| dc.creator |
KÜÇÜKSİLLE, Ecir Uğur |
|
| dc.creator |
Selbas, Reşat |
|
| dc.creator |
SENCAN, Arzu |
|
| dc.date |
2011-01-31T22:00:00Z |
|
| dc.date.accessioned |
2020-10-06T10:33:19Z |
|
| dc.date.available |
2020-10-06T10:33:19Z |
|
| dc.identifier |
7b58aed7-7e3e-487e-a19e-4d56b8cc5345 |
|
| dc.identifier |
10.1016/j.enconman.2010.08.009 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/7b58aed7-7e3e-487e-a19e-4d56b8cc5345/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/64208 |
|
| dc.description |
The analysis of vapor compression refrigeration systems requires the availability of simple and efficient mathematical formulations for the determination of thermodynamic properties of refrigerants. The aim of this study is to determine thermodynamic properties as enthalpy, entropy and specific volume of alternative refrigerants using data mining method. Alternative refrigerants used in the study are R134a, R404a. R407c and R410a. The results obtained from data mining have been compared to actual data from the literature. The study shows that the data mining methodology is successfully applicable to determine enthalpy, entropy and specific volume values for any temperature and pressure of refrigerants. Therefore, computation time reduces and simulation of vapor compression refrigeration systems is fairly facilitated. (C) 2010 Elsevier Ltd. All rights reserved. |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Prediction of thermodynamic properties of refrigerants using data mining |
|
| dc.type |
info:eu-repo/semantics/article |
|