Development of simple-to-use predictive models to determine thermal properties of Fe₂O₃/water-ethylene glycol nanofluid

Keyphrases

• Thermal Properties 100%
• Iron Oxide 100%
• Predictive Models 100%
• Nanofluid 100%
• Ethylene Glycol-water 100%
• Genetic Algorithm 75%
• Least Squares Support Vector Machine 75%
• EG-water 75%
• Artificial Neural Network 50%
• Thermal Conductivity 50%
• Mass Ratio 50%
• Thermophysical Properties 50%
• Dynamic Viscosity 50%
• Thermal Dynamics 50%
• Heat Transfer Rate 25%
• Thermal Behavior 25%
• Relative Standard Deviation 25%
• Particle Swarm Optimization 25%
• Support Vector Machine Model 25%
• Nanoparticle Concentration 25%
• Vector Particles 25%

Engineering

• Nanofluid 100%
• Genetic Algorithm 75%
• Least Square 75%
• Support Vector Machine 75%
• Thermal Conductivity 50%
• Dynamic Viscosity 50%
• Artificial Neural Network 50%
• Mass Ratio 50%
• Nanoparticles 25%
• Thermal Behavior 25%
• Dependent Variable 25%
• Particle Swarm Optimization 25%

Chemical Engineering

• Ethylene 100%
• Support Vector Machine 100%
• Thermal Conductivity 66%
• Neural Network 66%
• Nanoparticle 33%