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Reduced Partial Factors for Assessment in UK Assessment Standards

 Reduced Partial Factors for Assessment in UK Assessment Standards
Auteur(s): , , ,
Présenté pendant IABSE Conference: Engineering the Past, to Meet the Needs of the Future, Copenhagen, Denmark, 25-27 June 2018, publié dans , pp. 312-319
DOI: 10.2749/copenhagen.2018.312
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Design standards are based upon a range of input variables for resistance, action and modelling. The distribution type and parameters for each determine the partial factors appropriate to achieve a ...
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Détails bibliographiques

Auteur(s): (Atkins, Epsom United Kingdom)
(Atkins, Epsom United Kingdom)
(Atkins, Epsom United Kingdom)
(Highways England, Guildford United Kingdom)
Médium: papier de conférence
Langue(s): anglais
Conférence: IABSE Conference: Engineering the Past, to Meet the Needs of the Future, Copenhagen, Denmark, 25-27 June 2018
Publié dans:
Page(s): 312-319 Nombre total de pages (du PDF): 8
Page(s): 312-319
Nombre total de pages (du PDF): 8
DOI: 10.2749/copenhagen.2018.312
Abstrait: Design standards are based upon a range of input variables for resistance, action and modelling. The distribution type and parameters for each determine the partial factors appropriate to achieve a defined reliability level over a specified reference period. For assessment a reduced reliability level may be accepted due to the greater cost of providing reliability through strengthening when compared to the cost of providing it at design. This would allow the use of lower partial factors, although they are still limited by the need to provide a minimum level for human safety. Adoption of this approach for assessment would have significant benefits for an ageing UK infrastructure by reducing the need to carry out costly strengthening and retrofitting schemes whilst still ensuring appropriate structural reliability levels are maintained. This paper presents a study investigating appropriate reduced partial factors to be applied through UK assessment standards, the sensitivity of these values to input distribution model assumptions, and how they could be implemented in industry.
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