IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v99y2012icp139-150.html
   My bibliography  Save this article

Automated finite element updating using strain data for the lifetime reliability assessment of bridges

Author

Listed:
  • Okasha, Nader M.
  • Frangopol, Dan M.
  • Orcesi, André D.

Abstract

The importance of improving the understanding of the performance of structures over their lifetime under uncertainty with information obtained from structural health monitoring (SHM) has been widely recognized. However, frameworks that efficiently integrate monitoring data into the life-cycle management of structures are yet to be developed. The objective of this paper is to propose and illustrate an approach for updating the lifetime reliability of aging bridges using monitored strain data obtained from crawl tests. It is proposed to use automated finite element model updating techniques as a tool for updating the resistance parameters of the structure. In this paper, the results from crawl tests are used to update the finite element model and, in turn, update the lifetime reliability. The original and updated lifetime reliabilities are computed using advanced computational tools. The approach is illustrated on an existing bridge.

Suggested Citation

  • Okasha, Nader M. & Frangopol, Dan M. & Orcesi, André D., 2012. "Automated finite element updating using strain data for the lifetime reliability assessment of bridges," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 139-150.
    • Handle: RePEc:eee:reensy:v:99:y:2012:i:c:p:139-150
    DOI: 10.1016/j.ress.2011.11.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832011002596
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2011.11.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Okasha, Nader M. & Frangopol, Dan M., 2010. "Redundancy of structural systems with and without maintenance: An approach based on lifetime functions," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 520-533.
    2. 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.
    3. 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.
    4. Marsh, Philip S. & Frangopol, Dan M., 2008. "Reinforced concrete bridge deck reliability model incorporating temporal and spatial variations of probabilistic corrosion rate sensor data," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 394-409.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jerez, D.J. & Jensen, H.A. & Beer, M., 2022. "An effective implementation of reliability methods for Bayesian model updating of structural dynamic models with multiple uncertain parameters," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    2. 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.
    3. Datteo, Alessio & Busca, Giorgio & Quattromani, Gianluca & Cigada, Alfredo, 2018. "On the use of AR models for SHM: A global sensitivity and uncertainty analysis framework," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 99-115.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Barone, Giorgio & Frangopol, Dan M., 2014. "Reliability, risk and lifetime distributions as performance indicators for life-cycle maintenance of deteriorating structures," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 21-37.
    2. Chou, Jui-Sheng & Le, Thanh-Son, 2011. "Reliability-based performance simulation for optimized pavement maintenance," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1402-1410.
    3. 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).
    4. Vishwanath, B Sharanbaswa & Banerjee, Swagata, 2023. "Considering uncertainty in corrosion process to estimate life-cycle seismic vulnerability and risk of aging bridge piers," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    5. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    6. Mitropoulou, Chara Ch. & Lagaros, Nikos D. & Papadrakakis, Manolis, 2011. "Life-cycle cost assessment of optimally designed reinforced concrete buildings under seismic actions," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1311-1331.
    7. Nogal, M. & Honfi, D., 2019. "Assessment of road traffic resilience assuming stochastic user behaviour," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 72-83.
    8. Okasha, Nader M. & Frangopol, Dan M., 2010. "Redundancy of structural systems with and without maintenance: An approach based on lifetime functions," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 520-533.
    9. Wang, Tiao & Li, Chunhe & Zheng, Jian-jun & Hackl, Jürgen & Luan, Yao & Ishida, Tetsuya & Medepalli, Satya, 2023. "Consideration of coupling of crack development and corrosion in assessing the reliability of reinforced concrete beams subjected to bending," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    10. Fan Zhang & Pingyi Wang & Huaihan Liu & Bin Zhang & Jianle Sun & Jian Li, 2023. "Inland Waterway Infrastructure Maintenance Prediction Model Based on Network-Level Assessment," Sustainability, MDPI, vol. 15(22), pages 1-17, November.
    11. Petchrompo, Sanyapong & Parlikad, Ajith Kumar, 2019. "A review of asset management literature on multi-asset systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 181-201.
    12. Bigaud, David & Ali, Osama, 2014. "Time-variant flexural reliability of RC beams with externally bonded CFRP under combined fatigue-corrosion actions," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 257-270.
    13. Tong Wang & Yang Liu & Qiyuan Li & Peng Du & Xiaogong Zheng & Qingfei Gao, 2023. "State-of-the-Art Review of the Resilience of Urban Bridge Networks," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    14. Andriotis, C.P. & Papakonstantinou, K.G., 2021. "Deep reinforcement learning driven inspection and maintenance planning under incomplete information and constraints," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    15. Andriotis, C.P. & Papakonstantinou, K.G., 2019. "Managing engineering systems with large state and action spaces through deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Huaizhi Su & Jiang Hu & Men Yang & Zhiping Wen, 2015. "Assessment and prediction for service life of water resources and hydropower engineering," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(3), pages 3005-3019, February.
    17. Klerk, Wouter Jan & Kanning, Wim & Kok, Matthijs & Wolfert, Rogier, 2021. "Optimal planning of flood defence system reinforcements using a greedy search algorithm," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    18. Iannacone, Leandro & Sharma, Neetesh & Tabandeh, Armin & Gardoni, Paolo, 2022. "Modeling Time-varying Reliability and Resilience of Deteriorating Infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 217(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:99:y:2012:i:c:p:139-150. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.