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Fuzzy semi-quantitative approach for probability evaluation using Bow-Tie analysis

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  • معلومة اضافية
    • Contributors:
      Institut National de l'Environnement Industriel et des Risques (INERIS); Gestion et Conduite des Systèmes de Production (G-SCOP_GCSP); Laboratoire des sciences pour la conception, l'optimisation et la production (G-SCOP); Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ); CEPIN, Marko; BRIS, Radim
    • بيانات النشر:
      CCSD
      CRC Press
    • الموضوع:
      2017
    • Collection:
      Université Grenoble Alpes: HAL
    • الموضوع:
    • الموضوع:
      Portoroz, Slovenia
    • نبذة مختصرة :
      International audience ; The International Organization for Standardization (ISO) imposes the evaluation of the probability of accidents during risk analysis with the consideration of uncertainty. However, quantitative probability analysis can be too expensive and lead to unreliable estimation. This is due to imprecision and lack of data where unjustifiable assumptions should be added, while quantitative information is lost by using a qualitative probability analysis. This paper proposes a fuzzy semi-quantitative approach to address data uncertainties as an alternative for losing and adding information. A fuzzy-based approach is used for handling vagueness and imprecision in the input parameter frequencies. The application of this approach is demonstrated using the casestudy of a Loss of Containment Scenario (LOC) in a chemical facility.
    • الدخول الالكتروني :
      https://ineris.hal.science/ineris-01853453
      https://ineris.hal.science/ineris-01853453v1/document
      https://ineris.hal.science/ineris-01853453v1/file/2017-076%20post-print.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.1AD04648