Prediction and modeling of MWCNT/Carbon (60/40)/SAE 10 W 40/SAE 85 W 90(50/50) nanofluid viscosity using artificial neural network (ANN) and self-organizing map (SOM)

• Published in: Journal of thermal analysis and calorimetry Vol. 134; no. 3; pp. 2275 - 2286
• Main Authors: Maddah, Heydar, Aghayari, Reza, Ahmadi, Mohammad Hossein, Rahimzadeh, Mohammad, Ghasemi, Nahid
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2018; Springer Nature B.V
• Subjects: Analytical Chemistry; Artificial neural networks; Automotive engineering; Carbon; Chemistry; Chemistry and Materials Science; Correlation coefficients; Inorganic Chemistry; Mathematical models; Measurement Science and Instrumentation; Multi wall carbon nanotubes; Nanofluids; Nanoparticles; Neural networks; Neurons; Physical Chemistry; Polymer Sciences; Predictions; Self organizing maps; Standard deviation; Viscosity; Viscosity; Nanofluid; Self-organizing map; Artificial neural networks

The present study investigated and predicted the relative viscosity of multiwall carbon nanotube/carbon (60/40)/SAE 10 W 40/(Society of Automotive Engineers) SAE 85 W 90(50/50) at different temperatures and the different volumetric fraction by applying artificial neural networks based on experimenta...