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Improving the solidification performance of a latent heat thermal energy storage unit using arrow-shaped fins obtained by an innovative fast optimization algorithm

Author

Listed:
  • Zheng, Zhang-Jing
  • Cai, Xiao
  • Yang, Chao
  • Xu, Yang

Abstract

Aiming to improve the solidification performance of the shell-and-tube latent heat thermal energy storage unit (LHTESU), a fin structure based on an innovative fast optimization algorithm is proposed. The fast optimization algorithm takes the distance from PCM to fin or cold source as the optimization objective. Genetic algorithm (GA) is used to find the minimum distance between PCM and fins or cold source. In order to deal with different types of fins, a unified method to calculate the distance between PCM and fins is designed. That is, the PCM region and the fin region are divided into smaller grids. The cold source/sink surface is also divided into smaller parts. The distance between PCM and fins or cold source is represented by the sum of the distances between each PCM grid and its nearest fin gird or cold source/sink surface. The cross-section structure of one-level Y-shaped fin in shell-and-tube LHTESU is optimized based on the proposed fast optimization algorithm. The length of each branch, the width ratio of sub-branch to main-branch, and the angle between the sub-branch are selected as the variables. The fin mass expressed by the fin cross area is selected as the constraint condition. Monte Carlo method is used to calculate the fin area due to the complex structure of Y-shaped fin. Meanwhile the effects of cold source and fin number on the final optimization results are also studied. The results show that the optimized fin has an arrow shape. When the number of fins is 2, compared with the traditional Y-shaped fin, the arrow-shaped fin can shorten the complete solidification time by more than 52.8% and increase the heat release rate by more than 110%.

Suggested Citation

  • Zheng, Zhang-Jing & Cai, Xiao & Yang, Chao & Xu, Yang, 2022. "Improving the solidification performance of a latent heat thermal energy storage unit using arrow-shaped fins obtained by an innovative fast optimization algorithm," Renewable Energy, Elsevier, vol. 195(C), pages 566-577.
    • Handle: RePEc:eee:renene:v:195:y:2022:i:c:p:566-577
    DOI: 10.1016/j.renene.2022.06.031
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    References listed on IDEAS

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    3. Liu, Shuli & Han, Junrui & Shen, Yongliang & Khan, Sheher Yar & Ji, Wenjie & Jin, Haibo & Kumar, Mahesh, 2025. "The contribution of artificial intelligence to phase change materials in thermal energy storage: From prediction to optimization," Renewable Energy, Elsevier, vol. 238(C).
    4. Yang Xu & Hang Yin & Chen He & Yong Wei & Ming Cui & Zhang-Jing Zheng, 2022. "Structure Optimization of Longitudinal Rectangular Fins to Improve the Melting Performance of Phase Change Materials through Genetic Algorithm," Energies, MDPI, vol. 15(24), pages 1-21, December.
    5. Jiang, Ruicheng & Qian, Gao & Li, Zhi & Yu, Xiaoli & Lu, Yiji, 2024. "Progress and challenges of latent thermal energy storage through external field-dependent heat transfer enhancement methods," Energy, Elsevier, vol. 304(C).
    6. He, Fan & Bo, Renfei & Hu, Chenxi & Meng, Xi & Gao, Weijun, 2023. "Employing spiral fins to improve the thermal performance of phase-change materials in shell-tube latent heat storage units," Renewable Energy, Elsevier, vol. 203(C), pages 518-528.

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