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Flooding Fragility Model Development Using Bayesian Regression

In: The Monte Carlo Methods - Recent Advances, New Perspectives and Applications

Author

Listed:
  • Alison Wells
  • Chad L. Pope

Abstract

Traditional component pass/fail design analysis and testing protocol drives excessively conservative operating limits and setpoints as well as unnecessarily large margins of safety. Component performance testing coupled with failure probability model development can support selection of more flexible operating limits and setpoints as well as softening defense-in-depth elements. This chapter discuses the process of Bayesian regression fragility model development using Markov Chain Monte Carlo methods and model checking protocol using three types of Bayesian p-values. The chapter also discusses application of the model development and testing techniques through component flooding performance experiments associated with industrial steel doors being subjected to a rising water scenario. These component tests yield the necessary data for fragility model development while providing insight into development of testing protocol that will yield meaningful data for fragility model development. Finally, the chapter discusses development and selection of a fragility model for industrial steel door performance when subjected to a water-rising scenario.

Suggested Citation

  • Alison Wells & Chad L. Pope, 2022. "Flooding Fragility Model Development Using Bayesian Regression," Chapters, in: Abdo Abou Jaoude (ed.), The Monte Carlo Methods - Recent Advances, New Perspectives and Applications, IntechOpen.
  • Handle: RePEc:ito:pchaps:243406
    DOI: 10.5772/intechopen.99556
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    More about this item

    Keywords

    fragility model development; Bayesian regression; Markov Chain Monte Carlo; fragility model checking; Bayesian p-value;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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