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

نویسندگان

چکیده

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

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ژورنال

عنوان ژورنال: Applied sciences

سال: 2022

ISSN: ['2076-3417']

DOI: https://doi.org/10.3390/app13010260