IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2018i1p1-d191909.html
   My bibliography  Save this article

Development of a Physics-Based Monitoring Algorithm Detecting CO 2 Ingress Accidents in a Sodium-Cooled Fast Reactor

Author

Listed:
  • Hyeonmin Kim

    (ICT Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea)

  • Jung-Taek Kim

    (ICT Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea)

  • Jaehyuk Eoh

    (SFR Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea)

  • Dong-Won Lim

    (Department of Mechanical Engineering, University of Suwon, Gyeonggi-do 18323, Korea)

Abstract

One of the benefits of the supercritical CO 2 Brayton cycle in Sodium-cooled Fast Reactors is an enhanced plant safety, since potential reactions of CO 2 with liquid sodium have been reported to be less stringent than a sodium-water reaction found in the Rankine cycle. However, moderate chemical interactions between CO 2 and liquid sodium make detecting CO 2 ingress accidents harder. Thus, this paper proposes a new physics-based detection algorithm by comparing the real-time pressure measurements of two identical heat exchangers for the early detection. The CO 2 ingress occurs owing to a crack at the pressure boundary wall, a certain self-recovery of structural damage does not happen over time, and an accident probabilistically starts at only one component of two. The proposed physics-based method with the probabilistic analysis was compared to the pure data-based method. Finally, the damage degradation was developed with a simplified mass and energy transfer model, and the proposed algorithm was verified with experimental data. The results show that a 99.99% detection probability can be achieved for the air ingress of 30 cc/s, which is equivalent to the 0.12 g/s CO 2 ingress, in a 70 s detection time, limiting down to 0.1% false alarms due to sensor noise.

Suggested Citation

  • Hyeonmin Kim & Jung-Taek Kim & Jaehyuk Eoh & Dong-Won Lim, 2018. "Development of a Physics-Based Monitoring Algorithm Detecting CO 2 Ingress Accidents in a Sodium-Cooled Fast Reactor," Energies, MDPI, vol. 12(1), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:1-:d:191909
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/1/1/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/1/1/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abram, Tim & Ion, Sue, 2008. "Generation-IV nuclear power: A review of the state of the science," Energy Policy, Elsevier, vol. 36(12), pages 4323-4330, December.
    2. Cross, Philip & Ma, Xiandong, 2014. "Nonlinear system identification for model-based condition monitoring of wind turbines," Renewable Energy, Elsevier, vol. 71(C), pages 166-175.
    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. Alexandra Akins & Derek Kultgen & Alexander Heifetz, 2023. "Anomaly Detection in Liquid Sodium Cold Trap Operation with Multisensory Data Fusion Using Long Short-Term Memory Autoencoder," Energies, MDPI, vol. 16(13), pages 1-19, June.

