Cloud model-based seismic risk assessment of road in earthquake region

被引：8

作者：

Jia, Xingli ^{[1
]}

Xu, Jinliang ^{[1
]}

机构：

[1] Key Laboratory for Special Area Highway Engineering of the Ministry of Education, Chang'an University, Xi'an

来源：

Tongji Daxue Xuebao/Journal of Tongji University | 2014年 / 42卷 / 09期

关键词：

Analytic hierarchy process; Cloud model; Earthquake; Principal component analysis; Risk assessment; Road engineering;

D O I：

10.3969/j.issn.0253-374x.2014.09.008

中图分类号：

学科分类号：

摘要：

The risk factors were discriminated according to its influence on seismic risk of highway based on the principal component analysis and expert surveys. Four factors such as the peak acceleration, vegetation coverage, formation lithology, slope, were selected as evaluation factors for their significant effect. Traditional analytic hierarchy process was improved by resorting to the cloud model, and a weight approach was proposed for seismic risk assessment based on cloud model-analytic hierarchy process. The scale scores of each risk factor was studied by using geographic information systems technology platform. The assessment model of seismic risk was set up, and the method was validated. The results indicate that the seismic risk index of the experiment area is 1.00∼6.96. Seismic risk value of most regional is less than 5.00, the maximum value in the south and the southeast of the starting point with high peak acceleration, hard rock and large slop is close to 7. Risk assessment results agree well with the measured data.

引用

页码：1352 / 1358and1458

共 15 条

[1] Jia X., Study on theory and method of highway alignment selection in high seismic intensity canyon region , (2013)
[2] Wemer S.D., Taylor E.C., Cho S.B., New developments in seismic risk analysis of highway systems, The 13th World Conference on Earthquake Engineering, pp. 2189-2194, (2004)
[3] Mualchin L., Seismic hazard analysis for critical infrastructures in California , Engineering Geology, 79, 3, (2005)
[4] Buekle G.G.I., Kim S.H., A vulnerability assessment modal for highway bridges, The 4th US Conference on Lifeline Earthquake Engineering, pp. 493-500, (1995)
[5] Lupoi A., Franchin P., Schotanus M., Seismic risk evaluation of RC bridge structure , Earthquake Engineering and Structural Dynamics, 32, 8, (2003)
[6] Crowley H., Bommer J., Modeling seismic hazard in earthquake loss models with spatially distributed exposure , Bulletin of Earthquake Engineering, 4, (2006)
[7] Feng Q., Yuan W., Method and application of seismic risk probability analysis for large-long span bridge based on IDA-MC, Journal of Chang'an University: Natural Science Edition, 30, 3, (2010)
[8] Qian B., Ye Z., Chen L., Et al., Summary of analysis method for seismic reliability of lifeline network system , Journal of Natural Disasters, 19, 1, (2010)
[9] Sun L., Yu Y., Gu W., Car ownership prediction method based on principal component analysis and hidden markov model , Journal of Traffic and Transportation Engineering, 13, 2, (2013)
[10] Malhi A., Gao R.X., PCA-based feature selection scheme for machine defect classification , Transactions on Instrumentation and Measurement, 53, 6, (2004)

← 1 2 →