Enhanced Bayesian Network approach to sea wave overtopping hazard quantification

S. Tolo, E. Patelli, M. Beer

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

3 Citations (Scopus)

Abstract

A novel, generally applicable and efficient framework for the quantification of the wave overtopping hazard is proposed. The approach adopted for the model implementation relies on the use of Bayesian Networks enhanced with System Reliability methods. The methodology ensures large flexibility in terms of representation of the uncertainties of the inputs (exact, probabilistic or intervals) as well as of the outputs. Moreover, the flexibility of the approach allows analysing several time scenarios from 2020 to 2100, taking into account different emission projections and their uncertainty. The overall aim of the study is to provide a simple and coherent framework which takes into account the expected sea level rise for the evaluation of future overtopping hazards for existing or planned sea defence structures. The model proposed is then applied to a simple case study, to highlight the advantages and drawbacks of the framework developed.

Original languageEnglish
Title of host publicationSafety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015
EditorsEnrico Zio, Luca Podofillini, Wolfgang Kröger, Bruno Sudret, Božidar Stojadinović
Pages1983-1990
Number of pages8
Publication statusPublished - 1 Jan 2015
Event25th European Safety and Reliability Conference, ESREL 2015 - Zurich, Swaziland
Duration: 7 Sep 201510 Sep 2015

Publication series

NameSafety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015

Conference

Conference25th European Safety and Reliability Conference, ESREL 2015
CountrySwaziland
CityZurich
Period7/09/1510/09/15

Keywords

  • floating breakwater
  • complex networks
  • hazards
  • reliability
  • uncertainty analysis
  • water waves
  • Bayesian networks

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