IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i24p9408-d1001209.html
   My bibliography  Save this article

Reliability Analysis and Life Prediction of Aging LNG Unloading Arms Based on Non-Destructive Test Data

Author

Listed:
  • Duc-Vu Ngo

    (Department of Ocean Science and Engineering, Kunsan National University, Gunsan 54150, Republic of Korea)

  • Jong-Kwon Lim

    (VARM Brain Co., Ltd., Seoul 05634, Republic of Korea)

  • Dong-Hyawn Kim

    (School of Architecture and Coastal Construction Engineering, Kunsan National University, Gunsan 54150, Republic of Korea)

Abstract

Unloading arms (ULAs) among seaport infrastructures are susceptible to deterioration posed by the effects of harsh marine environmental conditions. During infrastructure’s service life, the deterioration of structural integrity may increase the risk of failure of infrastructure, and should be taken into account during structural reliability assessment. In this study, a simple non-destructive test (NDT) was employed to examine the structural deterioration of ULAs which were installed over 30 years ago. Then, these aging ULAs were modeled by the finite-element program, using non-destructive test data to update the thickness dimensions of structural members. Next, a reliability assessment was conducted based on the stress distribution of the main structural components under external loads, which are calculated by their relation to wind speed. Moreover, the time-dependent reliability index curve was also built by considering the deterioration function to predict the failure probability of the particular components during the remaining lifetime. The study revealed that the present condition of the ULA system was satisfactory for current loading conditions. A reliability index predicted with deteriorations factors may be a rational and appropriate approach for the assessment of aging structures needed for efficient infrastructure management.

Suggested Citation

  • Duc-Vu Ngo & Jong-Kwon Lim & Dong-Hyawn Kim, 2022. "Reliability Analysis and Life Prediction of Aging LNG Unloading Arms Based on Non-Destructive Test Data," Energies, MDPI, vol. 15(24), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9408-:d:1001209
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/24/9408/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/24/9408/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cao Wang, 2021. "Time-Dependent Reliability Assessment," Springer Series in Reliability Engineering, in: Structural Reliability and Time-Dependent Reliability, chapter 0, pages 263-359, Springer.
    2. Kim, Dong Hyawn & Lee, Sang Geun, 2015. "Reliability analysis of offshore wind turbine support structures under extreme ocean environmental loads," Renewable Energy, Elsevier, vol. 79(C), pages 161-166.
    3. Liu, Yan & Frangopol, Dan M., 2018. "Time-dependent reliability assessment of ship structures under progressive and shock deteriorations," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 116-128.
    4. Wang, Cao & Zhang, Hao & Li, Quanwang, 2017. "Reliability assessment of aging structures subjected to gradual and shock deteriorations," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 78-86.
    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. Duc-Vu Ngo & Young-Jin Kim & Dong-Hyawn Kim, 2023. "Risk Assessment of Offshore Wind Turbines Suction Bucket Foundation Subject to Multi-Hazard Events," Energies, MDPI, vol. 16(5), pages 1-13, February.

    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. 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.
    2. 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).
    3. 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).
    4. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    5. Zhang, Yang & Xu, Jun & Beer, Michael, 2023. "A single-loop time-variant reliability evaluation via a decoupling strategy and probability distribution reconstruction," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    6. Song, Yupeng & Basu, Biswajit & Zhang, Zili & Sørensen, John Dalsgaard & Li, Jie & Chen, Jianbing, 2021. "Dynamic reliability analysis of a floating offshore wind turbine under wind-wave joint excitations via probability density evolution method," Renewable Energy, Elsevier, vol. 168(C), pages 991-1014.
    7. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
    8. Li, Shen & Kim, Do Kyun & Benson, Simon, 2021. "A probabilistic approach to assess the computational uncertainty of ultimate strength of hull girders," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    9. Wang, L. & Kolios, A. & Liu, X. & Venetsanos, D. & Rui, C., 2022. "Reliability of offshore wind turbine support structures: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    10. Li, Jianlan & Zhang, Xuran & Zhou, Xing & Lu, Luyi, 2019. "Reliability assessment of wind turbine bearing based on the degradation-Hidden-Markov model," Renewable Energy, Elsevier, vol. 132(C), pages 1076-1087.
    11. Zhiyu Jiang & Weifei Hu & Wenbin Dong & Zhen Gao & Zhengru Ren, 2017. "Structural Reliability Analysis of Wind Turbines: A Review," Energies, MDPI, vol. 10(12), pages 1-25, December.
    12. Jiang, Chen & Qiu, Haobo & Gao, Liang & Wang, Dapeng & Yang, Zan & Chen, Liming, 2020. "EEK-SYS: System reliability analysis through estimation error-guided adaptive Kriging approximation of multiple limit state surfaces," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    13. Zhang, Kun & Chen, Ning & Zeng, Peng & Liu, Jian & Beer, Michael, 2022. "An efficient reliability analysis method for structures with hybrid time-dependent uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    14. Wu, Xiaoni & Hu, Yu & Li, Ye & Yang, Jian & Duan, Lei & Wang, Tongguang & Adcock, Thomas & Jiang, Zhiyu & Gao, Zhen & Lin, Zhiliang & Borthwick, Alistair & Liao, Shijun, 2019. "Foundations of offshore wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 379-393.
    15. Gaidai, Oleg & Xu, Xiaosen & Wang, Junlei & Ye, Renchuan & Cheng, Yong & Karpa, Oleh, 2020. "SEM-REV offshore energy site wind-wave bivariate statistics by hindcast," Renewable Energy, Elsevier, vol. 156(C), pages 689-695.
    16. Bracale, Antonio & Carpinelli, Guido & De Falco, Pasquale, 2017. "A new finite mixture distribution and its expectation-maximization procedure for extreme wind speed characterization," Renewable Energy, Elsevier, vol. 113(C), pages 1366-1377.
    17. Okpokparoro, Salem & Sriramula, Srinivas, 2021. "Uncertainty modeling in reliability analysis of floating wind turbine support structures," Renewable Energy, Elsevier, vol. 165(P1), pages 88-108.
    18. Agostino Torti & Marika Arena & Giovanni Azzone & Piercesare Secchi & Simone Vantini, 2022. "Bridge closure in the road network of Lombardy: a spatio-temporal analysis of the socio-economic impacts," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 901-923, October.
    19. Shittu, Abdulhakim Adeoye & Mehmanparast, Ali & Hart, Phil & Kolios, Athanasios, 2021. "Comparative study between S-N and fracture mechanics approach on reliability assessment of offshore wind turbine jacket foundations," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    20. Seo, Junwon & Pokhrel, Jharna & Hu, Jong Wan, 2022. "Multi-Hazard Fragility Analysis of Offshore Wind Turbine Portfolios using Surrogate Models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(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:gam:jeners:v:15:y:2022:i:24:p:9408-:d:1001209. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.