Study on Phase-Shift Mechanism and Kriging-Based Global Optimization of the Active Displacer Pulse Tube Refrigerators

被引:1
作者
Geng, Zongtao [1 ]
Shao, Wei [1 ]
Cui, Zheng [1 ,2 ]
Zheng, Chen [2 ]
机构
[1] Shandong Univ, Inst Thermal Sci & Technol, Jinan 250061, Peoples R China
[2] Shandong Inst Adv Technol, Jinan 250100, Peoples R China
关键词
active displacer; pulse tube refrigerator; Kriging model; sensitivity analysis; CRYOCOOLER;
D O I
10.3390/en16114263
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Pulse tube refrigerators are widely used in certain special fields, such as aerospace, due to their unique advantages. Compared to a conventional phase shifter, the active displacer helps to achieve a higher cooling efficiency for pulse tube refrigerators. At present, the displacer is mainly studied by one-dimensional simulation, and the optimization method is not perfect due to its poor accuracy, which is not conducive to obtaining a better performance. Based on the current status of displacer research, phase-shift mechanisms of inertance tube pulse tube refrigerators and active displacer pulse tube refrigerators were firstly studied comparatively by multidimensional simulation, and then we determined the crucial effect properties that lead to a better cooling performance for the active displacer pulse tube refrigerator at different cooling temperatures. Finally, an efficient optimization method combining the Kriging model and genetic algorithm is proposed to further improve the cooling performance of the active displacer pulse tube refrigerator. The results show that the active displacer substantially improves the cooling performance compared to the inertance tube mainly by increasing the PV power and enthalpy flow in the pulse tube. The Kriging agent models of active displacer pulse tube refrigerator achieve 98.2%, 98.31%, 97.86%, and 97.32% prediction accuracy for no-load temperature, cooling capacity, coefficient of performance, and total input PV power, respectively. After optimization, the no-load temperature is minimally optimized for a 23.68% reduction compared to the initial one with a relatively high efficiency, and the founded optimization methods can also be weighted for multiple objectives, according to actual needs.
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页数:20
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