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Reliability-Based Optimal Inspection for Fracture-Critical Steel Bridge Members

Autor(en):


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Transportation Research Record: Journal of the Transportation Research Board, , n. 1, v. 1845
Seite(n): 39-47
DOI: 10.3141/1845-05
Abstrakt:

To prevent fatigue failure of members in steel bridges, one usually needs to perform frequent periodic bridge inspections and employ detailed inspection methods. This is especially true for fracture-critical members or details. Carrying out these inspections puts a large burden on a transportation agency’s bridge maintenance budget. A systematic reliabilitybased method for inspection scheduling is proposed to yield the most economical inspection strategy for steel bridges that, at the same time, guarantees an acceptable safety level through the planned service life. A methodology is presented for evaluating the fatigue reliability of a specified detail classified according to AASHTO fatigue categories. A Miner’s rule approach is used to evaluate the fatigue reliability. The inspection scheduling problem is modeled as an optimization problem with a welldefined objective function that includes the total expected cost of inspection, repair, and failure formulated on the basis of an event tree framework and appropriate constraints in inspection intervals and minimum (target) structural reliability. An optimal inspection-scheduling plan can thus be obtained for any specified fatigue details (fracture-critical details) in steel bridges. Examples presented demonstrate the advantage of the reliabilitybased optimal inspection scheduling in cost saving and structural reliability control over alternative periodic inspection plans. Two numerical examples for a steel bridge in Texas are presented to demonstrate the proposed reliability-based optimal inspection scheduling.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.3141/1845-05.
  • Über diese
    Datenseite
  • Reference-ID
    10778377
  • Veröffentlicht am:
    12.05.2024
  • Geändert am:
    12.05.2024
 
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