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    仿生树形流道蓄冷板充冷过程的数值仿真研究

    Numerical simulation study on the cooling process of bionic tree-shaped cold storage plate

    • 摘要: 随着冷链物流行业的迅猛发展和节能减排需求的持续扩张,相变蓄冷技术已成为研究的热点方向。本文结合强化换热技术中的仿生结构,基于相变材料(Phase Change Material,PCM)冻结过程的热阻主导机制,将树形流道嵌入蓄冷板内来提高相变蓄冷板的储能密度。利用COMSOL仿真软件数值模拟验证了树形流道在流动与传热方面的优势,并分析了不同冷却工况下蓄冷板的储能速率、相界面动态变化以及温度分布特性。结果表明,树形结构本身具有较好的流阻特性,通过多级分形结构使流体形成涡旋来减薄热边界层,以及在蓄冷板内形成多区分向传热单元来提高储能效率。增大载冷剂(Heat Transfer Fluid,HTF)流量并降低其温度可提高蓄冷板储能速率、减小死区占比,但会使相变材料冻结速率差异增大、蓄冷板表面均温性变差。综合储能速率与温度分布特性,在最佳冷却工况为1.73 L/min、−26 ℃时,蓄冷板的蓄冷能体积速率可达10.98 kW∙m−3,温度标准偏差在2 K以内。

       

      Abstract: With the rapid development of the cold chain logistics industry and the continuous expansion of the demand for energy conservation and emission reduction, phase change cold storage technology has become a hot research direction. This paper integrated bionic structures into advanced heat transfer technology, in terms of the thermal resistance-dominated mechanism of phase change material (PCM) freezing process, embedded tree-shaped channels into the cold storage plate to enhance its energy storage density. A numerical model was established using COMSOL to verify the advantages of this tree-shaped channels for the flow and heat transfer characteristics. Energy storage rate, dynamic changes of the phase interface, and the temperature distribution within the cold storage plate were analyzed under different cooling conditions. The results indicate that the tree-shaped structure inherently exhibits favorable flow resistance characteristics. By employing a multi-stage fractal design, the fluid generates vortices that thin the thermal boundary layer. Additionally, the structure creates zoned multi-directional heat transfer units within the cold storage plate, thereby enhancing energy storage efficiency. Higher heat transfer fluid (HTF) flow rate and lower temperature can enhance energy storage rate and reduce dead zones proportion, but they also increase phase change material freezing rate variation and worsen surface temperature uniformity. Considering the energy storage rate and temperature distribution, an optimal cooling condition is identified at 1.73 L/min and -26 °C, yielding volumetric cold energy rate of 10.98 kW·m−3, and temperature standard deviation within 2 K.

       

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