Thermal conductivity prediction of pure refrigerants and mixtures based on entropy-scaling concept

Kang, Kai; Li, Xueli; Gu, Yaxiu; Wang, Xiaopo

doi:10.1016/j.molliq.2022.120568

Cited by 5 publications

(1 citation statement)

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“…Since the thermal conductivity of liquid refrigerants currently cannot be accurately estimated using rigorous theory [8], various semi-empirical and empirical models for calculating their liquid λ were developed. Some of the main models are as follows: extended corresponding states models used in REFPROP 10.0 [9]; models based on the entropy-scaling concept [10][11][12][13]; models based on equations of state [14,15]; semi-empirical correlations that describe the λ dependence on temperature [16][17][18]; and empirical equations that present specific fixed parameters [19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Modeling Liquid Thermal Conductivity of Low-GWP Refrigerants Using Neural Networks

2022

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The thermal conductivity of refrigerants is needed to optimize and design the main components of HVAC&R systems. Consequently, it is crucial to have reliable models that are able to accurately calculate the temperature and pressure dependence of the thermal conductivity of refrigerants. For the first time, this study presents a neural network specifically developed to calculate the liquid thermal conductivity of various low-GWP-based refrigerants. In detail, a feed-forward network algorithm with 5 input parameters (i.e., the reduced temperature, the critical pressure, the acentric factor, the molecular weight, and the reduced pressure) and 1 hidden layer was applied to a large dataset of 3404 experimental points for 7 halogenated alkene refrigerants. The results provided by the neural network algorithm were very satisfactory, achieving an absolute average relative deviation of 0.389% with a maximum absolute relative deviation of 6.074% over the entire dataset. In addition, the neural network ensured lower deviations between the experimental and calculated data than that produced using different literature models, proving its accuracy for the liquid thermal conductivity of the studied refrigerants.

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