EMPIRICAL VULNERABILITY ANALYSIS OF RAILWAY BRIDGE SEISMIC DAMAGE BASED ON 2022 MENYUAN EARTHQUAKE

被引:0
|
作者
He, Jing [1 ]
Huang, Yong [1 ]
机构
[1] China Earthquake Adm, Minist Emergency Management, Inst Engn Mech, Key Lab Earthquake Engn & Engn Vibrat,Key Lab Eart, Harbin 150080, Peoples R China
来源
CIVIL ENGINEERING JOURNAL-STAVEBNI OBZOR | 2023年 / 33卷 / 03期
关键词
Railway bridges; Empirical vulnerability; Seismic damage prediction; Ordinal logistic regression;
D O I
10.14311/CEJ.2023.03.0028
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A 6.9 magnitude earthquake at a depth of 10 km struck Menyuan County, Haibei Prefecture, Qinghai Province, China, on January 8, 2022. This earthquake damaged some railway bridges on the Lanzhou-Xinjiang Passenger Dedicated Line. This study combines relevant historical earthquake damage experience, considers the effects of earthquake intensity, site soil classification, superstructure type, foundation failure factor, number of spans, and total bridge length, and develops empirical formulas for seismic damage prediction of railway bridges using ordinal logistic regression model in SPSS software. Since the accuracy of both predictions for seismic damage is practically the same, using this regression to predict seismic damage to railway bridges is considered valid. The predicated seismic damage matrix, as were the anticipated multi-intensity mean damage index and the empirical vulnerability curve based on the two-parameter lognormal distribution function, were generated on this basis. We get a risk assessment of future seismic damage for regional bridges when they experience different intensities or peak ground acceleration. According to the conclusions, although the suggested particular equations and vulnerability curves do not apply to the remainder of the region owing to geographical uniqueness, the technical approach is valid. It may be used as a reference for seismic damage prediction and vulnerability evaluation in other regions. The earthquake damage prediction matrix derived from the regression analysis can provide reasonable and fast forecasts before the next earthquake.
引用
收藏
页码:370 / 382
页数:13
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