## Cumulative Failure Probability of Deteriorating Structures: Can It Drop?

- The reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic Engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability. Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. InThe reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic Engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability. Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. In this paper, we illustrate—with the help of a numerical example—that such a drop is possible because the cumulative probability before and after the updating is not based on the same information, hence not on the same probabilistic model.…

Autoren/innen: | Ronald SchneiderORCiD, D. Straub |
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Persönliche Herausgeber/innen: | J.C. Matos, P.B. Lourenço, D.V. Oliveira, J. Branco, D. Proske, R.A. Silva, H.S. Sousa |

Dokumenttyp: | Beitrag zu einem Tagungsband |

Veröffentlichungsform: | Verlagsliteratur |

Sprache: | Englisch |

Titel des übergeordneten Werkes (Englisch): | 18th International Probabilistic Workshop. IPW 2020. Lecture Notes in Civil Engineering |

Jahr der Erstveröffentlichung: | 2021 |

Organisationseinheit der BAM: | 7 Bauwerkssicherheit |

7 Bauwerkssicherheit / 7.2 Ingenieurbau | |

Verlag: | Springer |

Verlagsort: | Cham, Switzerland |

Jahrgang/Band: | 153 |

Erste Seite: | 253 |

Letzte Seite: | 264 |

DDC-Klassifikation: | Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurbau |

Freie Schlagwörter: | Bayesian updating; Deterioration; Inspection; Monitoring; Structural systems; Time-variant reliability |

Themenfelder/Aktivitätsfelder der BAM: | Infrastruktur |

Infrastruktur / Sicherheit und Lebensdauer von Bauwerken | |

Veranstaltung: | 18th International Probabilistic Workshop (IPW 2020) |

Veranstaltungsort: | Online meeting |

Beginndatum der Veranstaltung: | 12.05.2021 |

Enddatum der Veranstaltung: | 14.05.2021 |

DOI: | https://doi.org/10.1007/978-3-030-73616-3_18 |

Verfügbarkeit des Dokuments: | Datei im Netzwerk der BAM verfügbar ("Closed Access") |

Datum der Freischaltung: | 09.06.2021 |

Referierte Publikation: | Nein |