Statistical and vulnerability prediction model considering empirical seismic damage to masonry structures. (May 2022)

• Record Type: Journal Article
• Authors: Li, Si-Qi; Liu, Hong-Bo
• Is Part Of: Structures. Volume 39(2022)
• Page Start: 147
• Page End: 163
• Publication Date: 2022-05
• Subjects: Masonry structure -- Field reconnaissance observation -- Empirical prediction vulnerability model -- Statistical and time-varying vulnerability model -- Mean prediction damage index (MPDI); Structural engineering -- Periodicals; 624.1
• DOI: 10.1016/j.istruc.2022.03.024
• Languages: English
• ISSNs: 2352-0124

Abstract

Abstract: For a detailed analysis of the seismic vulnerability and failure features of masonry structures (MSs) under different intensity grades, the reconnaissance data of 136 typical catastrophic earthquakes that occurred in 18 territories of China from 1975 to 2013 were summarized and counted, empirical seismic damage inspection samples of 15, 870.9888 × 10 4 m 2 and 446, 430 MS buildings were drawn, and the typical macro damage characteristics and mechanism of this type of structure were analysed. By employing the methods of probability and mathematical statistics, nonlinear vulnerability prediction, and numerical model analysis, multidimensional MS vulnerability probability statistical matrix considering the latest version of the China Macroseismic Intensity Scale (CSIS-20) was constructed. The Gauss prediction model and mean fragility probability prediction curve were proposed. The vulnerability nonlinear prediction model (function, curve, and point cloud) considering the failure/damage ratio and transcendental probability parameters was calculated and derived. According to the statistics and time-varying vulnerability analysis of damage observation data in four periods (before 1989, 1990–1999, 2000–2009, and after 2010), the empirical time-varying vulnerability models of each year were developed. Combined with the mean prediction damage index ( MPDI ) matrix parameter model and the probability matrix of the different intensity regions, the MPDI vulnerability parameter matrix and curve model of MS in the observation region were established.