Configuration Optimization of a Plate Fin Precooler Based on Multi-Objective Grey Wolf Optimizer

Changyin Zhao, Zhe Xu (), Xin Ning (), Min Wang () and Pengyu Jiang
Additional contact information
Changyin Zhao: Postdoctoral Innovation Base, School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China
Zhe Xu: Postdoctoral Innovation Base, School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China
Xin Ning: Postdoctoral Innovation Base, School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China
Min Wang: School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Pengyu Jiang: Postdoctoral Innovation Base, School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China

Energies, 2025, vol. 18, issue 22, 1-21

Abstract: The method of effectiveness-number of heat transfer units (ε-NTU) is adopted to establish a design indicator prediction model for plate fin precooler (PFP), and experimental verification is conducted. The average error between the experimental heat transfer capacity and the calculated heat transfer capacity is 4.65%, and the predicted mass matches the mass computed via the commercial software SolidWorks 2020. This outcome confirms the model’s reliability. An investigation is conducted into the influences of parametric factors, including hot stream flow length, cold stream flow length, hot side number of layers, and hot side fin pitch on the heat transfer capacity and mass of the PFP. To realize the maximization of heat transfer capacity and the minimization of mass, optimization is performed on the four sensitive configuration parameters by leveraging the multi-objective grey wolf optimizer (MOGWO). This optimization can significantly reduce the mass while ensuring the stability of the heat transfer capacity. Three classes of optimal configurations were derived from Pareto optimal points. Compared to the original structure, the selected schemes exhibit an average 2.95% rise in heat transfer capacity and a 10.7% reduction in mass. These findings show that the optimization method proposed in this study is effective and provides valuable guidance for precooler design.

Keywords: plate fin precooler; indicator prediction; configuration parameters; MOGWO (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: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/22/5952/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/22/5952/ (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:18:y:2025:i:22:p:5952-:d:1793088

Access Statistics for this article

Energies is currently edited by Ms. Cassie Shen

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