Bayesian structural reliability updating using a population track record

R. de Vries, R.D.J.M. Steenbergen and A.C.W.M. Vrouwenvelder

Reliability Engineering and System Safety, 2025, vol. 255, issue C

Abstract: In the assessment of existing structures, it is uncommon to consider a track record of the structural performance of the structure itself or similar structures. However, the structure's proven strength in service could play a significant role, along with the performance of similar structures in the population. Because the population track record does not apply in the design of new structures, it is not encountered in design standards. An assessment that does not incorporate the track record may conclude insufficient structural reliability whilst, in reality, the reliability is satisfactory. In the suggested approach, information obtained from laboratory experiments is combined with the track record in a Bayesian way to assess a structure's reliability. As a case study for this article, the reliability of the connection strength between wide slab floor elements is considered. Although laboratory tests indicate poor connection strength, the track record indicates just one failure and many well-performing floors. It is found that considering the time-dependent nature of structural reliability is vital for understanding how proven strength develops from the completion of the structure to its usage today. The number of similar objects in the population that show satisfactory performance is varied and is shown to have a significant effect when its number grows. The presented method and case study show that reliability assessments incorporating a track record enable more accurate structural reliability predictions for existing structures.

Keywords: Structural reliability; Existing structures; Bayesian updating; Track record; Proven strength (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:255:y:2025:i:c:s0951832024007154

DOI: 10.1016/j.ress.2024.110644

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