Study of developing a condensation heat transfer coefficient and pressure drop model for whole reduced pressure ranges

This study involves the collection of data from 10 different articles to develop experimental-based models for predicting the condensation heat transfer and the frictional pressure drop. The dataset comprises a total of 1168 condensation heat transfer coefficients and 792 frictional pressure drop da...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International Journal of Air-Conditioning and Refrigeration 2024, 32(1), , pp.1-9
Hauptverfasser: Ajayi, Abiola Samuel, Kim, Sugyeong, Yun, Rin
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This study involves the collection of data from 10 different articles to develop experimental-based models for predicting the condensation heat transfer and the frictional pressure drop. The dataset comprises a total of 1168 condensation heat transfer coefficients and 792 frictional pressure drop data. The applied operating range considered is within the reduced pressure of 0.1–0.95, mass flux ranging from 75 to 700 kg/m 2 s, and an inner diameter between 3.4 and 12.5 mm. We developed the models for the condensation heat transfer coefficient based on Akers et al.’s model, whose parameters are the Prandtl number, density ratio, vapor quality, and mass flux. The total error for the condensation heat transfer coefficient is ± 22.6%. The data is further categorized into two groups of the reduced pressure: P r   0.5 with an error of ± 18.9%. The frictional pressure drop models were developed based on the three different ranges of the reduced pressure. The utilized non-dimensionless parameters were the two-phase multiplier (Φ lo 2 ), the Bond number (Bo), the Weber number (We), and the Martinelli parameter (X tt ), along with the regression coefficients. Regarding the frictional pressure drop correlation, the total error is ± 32.7%, and the data is divided into three segments: P r  
ISSN:2010-1333
2010-1325
2010-1333
DOI:10.1007/s44189-024-00060-0