Viscosity modeling of nano-modified SAE50 engine oil using RSM and ANN methods
Author:
Publisher
Elsevier BV
Subject
Condensed Matter Physics,General Chemical Engineering,Atomic and Molecular Physics, and Optics
Reference24 articles.
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1. Dynamic viscosity prediction of nanofluids using artificial neural network (ANN) and genetic algorithm (GA);Journal of the Brazilian Society of Mechanical Sciences and Engineering;2024-06-05
2. Determining the best structure for an artificial neural network to model the dynamic viscosity of MWCNT-ZnO (25:75)/SAE 10W40 oil nano-lubricant;Materials Today Communications;2024-03
3. Investigation of different transfer functions for modeling the dynamic viscosity of hybrid nanolubricant containing MWCNTs and MgO nanoparticles using the response surface methodology (RSM);Tribology International;2023-05
4. A comparative study of RSM regression models to achieve the most optimal rheological behavior of MWCNT/SiO2(50−50)-SAE40 hybrid nanofluid and provide optimal lubrication conditions during the start of movement;Tribology International;2023-01
5. Influence of different parameters on the rheological behavior MWCNT (30%)-TiO2 (70%) / SAE50 hybrid nano-lubricant using of response surface methodology and artificial neural network methods;Arabian Journal of Chemistry;2022-12
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