Modeling the effective thermal conductivity of nanofluids using full factorial design analysis
Author:
Affiliation:
1. Department of Process Engineering, Laboratory of Industrial Analysis and Materials Engineering, Faculty of Sciences and Technology; University of Guelma; Guelma Algeria
Publisher
Wiley
Subject
Fluid Flow and Transfer Processes,Condensed Matter Physics
Link
http://onlinelibrary.wiley.com/wol1/doi/10.1002/htj.21524/fullpdf
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3. A novel nonlinear regression model of SVR as a substitute for ANN to predict conductivity of MWCNT-CuO/water hybrid nanofluid based on empirical data;Karimipour;Physica A,2019
4. Appraising influence of COOH-MWCNTs on thermal conductivity of antifreeze using curve fitting and neural network;Ghasemi;Physica A,2019
5. Effects on thermophysical properties of carbon based nanofluids: experimental data, modelling using regression, ANFIS and ANN;Alrashed;Int J Heat Mass Transf,2018
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