logo

Chinese Science Bulletin, Volume 64, Issue 11: 1191-1199(2019) https://doi.org/10.1360/N972018-01134

The topology optimization of the fin structure in latent heat storage

More info
  • ReceivedNov 16, 2018
  • AcceptedDec 5, 2018
  • PublishedMar 29, 2019

Abstract

Latent heat storage is widely investigated by the researchers due to its high volumetric energy density which makes it possible to largely reduce the energy storage cost. However, the phase change materials are known to suffer from poor thermal conductivity which greatly limits its use in the industry. A large amount of work has been carried out to enhance the heat transfer capability of the latent heat storage system. From a structural perspective, embedding of fin structure into the heat storage tank is considered as an effective way to lead to the overall heat transfer enhancement. For the moment, shape optimization and sizing optimization are the two most common optimization methods that are used to find the efficient finned structure in a heat storage tank. However, by predefining the shape of the geometry, the shape optimization and sizing optimization have more constraints when performing the optimization which limits the possibilities of a design change. Different from these two optimization approaches mentioned above, the topology optimization requires only few constraints when performing the optimization which enables dramatic design change without predefining the shape of the geometry. The core problem solved by the topology optimization is about the distribution of the materials and their topological connection within the design field. By topology optimization, high thermal conductive materials can be distributed in the heat storage tank in a way which maximizes the overall heat transfer capability of the heat storage system.

The topology optimization of a classic tube-and-shell latent heat storage tank is studied in this paper to enhance the overall heat transfer capability. By combining the topology optimization theory and the classic finite element method, a 2-D heat storage tank model has been built for the optimization of the fin structure. Besides, a comparison between the topology optimized fin structure and other typical types of fin structures is carried out. The numerical simulation is also performed considering the effect of natural convection to see its impact on the design change of final result. Furthermore, the current research on topology optimization focuses mainly on the design phase. Few studies have been done to validate numerically the reliability of the reconstructed topology optimized design which is necessary before an experimental validation. Hence, in this paper, a numerical reconstruction of the fin structures is carried out and the validation of the result is performed. Several results could be drawn from the current research: The topology optimization shows its advantage over common fin structure design; The influence of natural convection on optimization has been investigated and analyzed; The result has been reconstructed in common CAD form and corresponding validation has been performed which serves for the preparation of the upcoming experimental investigation.


Funded by

国家重点基础研究发展计划(2013CB228303)


References

[1] Zalba B, Marı́n J M, Cabeza L F, et al. Review on thermal energy storage with phase change: Materials, heat transfer analysis and applications. Appl Thermal Eng, 2003, 23: 251-283 CrossRef Google Scholar

[2] Zhang H, Baeyens J, Cáceres G, et al. Thermal energy storage: Recent developments and practical aspects. Prog Energy Combust Sci, 2016, 53: 1-40 CrossRef Google Scholar

[3] Py X, Olives R, Mauran S. Paraffin/porous-graphite-matrix composite as a high and constant power thermal storage material. Int J Heat Mass Transfer, 2001, 44: 2727-2737 CrossRef Google Scholar

[4] Zhao C Y, Wu Z G. Heat transfer enhancement of high temperature thermal energy storage using metal foams and expanded graphite. Sol Energy Mater Sol Cells, 2011, 95: 636-643 CrossRef Google Scholar

[5] Sarı A, Karaipekli A. Thermal conductivity and latent heat thermal energy storage characteristics of paraffin/expanded graphite composite as phase change material. Appl Thermal Eng, 2007, 27: 1271-1277 CrossRef Google Scholar

[6] Agyenim F, Eames P, Smyth M. A comparison of heat transfer enhancement in a medium temperature thermal energy storage heat exchanger using fins. Sol Energy, 2009, 83: 1509-1520 CrossRef ADS Google Scholar

[7] Zhu L, Yu J. Optimization of heat sink of thermoelectric cooler using entropy generation analysis. Int J Thermal Sci, 2017, 118: 168-175 CrossRef Google Scholar

[8] Kim D K. Thermal optimization of plate-fin heat sinks with fins of variable thickness under natural convection. Int J Heat Mass Transfer, 2012, 55: 752-761 CrossRef Google Scholar

[9] Huang S, Zhao J, Gong L, et al. Thermal performance and structure optimization for slotted microchannel heat sink. Appl Thermal Eng, 2017, 115: 1266-1276 CrossRef Google Scholar

