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Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm

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Abstract

The prediction accuracies of the two-phase heat transfer coefficient for the flow in a small channel, which are usually based on the mean absolute error (MAE) between the correlation and experimental data, have remained unsatisfactory. Conventionally, the regression method has been used to determine the correlation that best represents the experimental data. In this paper, an improved heat transfer correlation for the evaporation of propane is developed by applying the genetic algorithm method. A total of 789 data points from 4 sources with circular diameters ranging from 1.0 to 6.0 mm are used to minimise the MAE while searching for the optimum conditions for the suppression factor, S, and convective factor, F, in a selected superposition correlation for two different vapour quality ranges. The optimisation can minimise the MAE at 33% and 25% for Case I and Case II, respectively. The proposed method assists in attaining a precise empirical prediction that fits well with the experimental data.

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Abbreviations

a :

Optimisation variables

Bo :

Boiling number

C :

Chisholm parameter

D :

Diameter (m)

f :

Friction factor

F :

Convective factor

GA :

Genetic algorithm

G :

Mass flux (kg m−2 s−1)

g :

Gravitational acceleration, g = 9.81 m s−2

h :

Heat transfer coefficient (W m−2 K−1)

i :

Enthalpy (J kg−1)

k :

Thermal conductivity (W m−1 K−1)

M :

Molecular weight (kg kmol−1)

MAE :

Mean absolute error

P :

Pressure (Pa)

Pr :

Prandlt number

p r :

Reduced pressure

q :

Heat flux (W m−2)

Re :

Reynolds number

S :

Suppression factor

T sat :

Saturation temperature (°C)

x :

Vapour quality; GA design parameters

X :

Lockhart–Martinelli two-phase parameter

ρ :

Density (kg m−3)

μ :

Viscosity (kg m−1 s−1)

∅:

Two-phase multiplier

f :

liquid

fo :

single-phase liquid

g :

vapour

nb :

nucleate boiling

tp :

two-phase

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Funding

This work was supported by the Fundamental Research Grant Scheme (FRGS), Ministry of Education, Malaysia, under Vot5F070.

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Authors and Affiliations

  1. School of Mechanical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia

    Yushazaziah Mohd-Yunos, Normah Mohd-Ghazali & Maziah Mohamad

  2. Malaysian Institute of Chemical and Bioengineering Technology, Universiti Kuala Lumpur, 78000 Alor Gajah, Melaka, Malaysia

    Yushazaziah Mohd-Yunos

  3. Department of Mechanical Engineering, University of Indonesia, Kampus UI Depok, Depok, 16424, Indonesia

    Agus Sunjarianto Pamitran

  4. Department of Refrigeration and Air Conditioning Engineering, Chonnam National University, San 96-1, Dunduk-Dong, Yeosu, Chonnam, 550-749, Republic of Korea

    Jong-Taek Oh

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  1. Yushazaziah Mohd-Yunos
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Correspondence to Normah Mohd-Ghazali.

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Mohd-Yunos, Y., Mohd-Ghazali, N., Mohamad, M. et al. Improvement of two-phase heat transfer correlation superposition type for propane by genetic algorithm. Heat Mass Transfer 56, 1087–1098 (2020). https://doi.org/10.1007/s00231-019-02776-x

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