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Multi-defect modelling of bridge deterioration using truncated inspection records

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  • Calvert, Gareth
  • Neves, Luis
  • Andrews, John
  • Hamer, Matthew

Abstract

Bridge Management Systems (BMS) are decision support tools that have gained widespread use across the transportation infrastructure management industry. The Whole Life Cycle Cost (WLCC) modelling in a BMS is typically composed of two main components: a deterioration model and a decision model. An accurate deterioration model is fundamental to any quality decision output.

Suggested Citation

  • Calvert, Gareth & Neves, Luis & Andrews, John & Hamer, Matthew, 2020. "Multi-defect modelling of bridge deterioration using truncated inspection records," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:reensy:v:200:y:2020:i:c:s0951832019306015
    DOI: 10.1016/j.ress.2020.106962
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    References listed on IDEAS

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    1. Nicolai, Robin P. & Dekker, Rommert & van Noortwijk, Jan M., 2007. "A comparison of models for measurable deterioration: An application to coatings on steel structures," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1635-1650.
    2. Orcesi, André D. & Cremona, Christian F., 2010. "A bridge network maintenance framework for Pareto optimization of stakeholders/users costs," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1230-1243.
    3. Berrade, M.D. & Scarf, P.A. & Cavalcante, C.A.V. & Dwight, R.A., 2013. "Imperfect inspection and replacement of a system with a defective state: A cost and reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 80-87.
    4. Brian Heath & Raymond Hill & Frank Ciarallo, 2009. "A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-9.
    5. Ceravolo, R. & Pescatore, M. & De Stefano, A., 2009. "Symptom-based reliability and generalized repairing cost in monitored bridges," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1331-1339.
    6. Yang, Seung-Ie & Frangopol, Dan M. & Kawakami, Yoriko & Neves, Luís C., 2006. "The use of lifetime functions in the optimization of interventions on existing bridges considering maintenance and failure costs," Reliability Engineering and System Safety, Elsevier, vol. 91(6), pages 698-705.
    7. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
    8. Bocchini, Paolo & Frangopol, Dan M., 2011. "A probabilistic computational framework for bridge network optimal maintenance scheduling," Reliability Engineering and System Safety, Elsevier, vol. 96(2), pages 332-349.
    9. Yang, David Y. & Frangopol, Dan M., 2019. "Life-cycle management of deteriorating civil infrastructure considering resilience to lifetime hazards: A general approach based on renewal-reward processes," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 197-212.
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    Cited by:

    1. Yang, Yiming & Peng, Jianxin & Cai, C.S. & Zhou, Yadong & Wang, Lei & Zhang, Jianren, 2022. "Time-dependent reliability assessment of aging structures considering stochastic resistance degradation process," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    2. Ding, Wenzhe & Bai, Xiang & Wang, Qingwei & Long, Fang & Li, Hailin & Wu, Zhengrong & Liu, Jian & Yao, Huisheng & Yang, Hong, 2024. "A truncated test scheme design method for success-failure in-orbit tests," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Pugliese, F. & De Risi, R. & Sarno, L. Di, 2022. "Reliability assessment of existing RC bridges with spatially-variable pitting corrosion subjected to increasing traffic demand," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    4. Vega, Manuel A. & Hu, Zhen & Fillmore, Travis B. & Smith, Matthew D. & Todd, Michael D., 2021. "A Novel Framework for Integration of Abstracted Inspection Data and Structural Health Monitoring for Damage Prognosis of Miter Gates," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    5. Li Li & Yu Lu & Miaojuan Peng, 2022. "Deterioration Model for Reinforced Concrete Bridge Girders Based on Survival Analysis," Mathematics, MDPI, vol. 10(23), pages 1-16, November.
    6. Xu, Gaowei & Azhari, Fae, 2022. "Data-driven optimization of repair schemes and inspection intervals for highway bridges," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    7. Dan Su & Yi-Sheng Liu & Xin-Tong Li & Xiao-Yan Chen & Dong-Han Li, 2020. "Management Path of Concrete Beam Bridge in China from the Perspective of Sustainable Development," Sustainability, MDPI, vol. 12(17), pages 1-22, September.

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