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Stochastic methods for safety assessment of the flood defense system in the Scheldt Estuary of the Netherlands

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  • Mohammadreza Rajabalinejad
  • Tewfik Mahdi
  • Pieter Gelder

Abstract

In this study, we address the effective method to apply a novel reliability method integrated with finite element models to the safety assessment of pilot site Scheldt in the Netherlands. This site was considered as one of the three main pilot sites in Europe to assess the application of newly suggested techniques in order to reduce and manage the flood risk in the Floodsite project. http://www.floodsite.net , 2004–2009 ). The novel method of dynamic bounds (DB) is applied to this site after a successful experience in (Rajabalinejad in Reliability methods for finite element models, 1 edn. IOS Press, Amsterdam, 2009 ). In this study, the bi-functional response of the finite element model is considered, and the dimensional uncertainty is defined presenting the expected uncertainty for a certain dimension in the DB method. The uncertainty is used as a judgment tool to choose the dimension for the DB method for the desired accuracy. The results obtained by applying this technique are presented in this paper. Copyright Springer Science+Business Media B.V. 2010

Suggested Citation

  • Mohammadreza Rajabalinejad & Tewfik Mahdi & Pieter Gelder, 2010. "Stochastic methods for safety assessment of the flood defense system in the Scheldt Estuary of the Netherlands," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 55(1), pages 123-144, October.
    • Handle: RePEc:spr:nathaz:v:55:y:2010:i:1:p:123-144
    DOI: 10.1007/s11069-010-9563-0
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    References listed on IDEAS

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    1. Rajabalinejad, M., 2010. "Bayesian Monte Carlo method," Reliability Engineering and System Safety, Elsevier, vol. 95(10), pages 1050-1060.
    2. Mohammadreza Rajabalinejad & Tew-Fik Mahdi, 2010. "The inclusive and simplified forms of Bayesian interpolation for general and monotonic models using Gaussian and Generalized Beta distributions with application to Monte Carlo simulations," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 55(1), pages 29-49, October.
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