IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i24p4774-d1004562.html
   My bibliography  Save this article

Computational Modeling of Latent Heat Thermal Energy Storage in a Shell-Tube Unit: Using Neural Networks and Anisotropic Metal Foam

Author

Listed:
  • Jana Shafi

    (Department of Computer Science, College of Arts and Science, Prince Sattam Bin Abdul Aziz University, Wadi Ad-Dawasir 11991, Saudi Arabia)

  • Mehdi Ghalambaz

    (Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam)

  • Mehdi Fteiti

    (Physics Department, Faculty of Applied Sciences, Umm Al-Qura University, Makkah 24381, Saudi Arabia)

  • Muneer Ismael

    (Mechanical Engineering Department, Engineering College, University of Basrah, Basrah 61004, Iraq)

  • Mohammad Ghalambaz

    (Laboratory on Convective Heat and Mass Transfer, Tomsk State University, 634045 Tomsk, Russia)

Abstract

Latent heat storage in a shell-tube is a promising method to store excessive solar heat for later use. The shell-tube unit is filled with a phase change material PCM combined with a high porosity anisotropic copper metal foam (FM) of high thermal conductivity. The PCM-MF composite was modeled as an anisotropic porous medium. Then, a two-heat equation mathematical model, a local thermal non-equilibrium approach LTNE, was adopted to consider the effects of the difference between the thermal conductivities of the PCM and the copper foam. The Darcy–Brinkman–Forchheimer formulation was employed to model the natural convection circulations in the molten PCM region. The thermal conductivity and the permeability of the porous medium were a function of an anisotropic angle. The finite element method was employed to integrate the governing equations. A neural network model was successfully applied to learn the transient physical behavior of the storage unit. The neural network was trained using 4998 sample data. Then, the trained neural network was utilized to map the relationship between control parameters and melting behavior to optimize the storage design. The impact of the anisotropic angle and the inlet pressure of heat transfer fluid (HTF) was addressed on the thermal energy storage of the storage unit. Moreover, an artificial neural network was successfully utilized to learn the transient behavior of the thermal storage unit for various combinations of control parameters and map the storage behavior. The results showed that the anisotropy angle significantly affects the energy storage time. The melting volume fraction MVF was maximum for a zero anisotropic angle where the local thermal conductivity was maximum perpendicular to the heated tube. An optimum storage rate could be obtained for an anisotropic angle smaller than 45°. Compared to a uniform MF, utilizing an optimum anisotropic angle could reduce the melting time by about 7% without impacting the unit’s thermal energy storage capacity or adding weight.

