Synthesized CuFe2O4/SiO2 nanocomposites added to water/EG: Evaluation of the thermophysical properties beside sensitivity analysis & EANN

By Arash Karimipour, Seyed Amin Bagherzadeh, Marjan Goodarzi, A. Alnaqi, Mehdi Bahiraei, Mohammad Reza Safaei, Mostafa Safdari Shadloo. International Journal of Heat and Mass Transfer, 2018

141 citations recorded by the source corpus.

Abstract The new nanocomposite material of CuFe2O4 (copper ferrite) nanoparticles coated by SiO2 is synthesized. Then, this newly generated nanocomposite is dispersed in water/ethylene glycol (60:40) to make a new homogeneous nanofluid in order to avoid settling and agglomeration. Through suitable accurate experiments, density, viscosity and electrical conductivity of the mixture are measured at various temperatures and nanoparticles concentrations. Besides we empirical correlations for the same parameters developed via the curve fitting method. To have a better statistical view, the optimization procedure based on the enhanced artificial neural network (EANN), developed at present study, is performed. Furthermore, according to the obtained empirical results, the sensitivity analysis is provided and the margin of deviations is represented for each proposed correlation. Generation, stabilization and measuring the density, viscosity and electrical conductivity of the newly mentioned nanofluid, make present work different from the previous ones in this field. The highest amount of relative electrical conductivity is observed at T = 75 °C and φ = 0.02 (g/mL); however, the case of T = 30 °C and φ = 0.02 (g/mL) represents the maximum value of relative viscosity. Moreover, density is decreased by temperature augmentation, through all cases.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/d291e30267d75b822b729cbcde459868d2e5852d

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Citations in the corpus

A novel comprehensive experimental study concerned synthesizes and prepare liquid paraffin-Fe3O4 mixture to develop models for both thermal conductivity & viscosity: A new approach of GMDH type of neural network (2019, background): “[51] concerned the synthesized CuFe2O4/SiO2 nanocomposites through the water/EG.”