Performance comparison and analysis of gradient-optimized triply periodic minimal surface heat exchangers based on field synergy principle

被引:0
作者
Zhang, Fengrui [1 ]
Wang, Jiaxuan [1 ]
Qian, Chenyi [1 ]
Shi, Junye [1 ,2 ]
Yu, Binbin [1 ]
Chen, Jiangping [1 ,3 ]
机构
[1] Shanghai Jiao Tong Univ, Inst Refrigerat & Cryogen, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Zhongguancun Res Inst, Shanghai 213300, Peoples R China
[3] Shanghai Engn Res Ctr High Efficient Cooling Syst, Shanghai 200240, Peoples R China
关键词
Triply periodic minimal surfaces; Additive manufacturing; Shell-and-tube heat exchanger; Field synergy principle; Gradient-optimized; PHASE; DESIGN;
D O I
10.1016/j.applthermaleng.2025.126887
中图分类号
O414.1 [热力学];
学科分类号
摘要
With the growing demand for efficient heat exchangers in the power and chemical industries, there is an immediate necessity for the optimization of shell-and-tube heat exchangers. Triply Periodic Minimal Surface (TPMS) structures possess significant potential in the areas of flow and heat transfer, rendering them well-suited for heat exchangers. This study developed heat exchangers utilizing three TPMS-based structures (Gyroid, Diamond, Schwarz) and manufactured heat exchangers using AlSi10Mg material through additive manufacturing. In terms of research methodology, the reliability of the numerical simulations was systematically verified via experimental measurements. The results demonstrate that the Gyroid structure achieves a 78.6 % (Nu/f) enhancement in comprehensive thermofluidic performance compared to the Schwarz structure at the maximum Reynolds number. Based on the Gyroid structure, this study also proposed a gradient-optimized structure (Gradient-Gyroid) for heat exchangers based on the field synergy principle. While maintaining good flow capacity, it increases the disturbance capability to enhance heat transfer, with maximum Nu reaching 260, which is 6.6 % higher than the Gyroid structure. A comparison of comprehensive evaluation indicators shows that it is 63.1 % (Nu/f) higher than the structure before gradient optimization, proving the superior performance of this structure and the great potential of gradient optimization.
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页数:16
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