Numerical modelling of thermal processes in Chinese cabbage cold storage chamber using variable turbulence models

Kamil Leszek Śmierciew , Mirosława Kołodziejczyk , Jerzy Gagan , Dariusz Butrymowicz


Losses of stored fruits and vegetables may occur mainly due to non-uniformity of the environmental conditions. Cooling air flow pattern in the cold storage chamber strongly depends on the turbulence model applied. In modelling of mechanical ventilation standard k-ε model turbulence models is used routinely because of good convergence. However, this model is not able to predict the flow rate of the air stream and is unable to reproduce the Coanda effect. In the paper the results of numerical modelling of processes in cold storage chamber for vegetables are presented. The RANS turbulence models have been tested to determine the most appropriate ones for the studied configuration. The highest difference of measured and computed temperature in the bulk of vegetables is 0.40 K regardless of the turbulence model. Relative humidity difference varies between 4 and 13%. Tested turbulence models led to overprediction of air temperature and velocity, however the SST k-ω model gives the best results.
Author Kamil Leszek Śmierciew (FME / DMDTE)
Kamil Leszek Śmierciew,,
- Department of Machinery Design and Thermal Engineering
, Mirosława Kołodziejczyk
Mirosława Kołodziejczyk,,
, Jerzy Gagan (FME / DMDTE)
Jerzy Gagan,,
- Department of Machinery Design and Thermal Engineering
, Dariusz Butrymowicz (FME / DMDTE)
Dariusz Butrymowicz,,
- Department of Machinery Design and Thermal Engineering
Publication size in sheets0.5
Book Minea Vasile (eds.): Refrigeration Science and Technology Proceedings: 25th IIR International Congress of Refrigeration, 2019, International Institute of Refrigeration, ISBN 978-2-36215-035-7, 5052 p.
Keywords in Englishrefrigeration, CFD, turbulence, comparison, RANS, vegetables, relative humidity, simulations
Internal identifierROC 19-20
Languageen angielski
Score (nominal)0
Score sourceconferenceList
ScoreMinisterial score = 0.0, 17-01-2020, ChapterFromConference
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