[10] José S M, Aurélio L A, Victor F C, et al. Material distribution and sizing optimization of functionally graded plate-shell structures. Compos Pt B-Eng, 2018, 142: 263−272. Google Scholar

[11] Gkaragkounis K T, Papoutsis-Kiachagias E M, Giannakoglou K C. The continuous adjoint method for shape optimization in conjugate heat transfer problems with turbulent incompressible flows. Appl Thermal Eng, 2018, 140: 351-362 CrossRef Google Scholar

[12] Zeng S, Kanargi B, Lee P S. Experimental and numerical investigation of a mini channel forced air heat sink designed by topology optimization. Int J Heat Mass Transfer, 2018, 121: 663-679 CrossRef Google Scholar

[13] Allaire G E, Bonnetier E, Francfort G, et al. Shape optimization by the homogenization method. Numer Mathem, 1997, 76: 27-68 CrossRef Google Scholar

[14] Bendsøe M P, Kikuchi N. Generating optimal topologies in structural design using a homogenization method. Comput Methods Appl Mech Eng, 1988, 71: 197-224 CrossRef ADS Google Scholar

[15] Kunakote T, Bureerat S. Multi-objective topology optimization using evolutionary algorithms. Eng Optimization, 2011, 43: 541-557 CrossRef Google Scholar

[16] Asadpoure A, Tootkaboni M, Guest J K. Robust topology optimization of structures with uncertainties in stiffness– Application to truss structures. Comput Struct, 2011, 89: 1131-1141 CrossRef Google Scholar

[17] Eschenauer H A, Olhoff N. Topology optimization of continuum structures: A review. Appl Mech Rev, 2001, 54: 1453−1457. Google Scholar

[18] Sigmund O, Petersson J. Numerical instabilities in topology optimization: A survey on procedures dealing with checkerboards, mesh-dependencies and local minima. Struct Optimization, 1998, 16: 68-75 CrossRef Google Scholar

[19] Andreassen E, Clausen A, Schevenels M, et al. Efficient topology optimization in MATLAB using 88 lines of code. Struct Multidisc Optim, 2011, 43: 1-16 CrossRef Google Scholar

[20] Jang D, Yu S H, Lee K S. Multidisciplinary optimization of a pin-fin radial heat sink for LED lighting applications. Int J Heat Mass Transfer, 2012, 55: 515-521 CrossRef Google Scholar

[21] Alexandersen J, Sigmund O, Aage N. Large scale three-dimensional topology optimisation of heat sinks cooled by natural convection. Int J Heat Mass Transfer, 2016, 100: 876-891 CrossRef Google Scholar

[22] Haslinger J, Hillebrand A, Kärkkäinen T, et al. Optimization of conducting structures by using the homogenization method. Struct Multidiscip Optim, 2002, 24: 125-140 CrossRef Google Scholar

[23] Boichot R, Fan Y. A genetic algorithm for topology optimization of area-to-point heat conduction problem. Int J Thermal Sci, 2016, 108: 209-217 CrossRef Google Scholar

[24] Cui T F, Ding X H, Hou L Y. Topology optimization design on heat transfer structure based on density method (in Chinese). J Univ Shanghai Sci Technol, 2014, (6): 548−555 [崔天福, 丁晓红, 侯丽园. 基于密度法的传热结构拓扑优化设计. 上海理工大学学报, 2014, (6): 548−555]. Google Scholar

[25] Zhou M, Rozvany G I N. The COC algorithm, Part II: Topological, geometrical and generalized shape optimization. Comput Methods Appl Mech Eng, 1991, 89: 309-336 CrossRef ADS Google Scholar

[26] Bendsøe M P. Optimal shape design as a material distribution problem. Struct Optim, 1989, 1: 193-202 CrossRef Google Scholar

[27] Zhang Y Q, Luo Z, Chen L P, et al. Multi-stiffness topology optimization design based on MMA (in Chinese). Acta Astronaut Sin, 2006, 27: 1209−1216 [张云清, 罗震, 陈立平, 等. 基于移动渐近线方法的结构多刚度拓扑优化设计. 航空学报, 2006, 27: 1209−1216]. Google Scholar

[28] Svanberg K. A class of globally convergent optimization methods based on conservative convex separable approximations. SIAM J Optim, 2002, 12: 555-573 CrossRef Google Scholar

[29] Lazarov B S, Sigmund O. Filters in topology optimization based on Helmholtz-type differential equations. Int J Numer Meth Engng, 2011, 86: 765-781 CrossRef ADS Google Scholar

Copyright 2020 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备18024590号-1