Optimized Condition for Pairing of Different Friction Factor and Viscosity Equations for the Frictional Pressure Drop of R22 and R290

Qais Abid Yousif, Normah Mohd-Ghazali, Agus Sunjarianto Pamitran, Yushazaziah Mohd-Yunos

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Accurate prediction of the friction factor and consequently the pressure drop of two-phase flow in small channels is still an issue. Many correlations exist for the determination of the viscosity and the friction factor that appear in the frictional pressure drop and their combination often determined the degree of disagreements between the experimental data and predicted outcomes. Demands for environmentally friendly refrigerants have further posed a challenge to find compatible alternatives with as good a performance as the current coolants. Despite the many available correlations developed to date, many more are studied in effort to reduce the discrepancies. This paper presents the outcomes of a study comparing the optimized conditions when three different viscosity equations are paired with eight different friction factor correlations to minimize the frictional pressure drop. The approach used multi-objective genetic algorithm (MOGA) to assist in selecting the best pairing. Comparison is then completed with available experimental data. The study showed that the Blasius friction factor paired with the Dukler viscosity produced the least percentage difference for R22, while when paired with the McAdams viscosity produced a lower difference for R290, an environmentally friendly refrigerant being considered to replace R22.

Original languageEnglish
Article number1950037
JournalInternational Journal of Air-Conditioning and Refrigeration
DOIs
Publication statusAccepted/In press - 1 Jan 2019

Keywords

  • Friction factor
  • multi-objective genetic algorithm
  • pressure drop
  • two-phase viscosity

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