Data-driven multi-fidelity topology design of fin structures for latent heat thermal energy storage

Luo, Ji-Wang; Yaji, Kentaro; Chen, Li et al.

Applied Energy, 2024, 377, 124596

Number of Access:477（2025-08-14 00:38 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/98219

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Title
Data-driven multi-fidelity topology design of fin structures for latent heat thermal energy storage
Creator
CreatorName
Luo, Ji-Wang
NRID
1000090779373 1000090779373
ORCID
0000-0002-4309-2043 0000-0002-4309-2043
researchmap permalink
yajiken0609 yajiken0609
Scopus Author ID
55787947500 55787947500
CreatorName
Yaji, Kentaro
CreatorName
Chen, Li
CreatorName
Tao, Wen-Quan
Subject
Topology optimization
Data-driven approach
Multi-fidelity design
Phase change material
Latent heat thermal energy storage
Heat transfer enhancement
Description
Luo Ji-Wang, Yaji Kentaro, Chen Li, et al. Data-driven multi-fidelity topology design of fin structures for latent heat thermal energy storage. Applied Energy 377, 124596 (2024); https://doi.org/10.1016/j.apenergy.2024.124596.
Abstract
This work develops a data-driven multi-fidelity topology design (MFTD) method for designing fins in a latent heat thermal energy storage tube. The high-fidelity simulation resolves the actual solid-liquid phase change process using the enthalpy method, while the low-fidelity topology optimization (TO) simply considers the natural convection with Darcy flow. The above MFTD method is integrated into the framework of evolutional algorithm, and the variational autoencoder is introduced to generate new offspring. Fins for accelerating the melting and solidification processes at different Grashof number (Gr) are designed. It is found that when the fin volume fraction is low, the melt designs exhibit strong heterogeneity due to the strong convection, while the solidification designs are almost isotropic. Along with the increase of the fin volume fraction, the fins are first getting longer, then having more branches or sub-branches and finally becoming thicker. The superiority of the present data-driven MFTD method to the gradient-based direct TO method for solving optimization problems with strong multimodality has been demonstrated in this work. Results find that compared with the designs from direct TO, the MFTD melt design can further reduce the melting time by at least 27 % and 20 % at Gr = 3.3 × 103 and Gr = 3.3 × 104 respectively, and the MFTD solidification design can further shorten the solidification time by at least 9 %.
Publisher
Elsevier BV
Source Title
Applied Energy
Volume (Issue)
377
Page
124596
Date of Issued
2024-10-01
Handle URL
https://hdl.handle.net/11094/98219
PISSN
03062619
Relation.isVersionOf
DOI (Publisher Version)
https://doi.org/10.1016/j.apenergy.2024.124596
Access Rights
embargoed access
CopyRight
© 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
oaire:version
Accepted Manuscript
Category
学術雑誌論文 Journal Article