    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. Miguel A. Rodríguez-López & Luis M. López-González & Luis M. López-Ochoa & Jesús Las-Heras-Casas, 2018. "Methodology for Detecting Malfunctions and Evaluating the Maintenance Effectiveness in Wind Turbine Generator Bearings Using Generic versus Specific Models from SCADA Data," Energies, MDPI, vol. 11(4), pages 1-22, March.
    2. Peng Sun & Jian Li & Junsheng Chen & Xiao Lei, 2016. "A Short-Term Outage Model of Wind Turbines with Doubly Fed Induction Generators Based on Supervisory Control and Data Acquisition Data," Energies, MDPI, vol. 9(11), pages 1-21, October.
    3. Delsoto, G.S. & Battisti, F.G. & da Silva, A.K., 2023. "Dynamic modeling and control of a solar-powered Brayton cycle using supercritical CO2 and optimization of its thermal energy storage," Renewable Energy, Elsevier, vol. 206(C), pages 336-356.
    4. Xu, Qifa & Fan, Zhenhua & Jia, Weiyin & Jiang, Cuixia, 2020. "Fault detection of wind turbines via multivariate process monitoring based on vine copulas," Renewable Energy, Elsevier, vol. 161(C), pages 939-955.
    5. Crespi, Francesco & Gavagnin, Giacomo & Sánchez, David & Martínez, Gonzalo S., 2017. "Supercritical carbon dioxide cycles for power generation: A review," Applied Energy, Elsevier, vol. 195(C), pages 152-183.
    6. Locatelli, Giorgio & Mancini, Mauro & Todeschini, Nicola, 2013. "Generation IV nuclear reactors: Current status and future prospects," Energy Policy, Elsevier, vol. 61(C), pages 1503-1520.
    7. Rodríguez-López, Miguel A. & López-González, Luis M. & López-Ochoa, Luis M. & Las-Heras-Casas, Jesús, 2016. "Development of indicators for the detection of equipment malfunctions and degradation estimation based on digital signals (alarms and events) from operation SCADA," Renewable Energy, Elsevier, vol. 99(C), pages 224-236.
    8. Gao, Richie & Gao, Zhiwei, 2016. "Pitch control for wind turbine systems using optimization, estimation and compensation," Renewable Energy, Elsevier, vol. 91(C), pages 501-515.
    9. Chenhua Ni & Xiandong Ma, 2018. "Prediction of Wave Power Generation Using a Convolutional Neural Network with Multiple Inputs," Energies, MDPI, vol. 11(8), pages 1-18, August.
    10. Santos, Ricardo Luis Pereira dos & Rosa, Luiz Pinguelli & Arouca, Maurício Cardoso & Ribeiro, Alan Emanuel Duailibe, 2013. "The importance of nuclear energy for the expansion of Brazil's electricity grid," Energy Policy, Elsevier, vol. 60(C), pages 284-289.
    11. Bi, Ran & Zhou, Chengke & Hepburn, Donald M., 2017. "Detection and classification of faults in pitch-regulated wind turbine generators using normal behaviour models based on performance curves," Renewable Energy, Elsevier, vol. 105(C), pages 674-688.
    12. Lorenzo Malerba & Abderrahim Al Mazouzi & Marjorie Bertolus & Marco Cologna & Pål Efsing & Adrian Jianu & Petri Kinnunen & Karl-Fredrik Nilsson & Madalina Rabung & Mariano Tarantino, 2022. "Materials for Sustainable Nuclear Energy: A European Strategic Research and Innovation Agenda for All Reactor Generations," Energies, MDPI, vol. 15(5), pages 1-48, March.
    13. Stephen Thomas & M. V. Ramana, 2022. "A hopeless pursuit? National efforts to promote small modular nuclear reactors and revive nuclear power," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(4), July.
    14. Pfenninger, Stefan & Keirstead, James, 2015. "Comparing concentrating solar and nuclear power as baseload providers using the example of South Africa," Energy, Elsevier, vol. 87(C), pages 303-314.
    15. Chen, Junsheng & Li, Jian & Chen, Weigen & Wang, Youyuan & Jiang, Tianyan, 2020. "Anomaly detection for wind turbines based on the reconstruction of condition parameters using stacked denoising autoencoders," Renewable Energy, Elsevier, vol. 147(P1), pages 1469-1480.
    16. Frederik Reitsma & Peter Woods & Martin Fairclough & Yongjin Kim & Harikrishnan Tulsidas & Luis Lopez & Yanhua Zheng & Ahmed Hussein & Gerd Brinkmann & Nils Haneklaus & Anand Rao Kacham & Tumuluri Sre, 2018. "On the Sustainability and Progress of Energy Neutral Mineral Processing," Sustainability, MDPI, vol. 10(1), pages 1-18, January.
    17. Contu, Davide & Strazzera, Elisabetta & Mourato, Susana, 2016. "Modeling individual preferences for energy sources: The case of IV generation nuclear energy in Italy," Ecological Economics, Elsevier, vol. 127(C), pages 37-58.
    18. Brook, Barry W., 2012. "Could nuclear fission energy, etc., solve the greenhouse problem? The affirmative case," Energy Policy, Elsevier, vol. 42(C), pages 4-8.
    19. Crespi, Francesco & Sánchez, David & Rodríguez, José M. & Gavagnin, Giacomo, 2020. "A thermo-economic methodology to select sCO2 power cycles for CSP applications," Renewable Energy, Elsevier, vol. 147(P3), pages 2905-2912.
    20. Ramana, M.V. & Saikawa, Eri, 2011. "Choosing a standard reactor: International competition and domestic politics in Chinese nuclear policy," Energy, Elsevier, vol. 36(12), pages 6779-6789.

    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:12:y:2018:i:1:p:1-:d:191909. 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.