Effect of Statistical Uncertainties in Ground Snow Load on Structural Reliability
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Bibliographic Details
| Author(s): |
Árpád Rózsás
(Budapest University of Technology and Economics, Budapest, Hungary)
Miroslav Sýkora 
(Czech Technical University in Prague, Prague, Czech Republic)
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| Medium: | conference paper | ||||
| Language(s): | English | ||||
| Conference: | IABSE Conference: Structural Engineering: Providing Solutions to Global Challenges, Geneva, Switzerland, September 2015 | ||||
| Published in: | IABSE Conference Geneva 2015 | ||||
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| Page(s): | 220-227 | ||||
| Total no. of pages: | 8 | ||||
| Year: | 2015 | ||||
| DOI: | 10.2749/222137815818357142 | ||||
| Abstract: |
This paper studies the effect of commonly neglected statistical uncertainties on structural reliability. The failure probability of a generic structural member, subjected to snow load is analysed using frequentist and Bayesian techniques to quantify parameter estimation and model selection uncertainties in ground snow load. Various variable to dead load ratios are considered to cover a wide range of real structures. The analysis reveals that statistical uncertainties may have a substantial effect on reliability. By accounting for parameter estimation uncertainty, the failure probability can increase by more than an order of magnitude. Bayesian posterior predictive distribution is recommended to incorporate parameter estimation uncertainty in reliability studies. |
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| Keywords: |
snow load Bayesian statistics structural reliability statistical uncertainty posterior predictive model averaging maximum likelihood
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