刘文巍， 石欣琳， 付景文， 黄云

中国科学院 过程工程研究所，介科学与过程工程全国重点实验室， 北京 100190；中国科学院大学 化学工程学院， 北京100049

引用格式：

刘文巍， 石欣琳， 付景文， 等. 球壳形复合相变材料熔化特性的数值模拟［J］. 中国粉体技术， 2026， 32（5）： 1-12.

Liu Wenwei， Shi Xinlin， Fu Jingwen， et al. Numerical simulation of melting performance of core-shell composite phase change materials［J］. China Powder Science and Technology， 2026， 32（5）： 1-12.

DOI：10.13732/j.issn.1008-5548.2026.05.004

收稿日期： 2026-07-21， 修回日期： 2026-08-18， 上线日期： 2026-08-31。

基金项目： 国家科技重大专项，编号 ：2026ZD1702301；中国科学院前沿战略科技A类先导专项课题，编号：XDA0400102。

第一作者： 刘文巍（1990—），男，研究员，博士，博士生导师，研究方向为颗粒动力学，多相流，储热技术。E-mail：liuwenwei@ipe.ac.cn。

摘要： 【目的】 探究高导热球壳材料厚度、物性参数及颗粒堆积结构对于球壳形复合相变材料熔化过程的影响，实现对颗粒堆积床储热系统的结构优化。 【方法】 采用格子玻尔兹曼方法，建立传热流体-导热球壳-相变材料的多组分传热数学和物理模型，采用第一类边界条件，分别探究无量纲球壳厚度、导热系数、比热容和颗粒堆积密度对于相变材料熔化速率的影响。 【结果】 相变材料熔化时间随着球壳厚度增大而线性下降；球壳相对厚度相同时，相变材料体积越大，熔化越慢；增大球壳材料的导热系数，并减小其比热容能够加快相变材料的熔化；颗粒床的熔化时间随着堆积密度的增大而呈指数下降。 【结论】 添加高导热球壳能够有效缩短相变材料的熔化时间，球壳的导热系数应至少为相变材料导热系数的10倍以上，采用随机堆积形成的颗粒床结构能够有效的提升熔化性能，进一步增大堆积密度获得的收益较为有限。

关键词： 相变材料； 储热； 颗粒； 随机堆积； 格子玻尔兹曼方法

Abstract 

Objective The packed bed with core-shell particles provides an effective approach for improving the release efficiency of high-temperature thermal energy storage systems using phase change materials （PCMs）. However， the comprehensive understanding of the heat transfer mechanisms of composite particles remains unclear， which limits the optimization of packed bed structures. To explore the effects of shell thickness， thermal properties， and packing structure on the melting performance of spherical core-shell composite PCMs， this study performs numerical simulations of the melting processes of single particles and particle beds generated by random packing.

Methods The lattice Boltzmann method with double distribution functions was employed to solve the fluid flow and PCM enthalpy. The simulation domain was set as a square with dimensions of 200 × 200 lattice units. The four boundaries were set as no-slip walls. The left and right walls were set to constant temperatures and ， respectively， while the top and bottom walls were set as adiabatic. The domain was filled with randomly packed particles， where each particle was composed of a PCM core and a shell material with high thermal conductivity. The PCM was selected as NaNO3， and the shell materials included Al， graphite， and multi-wall nanotubes （MWNTs）. Two series of simulations were carried out. The first series involved single-particle melting simulations with a PCM size of lattice units and a dimensionless shell thickness of . The second series involved the melting of random packings with a packing density of .

Results and Discussion For the melting of single core-shell particles， it was found that the complete melting time decreased linearly with increasing shell thickness. This was because the thicker shell enlarged the heat transfer area between the shell and the fluid in the domain. However， the linear slope decreased with the decrease of PCM volume， indicating that the enhancement effect of the shell became more prominent for larger volumes of PCM. Furthermore， the physical properties of the shell material had a significant effect on the melting process. Among the three shell materials considered in this study， graphite exhibited the best performance due to its lower heat capacity， followed by Al and MWNTs. This was because the thermal conductivities of these three shell materials were sufficiently high， so that the thermal resistance inside the shell could be neglected and heat transfer was instantaneous. The thermal energy from the fluid was first transferred to heat the shell， which was determined by its heat capacity. As a result， less thermal energy was required to heat the graphite shell， leading to a faster PCM melting rate under the same thermal input. By artificially tuning the thermal conductivity of the shell material， it was found that the PCM melting was remarkably suppressed when the thermal conductivity of the shell material was reduced to 1/1 000 of the original value. Moreover， the results suggested that the thermal conductivity of the shell material should be at least 10 times higher than that of the PCM， where little improvement was achieved with further increases in thermal conductivity. For the melting of the packed bed， it was observed that the complete melting time decreased exponentially with increasing packing density， which was attributed to the formation of a highly connected network between particle contacts. The packed bed structure formed by random packing was sufficient to achieve an acceptable melting rate， and further increasing the packing density yielded limited benefits.

Conclusion This study provides a systematic numerical investigation of the melting performance of composite PCMs with core-shell structures at the microscopic particle scale， which can be used to guide material design， parameter selection， and packed bed structure optimization. The results demonstrate that adding a high-thermal-conductivity shell can effectively enhance the melting rate of PCMs. However， it reduces the PCM volume， which leads to a decrease in the total heat storage capacity. From the perspective of practical applications， a trade-off needs to be achieved between heat storage capacity and melting rate. Therefore， it is necessary to establish a more comprehensive and integrated evaluation indicator in future studies.

Keywords： phase change material； thermal energy storage； particle； random packing； lattice Boltzmann method

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