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Methods to Increase the Robustness of Finite-Volume Flow Models in Thermodynamic Systems

Author

Listed:
  • Sylvain Quoilin

    (Thermodynamics Laboratory, University of Liege, Batiment B49, Chemin des Chevreuils 7, 4000 Liège, Belgium)

  • Ian Bell

    (Thermodynamics Laboratory, University of Liege, Batiment B49, Chemin des Chevreuils 7, 4000 Liège, Belgium)

  • Adriano Desideri

    (Thermodynamics Laboratory, University of Liege, Batiment B49, Chemin des Chevreuils 7, 4000 Liège, Belgium)

  • Pierre Dewallef

    (Thermodynamics Laboratory, University of Liege, Batiment B49, Chemin des Chevreuils 7, 4000 Liège, Belgium)

  • Vincent Lemort

    (Thermodynamics Laboratory, University of Liege, Batiment B49, Chemin des Chevreuils 7, 4000 Liège, Belgium)

Abstract

This paper addresses the issues linked to simulation failures during integration in finite-volume flow models, especially those involving a two-phase state. This kind of model is particularly useful when modeling 1D heat exchangers or piping, e.g., in thermodynamic cycles involving a phase change. Issues, such as chattering or stiff systems, can lead to low simulation speed, instabilities and simulation failures. In the particular case of two-phase flow models, they are usually linked to a discontinuity in the density derivative between the liquid and two-phase zones. In this work, several methods to tackle numerical problems are developed, described, implemented and compared. In addition, methods available in the literature are also implemented and compared to the proposed approaches. Results suggest that the robustness of the models can be significantly increased with these different methods, at the price of a small increase of the error in the mass and energy balances.

Suggested Citation

  • Sylvain Quoilin & Ian Bell & Adriano Desideri & Pierre Dewallef & Vincent Lemort, 2014. "Methods to Increase the Robustness of Finite-Volume Flow Models in Thermodynamic Systems," Energies, MDPI, vol. 7(3), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:3:p:1621-1640:d:34145
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    References listed on IDEAS

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    1. Quoilin, Sylvain & Aumann, Richard & Grill, Andreas & Schuster, Andreas & Lemort, Vincent & Spliethoff, Hartmut, 2011. "Dynamic modeling and optimal control strategy of waste heat recovery Organic Rankine Cycles," Applied Energy, Elsevier, vol. 88(6), pages 2183-2190, June.
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    2. Pili, Roberto & Romagnoli, Alessandro & Jiménez-Arreola, Manuel & Spliethoff, Hartmut & Wieland, Christoph, 2019. "Simulation of Organic Rankine Cycle – Quasi-steady state vs dynamic approach for optimal economic performance," Energy, Elsevier, vol. 167(C), pages 619-640.
    3. Vaupel, Yannic & Huster, Wolfgang R. & Holtorf, Flemming & Mhamdi, Adel & Mitsos, Alexander, 2019. "Analysis and improvement of dynamic heat exchanger models for nominal and start-up operation," Energy, Elsevier, vol. 169(C), pages 1191-1201.
    4. Cai, Jinwen & Shu, Gequn & Tian, Hua & Wang, Xuan & Wang, Rui & Shi, Xiaolei, 2020. "Validation and analysis of organic Rankine cycle dynamic model using zeotropic mixture," Energy, Elsevier, vol. 197(C).
    5. Desideri, Adriano & Hernandez, Andres & Gusev, Sergei & van den Broek, Martijn & Lemort, Vincent & Quoilin, Sylvain, 2016. "Steady-state and dynamic validation of a small-scale waste heat recovery system using the ThermoCycle Modelica library," Energy, Elsevier, vol. 115(P1), pages 684-696.
    6. Cai, Jinwen & Tian, Hua & Wang, Xuan & Wang, Rui & Shu, Gequn & Wang, Mingtao, 2021. "A calibrated organic Rankine cycle dynamic model applying to subcritical system and transcritical system," Energy, Elsevier, vol. 237(C).
    7. Abarr, Miles & Geels, Brendan & Hertzberg, Jean & Montoya, Lupita D., 2017. "Pumped thermal energy storage and bottoming system part A: Concept and model," Energy, Elsevier, vol. 120(C), pages 320-331.
    8. Adriano Desideri & Bertrand Dechesne & Jorrit Wronski & Martijn Van den Broek & Sergei Gusev & Vincent Lemort & Sylvain Quoilin, 2016. "Comparison of Moving Boundary and Finite-Volume Heat Exchanger Models in the Modelica Language," Energies, MDPI, vol. 9(5), pages 1-18, May.
    9. Pili, R. & Eyerer, S. & Dawo, F. & Wieland, C. & Spliethoff, H., 2020. "Development of a non-linear state estimator for advanced control of an ORC test rig for geothermal application," Renewable Energy, Elsevier, vol. 161(C), pages 676-690.
    10. Gleinser, Moritz & Wieland, Christoph & Spliethoff, Hartmut, 2018. "Batch evaporation power cycle: Influence of thermal inertia and residence time," Energy, Elsevier, vol. 157(C), pages 1090-1101.
    11. Imran, Muhammad & Pili, Roberto & Usman, Muhammad & Haglind, Fredrik, 2020. "Dynamic modeling and control strategies of organic Rankine cycle systems: Methods and challenges," Applied Energy, Elsevier, vol. 276(C).
    12. Palagi, Laura & Pesyridis, Apostolos & Sciubba, Enrico & Tocci, Lorenzo, 2019. "Machine Learning for the prediction of the dynamic behavior of a small scale ORC system," Energy, Elsevier, vol. 166(C), pages 72-82.
    13. Yousefzadeh, Moslem & Uzgoren, Eray, 2015. "Mass-conserving dynamic organic Rankine cycle model to investigate the link between mass distribution and system state," Energy, Elsevier, vol. 93(P1), pages 1128-1139.

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