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A Cost-Benefit Methodology for Selecting Analytical Reinforced Concrete Corrosion Onset Models

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  • معلومة اضافية
    • Contributors:
      Institut de Recherche en Génie Civil et Mécanique (GeM); Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST); Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS); Laboratoire Matériaux et Durabilité des constructions (LMDC); Institut National des Sciences Appliquées - Toulouse (INSA Toulouse); Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3); Université de Toulouse (UT); ANR-11-VILD-0002,EvaDéOS,Evaluation non destructive pour la prédiction de la Dégradation des structures et l'Optimisation de leur Suivi(2011)
    • بيانات النشر:
      HAL CCSD
      Hindawi Publishing Corporation
    • الموضوع:
      2020
    • Collection:
      Université de Nantes: HAL-UNIV-NANTES
    • نبذة مختصرة :
      International audience ; This work focuses on predicting corrosion onset induced by concrete carbonation or chloride ingress when using analytical predictive models. The paper proposes a procedure that helps building and infrastructure managers to select an appropriate model depending on the available information and the means granted to auscultation campaigns. The approach proposed combines the costs of input parameters, their relative importance, the benefits brought through obtaining parameters, and the maintenance strategy of the manager. Costs represent the intellectual investment to obtain parameters. This encompasses the time spent to obtain and analyze a result and the required expertise. Relative importance and benefits are obtained from sensitivity analysis. The effect of the maintenance strategy is introduced through a scalar called efficiency of the model. The proposed methodology is illustrated with two case studies where it is supposed that more or less extended information is available. Three concrete qualities are also considered in the case studies. The results highlight that the available data and concrete type have significant impacts on the selection of the most appropriate model.
    • الرقم المعرف:
      10.1155/2020/3286721
    • الدخول الالكتروني :
      https://hal.science/hal-02913829
      https://hal.science/hal-02913829v1/document
      https://hal.science/hal-02913829v1/file/3286721.pdf
      https://doi.org/10.1155/2020/3286721
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.F54210DD