A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Fragility Prediction for Earthquake-Induced Embankment Failures Through Empirical Methods
In this paper, a time-conserving fragility curve formulation methodology for extreme events is discussed. Uncertainty is a parameter that has a significant effect on the probabilistic estimations of infrastructure failures. Structural damages to civil infrastructure range from minor defects to collapse relative to serviceability or restoration measures. In this paper, earthquake-induced landslides are used as a sample case study, to study empirical methods of fragility curve formulation. Method of maximum likelihood and best-fit regression methods are applied to an extreme event, and fragility curves are derived. Monte Carlo stimulation is applied to analyse the behaviour of uncertainty parameter concerning standard sections of highway and railway embankments. Finally, the coefficient of determination was calculated to illustrate the correlation between developed curves and data points. The proposed method suggests an optimum method to quantify the failure probability from an available data sample or a real incident-based data sample, which is computationally very effective. Improvement in vulnerability estimations provides high maintenance and efficient restoration schemes for transportation networks which are prone to extreme events such as landslides.
Fragility Prediction for Earthquake-Induced Embankment Failures Through Empirical Methods
In this paper, a time-conserving fragility curve formulation methodology for extreme events is discussed. Uncertainty is a parameter that has a significant effect on the probabilistic estimations of infrastructure failures. Structural damages to civil infrastructure range from minor defects to collapse relative to serviceability or restoration measures. In this paper, earthquake-induced landslides are used as a sample case study, to study empirical methods of fragility curve formulation. Method of maximum likelihood and best-fit regression methods are applied to an extreme event, and fragility curves are derived. Monte Carlo stimulation is applied to analyse the behaviour of uncertainty parameter concerning standard sections of highway and railway embankments. Finally, the coefficient of determination was calculated to illustrate the correlation between developed curves and data points. The proposed method suggests an optimum method to quantify the failure probability from an available data sample or a real incident-based data sample, which is computationally very effective. Improvement in vulnerability estimations provides high maintenance and efficient restoration schemes for transportation networks which are prone to extreme events such as landslides.
Fragility Prediction for Earthquake-Induced Embankment Failures Through Empirical Methods
Lecture Notes in Civil Engineering
Dissanayake, Ranjith (editor) / Mendis, Priyan (editor) / Weerasekera, Kolita (editor) / De Silva, Sudhira (editor) / Fernando, Shiromal (editor) / Konthesingha, Chaminda (editor) / Gajanayake, Pradeep (editor) / Sathya, S. U. (author) / Mahmoodian, M. (author) / Bandara, C. S. (author)
International Conference on Sustainable Built Environment ; 2022 ; Yogyakarta, Indonesia
2023-08-10
17 pages
Article/Chapter (Book)
Electronic Resource
English
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