Modeling the Thermal Conductivity of Ionic Liquids and Ionanofluids Based on a Group Method of Data Handling and Modified Maxwell Model

被引:57
作者
Atashrouz, Saeid [1 ]
Mozaffarian, Mehrdad [1 ]
Pazuki, Gholamreza [1 ]
机构
[1] Amirkabir Univ Technol, Tehran Polytech, Dept Chem Engn, Tehran, Iran
关键词
NEURAL-NETWORK; CARBON NANOTUBES; ACENTRIC FACTORS; BINARY-MIXTURES; HEAT-TRANSFER; VISCOSITY; EQUILIBRIUM; NANOFLUIDS; PREDICTION; TEMPERATURE;
D O I
10.1021/acs.iecr.5b00932
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The objective of this study is to develop a model to determine the thermal conductivity of pure ionic liquids and ionanofluids. In order to estimate the thermal conductivity of pure ionic liquids, a group method of data handling model is proposed based on 23 ionic liquids corresponding to 216 experimental data points. The average absolute relative deviation for all studied systems was 1.79%, which is a satisfactory degree of accuracy for the proposed model. Furthermore, the Maxwell model is modified to correlate the thermal conductivity of ionanofluids as a function of temperature and volume fraction of nanoparticles. The average absolute relative deviation for this model is 0.61%. Additionally, Maxwell and modified geometric mean (mGM) models are used to evaluate the models that predict the thermal conductivity of ionanofluids. The results show that mGM is more accurate for prediction of thermal conductivity of ionanofluids.
引用
收藏
页码:8600 / 8610
页数:11
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