Analysis of Entropy Generation and Multi-Parameter Optimization of Flying-Wing Fins in Condensers

This study investigates the application of flying-wing fins (FWF) in refrigerator condensers. Compared with conventional condensers, FWF structures eliminate contact thermal resistance and reduce refrigerator energy consumption by 6.06%. The heat transfer mechanism, entropy generation characteristics, and parameter optimization of FWF are comprehensively analyzed. Results show that the local convective heat transfer coefficient decreases along the flow direction, with the maximum value in the wave-crest region and the minimum in the wave-trough region. The Colburn j factor is positively correlated with fin pitch (Fp) and amplitude (A), but negatively correlated with fin length (H) and thickness (Ft). The fanning friction factor (f) increases with A and Ft, decreases with H, and first increases then decreases with Fp. Fin height (Fh) exerts minimal influence on j and f factors. Thermal entropy generation and flow entropy generation are negatively correlated with Fp and positively with other parameters. The Bejan number remains around 0.9, indicating that thermal entropy generation dominates total entropy generation. Finally, the contribution ratios of key parameters to j and f factors are quantified. These findings clarify the heat transfer behavior of FWF and provide a theoretical foundation for designing high-efficiency flying-wing condensers with reduced energy consumption.

Authors

Institutions

Publication Details

Journal
Heat Transfer Engineering
Published
2026-07-25
DOI
https://doi.org/10.1080/01457632.2026.2705643
Primary Topic
Heat Transfer and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Entropy Generation and Multi-Parameter Optimization of Flying-Wing Fins in Condensers

Zipei Zhang, Pengcheng Zheng, Wenqiang Suo, Shiqun Liu et al.
Heat Transfer Engineering
Heat Transfer and Optimization
article

Analysis of Entropy Generation and Multi-Parameter Optimization of Flying-Wing Fins in Condensers

Zipei Zhang, Pengcheng Zheng, Wenqiang Suo, Shiqun Liu, P Yang, Hui Chen, Yingwen Liu, Chunbo Zhou
article en

Abstract

This study investigates the application of flying-wing fins (FWF) in refrigerator condensers. Compared with conventional condensers, FWF structures eliminate contact thermal resistance and reduce refrigerator energy consumption by 6.06%. The heat transfer mechanism, entropy generation characteristics, and parameter optimization of FWF are comprehensively analyzed. Results show that the local convective heat transfer coefficient decreases along the flow direction, with the maximum value in the wave-crest region and the minimum in the wave-trough region. The Colburn j factor is positively correlated with fin pitch (Fp) and amplitude (A), but negatively correlated with fin length (H) and thickness (Ft). The fanning friction factor (f) increases with A and Ft, decreases with H, and first increases then decreases with Fp. Fin height (Fh) exerts minimal influence on j and f factors. Thermal entropy generation and flow entropy generation are negatively correlated with Fp and positively with other parameters. The Bejan number remains around 0.9, indicating that thermal entropy generation dominates total entropy generation. Finally, the contribution ratios of key parameters to j and f factors are quantified. These findings clarify the heat transfer behavior of FWF and provide a theoretical foundation for designing high-efficiency flying-wing condensers with reduced energy consumption.

Heat Transfer Engineering
Suzhou Thermal Engineering Research Institute (CN), China Automotive Engineering Research Institute (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 16%
Heat Transfer and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.