Multi-Objective Parameter Optimization of Pulse Tube Refrigerator Based on Kriging Metamodel and Non-Dominated Ranking Genetic Algorithms

Hongxiang Zhao, Wei Shao, Zheng Cui () and Chen Zheng ()
Additional contact information
Hongxiang Zhao: Institute of Thermal Science and Technology, Shandong University, Jinan 250061, China
Wei Shao: Institute of Thermal Science and Technology, Shandong University, Jinan 250061, China
Zheng Cui: Institute of Thermal Science and Technology, Shandong University, Jinan 250061, China
Chen Zheng: Shandong Institute of Advanced Technology, Jinan 250100, China

Energies, 2023, vol. 16, issue 6, 1-18

Abstract: Structure parameters have an important influence on the refrigeration performance of pulse tube refrigerators. In this paper, a method combining the Kriging metamodel and Non-Dominated Sorting Genetic Algorithm II (NSGA II) is proposed to optimize the structure of regenerators and pulse tubes to obtain better cooling capacity. Firstly, the Kriging metamodel of the original pulse tube refrigerator CFD model is established to improve the iterative solution efficiency. On this basis, NSGA II was applied to the optimization iteration process to obtain the optimal and worst Pareto front solutions for cooling performance, the heat and mass transfer characteristics of which were further analyzed comparatively to reveal the influence mechanism of the structural parameters. The results show that the Kriging metamodel presents a prediction error of about 2.5%. A 31.24% drop in the minimum cooling temperature and a 31.7% increase in cooling capacity at 120 K are achieved after optimization, and the pressure drop loss at the regenerator and the vortex in the pulse tube caused by the structure parameter changes are the main factors influencing the whole cooling performance of the pulse tube refrigerators. The current study provides a scientific and efficient design method for miniature cryogenic refrigerators.

Keywords: pulse tube; Kriging model; NSGA II; multi-objective optimization; heat and mass transfer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/6/2736/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/6/2736/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:6:p:2736-:d:1097919

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().