Toward a Vulnerability Model for Sichuan, China: Rc Index Buildings Definition and Capacity Curves
Year: 2025
Type: conference-paper
Abstract: Although probabilistic seismic risk assessment is now consolidated enough to escape academic boundaries and become \nwidely used in several practical applications, China has fallen behind the state-of-art in developing tools for its practical \nimplementation, particularly from the perspective of seismic vulnerability assessment. Research in other countries, for \ninstance in the US and in Southern European countries, can be adopted as a reference to advance models and tools for \nassessing seismic vulnerability in China. Specifically, using the Global Earthquake Model (GEM) Analytical Vulnerability \nframework, this study describes the first steps in deriving a robust procedure for obtaining fragility and vulnerability \nfunctions for structures in China. The first part of this paper looks at developing an inventory of typical building types in the \nSichuan Province by deriving data from the latest 2010 Chinese Census. This allows the definition of a set of 21 index \nbuildings to be used in the fragility assessment of low-rise and mid-rise reinforced concrete (RC) structures. The index \nbuildings of 2-storey, 5-storey and 8-storey are designed following the detailing characteristics representative of the Sichuan \nconstruction practice. Different versions of Chinese seismic design codes e.g., GBJ11-1989, GB50011-2001, GB50011- \n2010 are considered in the definition of the archetype buildings. Nonlinear static analysis is performed on detailed 3D \nmodels of the buildings to generate capacity curves. These curves constitute the first step in the ongoing development of a \ngeneric framework for constructing a state-of-the-art vulnerability model for China, properly accounting for structural and \nground motion uncertainties.
Authors: L. Zhou, C. Galasso And D. D'Ayala
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2743922709