IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i6p1506-d1615043.html
   My bibliography  Save this article

A Novel Model for U-Tube Steam Generators for Pressurized Water Reactors

Author

Listed:
  • Huseyin Emre Sahin

    (Mechanical Engineering Department, Pamukkale University, 20160 Denizli, Turkey)

  • Harun Kemal Ozturk

    (Mechanical Engineering Department, Pamukkale University, 20160 Denizli, Turkey)

Abstract

A novel model was proposed for U-Tube Steam Generators in Pressurized Water Reactors to be utilized in dynamics and control studies. The steam generator was divided into 14 nodes and investigated by applying mass and energy conservation equations in differential form. A system of nonlinear differential equations was obtained. This equation system was numerically simulated using the Julia programming language through a fourth order Runge–Kutta method. Accurate values for thermodynamic properties were taken from the Coolprop library, eliminating the need to take constant values or linear interpolations. A three-element proportional and integral control was applied as the control system in the model. Changes in feedwater flow rate, steam outlet flow rate, primary inlet flow rate, feedwater inlet temperature and primary inlet temperature were investigated, and the response of the steam generator was simulated using the developed model. It was observed that the proposed model gives results for U-Tube Steam Generators comparable to those in the literature and that it can be used in dynamic model and control simulations.

Suggested Citation

  • Huseyin Emre Sahin & Harun Kemal Ozturk, 2025. "A Novel Model for U-Tube Steam Generators for Pressurized Water Reactors," Energies, MDPI, vol. 18(6), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:6:p:1506-:d:1615043
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/6/1506/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/6/1506/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lorenzo Bolfo & Francesco Devia & Guglielmo Lomonaco, 2021. "Nuclear Hydrogen Production: Modeling and Preliminary Optimization of a Helical Tube Heat Exchanger," Energies, MDPI, vol. 14(11), pages 1-24, May.
    2. Hui, Jiuwu, 2024. "Fixed-time fractional-order sliding mode controller with disturbance observer for U-tube steam generator," Renewable and Sustainable Energy Reviews, Elsevier, vol. 205(C).
    3. Ben Qi & Jingang Liang & Jiejuan Tong, 2023. "Fault Diagnosis Techniques for Nuclear Power Plants: A Review from the Artificial Intelligence Perspective," Energies, MDPI, vol. 16(4), pages 1-27, February.
    Full references (including those not matched with items on IDEAS)

    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. Alvaro Rodríguez-Prieto & Ana María Camacho & Carlos Mendoza & John Kickhofel & Guglielmo Lomonaco, 2021. "Evolution of Standardized Specifications on Materials, Manufacturing and In-Service Inspection of Nuclear Reactor Vessels," Sustainability, MDPI, vol. 13(19), pages 1-25, September.
    2. Hui Xiang & Xiaolei Li & Xiao Liao & Wei Cui & Fengkai Liu & Donghe Li, 2025. "Artificial Intelligence in Renewable Energy Systems: Applications and Security Challenges," Energies, MDPI, vol. 18(8), pages 1-24, April.
    3. Ricardo Fabricio Escobar-Jiménez & Isaac Justine Canela-Sánchez & Manuel Adam-Medina & Abisai Acevedo-Quiroz & Armando Huicochea-Rodríguez & David Juárez-Romero, 2024. "Implementation of Adaptive Observer and Mathematical Model Validation of the Evaporator of an Absorption Heat Transformer," Mathematics, MDPI, vol. 12(23), pages 1-21, November.
    4. Daria Kolbantseva & Dmitriy Treschev & Milana Trescheva & Irina Anikina & Yuriy Kolbantsev & Konstantin Kalmykov & Alena Aleshina & Aleksandr Kalyutik & Iaroslav Vladimirov, 2022. "Analysis of Technologies for Hydrogen Consumption, Transition and Storage at Operating Thermal Power Plants," Energies, MDPI, vol. 15(10), pages 1-30, May.
    5. Seyed Majid Bigonah Ghalehsari & Jiaming Wang & Tianyi Zhao, 2025. "A Review of the Evaluation, Simulation, and Control of the Air Conditioning System in a Nuclear Power Plant," Energies, MDPI, vol. 18(7), pages 1-15, March.
    6. Lorenzo Damiani & Francesco Novarini & Guglielmo Lomonaco, 2025. "An FMEA Assessment of an HTR-Based Hydrogen Production Plant," Energies, MDPI, vol. 18(8), pages 1-22, April.
    7. Yangping Zhou & Zhengwei Gu & Yujie Dong & Fangzhou Xu & Zuoyi Zhang, 2021. "Combining Dual Fluidized Bed and High-Temperature Gas-Cooled Reactor for Co-Producing Hydrogen and Synthetic Natural Gas by Biomass Gasification," Energies, MDPI, vol. 14(18), pages 1-21, September.
    8. Zhaohui Liu & Enhong Hu & Hua Liu, 2025. "A Fault Diagnosis Framework for Pressurized Water Reactor Nuclear Power Plants Based on an Improved Deep Subdomain Adaptation Network," Energies, MDPI, vol. 18(9), pages 1-23, May.
    9. Chenyang Lai & Ibrahim Ahmed & Enrico Zio & Wei Li & Yiwang Zhang & Wenqing Yao & Juan Chen, 2024. "A Multistage Physics-Informed Neural Network for Fault Detection in Regulating Valves of Nuclear Power Plants," Energies, MDPI, vol. 17(11), pages 1-23, May.
    10. Xingyu Xiao & Jingang Liang & Jiejuan Tong & Haitao Wang, 2024. "Emergency Decision Support Techniques for Nuclear Power Plants: Current State, Challenges, and Future Trends," Energies, MDPI, vol. 17(10), pages 1-35, May.
    11. Zhiqiang Peng & Jichong Lei & Zining Ni & Tao Yu & Jinsen Xie & Jun Hong & Hong Hu, 2024. "Research on Data-Driven Methods for Solving High-Dimensional Neutron Transport Equations," Energies, MDPI, vol. 17(16), pages 1-11, August.
    12. Xingyu Xiao & Ben Qi & Jingang Liang & Jiejuan Tong & Qing Deng & Peng Chen, 2023. "Enhancing LOCA Breach Size Diagnosis with Fundamental Deep Learning Models and Optimized Dataset Construction," Energies, MDPI, vol. 17(1), pages 1-20, December.
    13. Miltiadis Alamaniotis & Konstantinos Ipiotis, 2025. "Artificial Intelligence as Enabler for Adoption of Sustainable Nuclear-Powered Maritime Ships: Challenges and Opportunities," Sustainability, MDPI, vol. 17(8), pages 1-21, April.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:18:y:2025:i:6:p:1506-:d:1615043. 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.