenario assessment, as shown with an application to an entire historical centre. Highlights: A model to forecast usability of unreinforced masonry buildings is developed. The model is based on scores given to seven building parameters. The model is calibrated on data from the 2009 L'Aquila earthquake. The parameters are weighted through principal component analysis. Usability probability matrices are derived and applied to a scenario analysis.