Influences on determining structural reliability

Robert Hertle, Eric Brehm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The influences to investigate when trying to assess the reliability of structures are manifold. Even if all the relevant stochastic parameters and data for establishing a typical reliability model are known, there are uncertainties to be considered which cannot be covered by probabilistic methods only. In a probabilistic analysis, the basic variables of a design problem, such as e.g. material strength or load effects, have to be modelled as random variables. From there, the failure probability of a member can be determined by use of methods of reliability analysis. This relatively straightforward procedure reaches its limits when additional influences like the simplification and/or linearization of the design problem, the model-reality-antagonism, the paperbuilding site transformation or human error are to be considered. Especially the three latter are not tangible by stochastic methods only. As the nature of these issues is predominantly human, individual competence or its opposite deprive a purely mathematical approach to achieving sufficient reliability.

Original languageEnglish
Title of host publicationIABSE Conference, Vancouver 2017
Subtitle of host publicationEngineering the Future - Report
PublisherInternational Association for Bridge and Structural Engineering (IABSE)
Pages1328-1335
Number of pages8
ISBN (Electronic)9783857481536
StatePublished - 2017
Externally publishedYes
Event39th IABSE Symposium in Vancouver 2017: Engineering the Future - Vancouver, Canada
Duration: 21 Sep 201723 Sep 2017

Publication series

NameIABSE Conference, Vancouver 2017: Engineering the Future - Report
Volume109

Conference

Conference39th IABSE Symposium in Vancouver 2017: Engineering the Future
Country/TerritoryCanada
CityVancouver
Period21/09/1723/09/17

Keywords

  • Design checking
  • Design supervision
  • Human error
  • Model uncertainty
  • Reliability

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