Suggested Citation

  • Jana Shafi & Mehdi Ghalambaz & Mehdi Fteiti & Muneer Ismael & Mohammad Ghalambaz, 2022. "Computational Modeling of Latent Heat Thermal Energy Storage in a Shell-Tube Unit: Using Neural Networks and Anisotropic Metal Foam," Mathematics, MDPI, vol. 10(24), pages 1-26, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:24:p:4774-:d:1004562
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/24/4774/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/24/4774/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Zhi & Lu, Yiji & Huang, Rui & Chang, Jinwei & Yu, Xiaonan & Jiang, Ruicheng & Yu, Xiaoli & Roskilly, Anthony Paul, 2021. "Applications and technological challenges for heat recovery, storage and utilisation with latent thermal energy storage," Applied Energy, Elsevier, vol. 283(C).
    2. Zhang, Shengqi & Pu, Liang & Mancin, Simone & Dai, Minghao & Xu, Lingling, 2022. "Role of partial and gradient filling strategies of copper foam on latent thermal energy storage: An experimental study," Energy, Elsevier, vol. 255(C).
    3. Ge, Ruihuan & Li, Qi & Li, Chuan & Liu, Qing, 2022. "Evaluation of different melting performance enhancement structures in a shell-and-tube latent heat thermal energy storage system," Renewable Energy, Elsevier, vol. 187(C), pages 829-843.
    4. Zhao, Chunrong & Wang, Jianyong & Sun, Yubiao & He, Suoying & Hooman, Kamel, 2022. "Fin design optimization to enhance PCM melting rate inside a rectangular enclosure," Applied Energy, Elsevier, vol. 321(C).
    5. Showkat Ahmad Bhat & Nen-Fu Huang & Imtiyaz Hussain & Farzana Bibi & Uzair Sajjad & Muhammad Sultan & Abdullah Saad Alsubaie & Khaled H. Mahmoud, 2021. "On the Classification of a Greenhouse Environment for a Rose Crop Based on AI-Based Surrogate Models," Sustainability, MDPI, vol. 13(21), pages 1-18, November.
    6. Cui, Wei & Si, Tianyu & Li, Xiangxuan & Li, Xinyi & Lu, Lin & Ma, Ting & Wang, Qiuwang, 2022. "Heat transfer enhancement of phase change materials embedded with metal foam for thermal energy storage: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    7. Buonomo, Bernardo & Manca, Oronzio & Nardini, Sergio & Plomitallo, Renato Elpidio, 2022. "Numerical study on latent heat thermal energy storage system with PCM partially filled with aluminum foam in local thermal equilibrium," Renewable Energy, Elsevier, vol. 195(C), pages 1368-1380.
    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. Zhang, Shuai & Yan, Yuying, 2022. "Evaluation of discharging performance of molten salt/ceramic foam composite phase change material in a shell-and-tube latent heat thermal energy storage unit," Renewable Energy, Elsevier, vol. 198(C), pages 1210-1223.
    2. Zhang, Shuai & Yan, Yuying, 2023. "Evaluation and optimisation of hybrid sensible-latent heat thermal energy storage unit with natural stones to enhance heat transfer," Renewable Energy, Elsevier, vol. 215(C).
    3. Huang, Xinyu & Li, Fangfei & Xiao, Tian & Li, Yuanji & Yang, Xiaohu & He, Ya-Ling, 2023. "Structural optimization of melting process of a latent heat energy storage unit and application of flip mechanism," Energy, Elsevier, vol. 280(C).
    4. Huang, Xinyu & Li, Fangfei & Guo, Junfei & Li, Yuanji & Du, Rui & Yang, Xiaohu & He, Ya-Ling, 2024. "Design optimization on solidification performance of a rotating latent heat thermal energy storage system subject to fluctuating heat source," Applied Energy, Elsevier, vol. 362(C).
    5. Zeng, Ziya & Zhao, Bingchen & Wang, Ruzhu, 2023. "High-power-density packed-bed thermal energy storage using form-stable expanded graphite-based phase change composite," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    6. Beata Pytlik & Daniel Smykowski & Piotr Szulc, 2022. "The Impact of Baffle Geometry in the PCM Heat Storage Unit on the Charging Process with High and Low Water Streams," Energies, MDPI, vol. 15(24), pages 1-17, December.
    7. Huo, Ying-Jie & Yan, Ting & Wu, Shao-Fei & Kuai, Zi-Han & Pan, Wei-Guo, 2024. "Preparation and thermal properties of palmitic acid/copper foam phase change materials," Energy, Elsevier, vol. 293(C).
    8. Hu, Yige & Wang, Hang & Chen, Hu & Ding, Yang & Liu, Changtian & Jiang, Feng & Ling, Xiang, 2023. "A novel hydrated salt-based phase change material for medium- and low-thermal energy storage," Energy, Elsevier, vol. 274(C).
    9. Xu, Ruoyu & Liu, Xiaochen & Liu, Xiaohua & Zhang, Tao, 2024. "Quantifying the energy flexibility potential of a centralized air-conditioning system: A field test study of hub airports," Energy, Elsevier, vol. 298(C).
    10. Tavakoli, Ali & Hashemi, Javad & Najafian, Mahyar & Ebrahimi, Amin, 2023. "Physics-based modelling and data-driven optimisation of a latent heat thermal energy storage system with corrugated fins," Renewable Energy, Elsevier, vol. 217(C).
    11. Yang, Chao & Xu, Xing-Rong & Bake, Maitiniyazi & Wu, Chun-Mei & Li, You-Rong & Zheng, Zhang-Jing & Yu, Jia-Jia, 2024. "Numerical investigation and optimization of the melting performance of latent heat thermal energy storage unit strengthened by graded metal foam and mechanical rotation," Renewable Energy, Elsevier, vol. 227(C).
    12. Li, Zhi & Wang, Lei & Jiang, Ruicheng & Wang, Bingzheng & Yu, Xiaonan & Huang, Rui & Yu, Xiaoli, 2022. "Experimental investigations on dynamic performance of organic Rankine cycle integrated with latent thermal energy storage under transient engine conditions," Energy, Elsevier, vol. 246(C).
    13. Li, Jiyan & Long, Yong & Jing, Yanju & Zhang, Jiaqing & Du, Silu & Jiao, Rui & Sun, Hanxue & Zhu, Zhaoqi & Liang, Weidong & Li, An, 2024. "Superhydrophobic multi-shell hollow microsphere confined phase change materials for solar photothermal conversion and energy storage," Applied Energy, Elsevier, vol. 365(C).
    14. Zhang, Shuai & Yan, Yuying, 2023. "Energy, exergy and economic analysis of ceramic foam-enhanced molten salt as phase change material for medium- and high-temperature thermal energy storage," Energy, Elsevier, vol. 262(PA).
    15. Gang Liu & Yuanji Li & Pan Wei & Tian Xiao & Xiangzhao Meng & Xiaohu Yang, 2022. "Thermo-Economic Assessments on a Heat Storage Tank Filled with Graded Metal Foam," Energies, MDPI, vol. 15(19), pages 1-16, September.
    16. Sohani, Ali & Cornaro, Cristina & Shahverdian, Mohammad Hassan & Moser, David & Pierro, Marco & Olabi, Abdul Ghani & Karimi, Nader & Nižetić, Sandro & Li, Larry K.B. & Doranehgard, Mohammad Hossein, 2023. "Techno-economic evaluation of a hybrid photovoltaic system with hot/cold water storage for poly-generation in a residential building," Applied Energy, Elsevier, vol. 331(C).
    17. Zhang, Shuai & Li, Ying & Yan, Yuying, 2024. "Hybrid sensible-latent heat thermal energy storage using natural stones to enhance heat transfer: Energy, exergy, and economic analysis," Energy, Elsevier, vol. 286(C).
    18. Qin, Siyu & Ji, Ruiyang & Miao, Chengyu & Jin, Liwen & Yang, Chun & Meng, Xiangzhao, 2024. "Review of enhancing boiling and condensation heat transfer: Surface modification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    19. Francesco Fornarelli & Lorenzo Dambrosio & Sergio Mario Camporeale & Luigi Terlizzi, 2023. "Novel Multi-Objective Optimal Design of a Shell-and-Tube Latent Heat Thermal Energy Storage Device," Energies, MDPI, vol. 16(4), pages 1-14, February.
    20. Modi, Nishant & Wang, Xiaolin & Negnevitsky, Michael, 2023. "Experimental investigation of the effects of inclination, fin height, and perforation on the thermal performance of a longitudinal finned latent heat thermal energy storage," Energy, Elsevier, vol. 274(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:jmathe:v:10:y:2022:i:24:p:4774-:d:1004562. 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.