Seismic Fragility Characteristics of Structural Populations with Irregularities

Seismic Fragility Characteristics of Structural Populations with Irregularities

Junwon Seo

Department of Civil and Environmental Engineering, South Dakota State University, USA

Page: 
944-954
|
DOI: 
https://doi.org/10.2495/CMEM-V6-N5-944-954
Received: 
N/A
| |
Accepted: 
N/A
| | Citation

OPEN ACCESS

Abstract: 

Earthquakes result in substantial structural damage of a number of structures across a region. Many studies have made an effort to examine regional seismic damage and vulnerability to different structure types, e.g. buildings and bridges, using varying computational methodologies. This paper focuses on the use of Response Surface Metamodels (RSMs) in conjunction with Monte Carlo Simulations (MCSs) to quantify probabilistic seismic performance for different classes of structural populations with irregularities, including irregular steel buildings and steel girder bridges. As part of the regional vulnerability study, each of the selected classes is constructed based upon the appropriate experimental design technique, i.e. the Central Composite Design (CCD), and the responses of each class subjected to multiple ground motions are captured during the nonlinear time history analyses of an individual computational model. Then, a RSM for each class is established by performing a least-square regression analysis within the considered CCD space. Seismic fragility curves are generated by means of the joint RSM-MCS enabling to treat uncertainties regarding overall configuration irregularities and additional structural parameters considered significant for each class. The influence of the irregularity parameters on seismic vulnerability for each class is investigated by comparison of the resulting fragilities. Results reveal that the RSM-MCS is able to efficiently assess seismic vulnerability of each class and directly examine the parameters’ influence on corresponding behaviours.

Keywords: 

irregularities, metamodel, seismic response, structural populations, vulnerability

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