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Offshore system safety and reliability considering microbial influenced multiple failure modes and their interdependencies

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  • Adumene, Sidum
  • Khan, Faisal
  • Adedigba, Sunday
  • Zendehboudi, Sohrab

Abstract

The stochastic nature of microbial corrosion creates spatial interdependencies among random corrosion parameters and their failure modes. These interdependencies need to be captured for robust offshore system reliability prediction considering complex multispecies biofilms.

Suggested Citation

  • Adumene, Sidum & Khan, Faisal & Adedigba, Sunday & Zendehboudi, Sohrab, 2021. "Offshore system safety and reliability considering microbial influenced multiple failure modes and their interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021003811
    DOI: 10.1016/j.ress.2021.107862
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    References listed on IDEAS

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    1. Kammouh, Omar & Gardoni, Paolo & Cimellaro, Gian Paolo, 2020. "Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
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    4. Gong, Changqing & Frangopol, Dan M., 2020. "Time-variant hull girder reliability considering spatial dependence of corrosion growth, geometric and material properties," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
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    Cited by:

    1. Dao, Uyen & Sajid, Zaman & Khan, Faisal & Zhang, Yahui, 2023. "Dynamic Bayesian network model to study under-deposit corrosion," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    2. Nagode, Marko & Oman, Simon & Klemenc, Jernej & Panić, Branislav, 2023. "Gumbel mixture modelling for multiple failure data," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    3. Wu, Shengnan & Zhang, Qiao & Li, Bin & Zhang, Laibin & Zheng, Wenpei & Li, Zhong & Li, Zhandong & Liu, Yiliu, 2023. "Reliability analysis of subsea wellhead system subject to fatigue and degradation during service life," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    4. Lu, Cheng & Teng, Da & Chen, Jun-Yu & Fei, Cheng-Wei & Keshtegar, Behrooz, 2023. "Adaptive vectorial surrogate modeling framework for multi-objective reliability estimation," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    5. Zheng, Xiao-Wei & Li, Hong-Nan & Gardoni, Paolo, 2023. "Hybrid Bayesian-Copula-based risk assessment for tall buildings subject to wind loads considering various uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    6. Sidum Adumene & Rabiul Islam & Ibitoru Festus Dick & Esmaeil Zarei & Morrison Inegiyemiema & Ming Yang, 2022. "Influence-Based Consequence Assessment of Subsea Pipeline Failure under Stochastic Degradation," Energies, MDPI, vol. 15(20), pages 1-10, October.
    7. Mendoza, Jorge & Bismut, Elizabeth & Straub, Daniel & Köhler, Jochen, 2022. "Optimal life-cycle mitigation of fatigue failure risk for structural systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    8. Yazdi, Mohammad & Khan, Faisal & Abbassi, Rouzbeh & Quddus, Noor & Castaneda-Lopez, Homero, 2022. "A review of risk-based decision-making models for microbiologically influenced corrosion (MIC) in offshore pipelines," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    9. Liu, Zengkai & Ma, Qiang & Cai, Baoping & Shi, Xuewei & Zheng, Chao & Liu, Yonghong, 2022. "Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    10. Pol, Johannes C. & Kindermann, Paulina & van der Krogt, Mark G. & van Bergeijk, Vera M. & Remmerswaal, Guido & Kanning, Willem & Jonkman, Sebastiaan N. & Kok, Matthijs, 2023. "The effect of interactions between failure mechanisms on the reliability of flood defenses," Reliability Engineering and System Safety, Elsevier, vol. 231(C).

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