<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Nano-additives are generally blended with the base lubricant oil, to enhance the lubricant characteristics such as wear, coefficient of friction (CoF), thermal conductivity, density, and flash and fire points of the lubricant. In this research, nano-additives of SiO2, Al2O3 and TiO2 are blended with the base SN500 oil with different proportions of mixture. When these three nanoparticles are used together in base oil, they enhance most of the desirable properties of a lubricant; 27 samples with three different levels of a mixture of nano-additives are identified using factorial design of experiments. The experimental outcomes for the selected three characteristics of interest of density, flash point and fire point are determined. Conducting experiments for ‘n’ number of samples with different proportions of mixture of nano-additives is a cumbersome, expensive and time-consuming process, in order to determine the optimum mix of nano-additives for the desirable level of characteristics of interest. In this research, attempt has been made to apply fuzzy logic to simulate a greater number of samples with different proportions of a mixture of three nano-additives with the respective outcomes of characteristics of three thermophysical properties. Out of the numerous samples simulated using fuzzy logic, the sample with the optimum mix of three nano-additives of SiO2, Al2O3 and TiO2 blended with the base oil is identified for the desirable level of characteristics of interest of density, flash point and fire point. The values of the identified sample are found to be at the desirable level of 0.9008 gm/ml, 231°C and 252°C, respectively.</p>
</abstract>

Nano-additives are generally blended with the base lubricant oil, to enhance the lubricant characteristics such as wear, coefficient of friction (CoF), thermal conductivity, density, and flash and fire points of the lubricant. In this research, nano-additives of SiO2, Al2O3 and TiO2 are blended with the base SN500 oil with different proportions of mixture. When these three nanoparticles are used together in base oil, they enhance most of the desirable properties of a lubricant; 27 samples with three different levels of a mixture of nano-additives are identified using factorial design of experiments. The experimental outcomes for the selected three characteristics of interest of density, flash point and fire point are determined. Conducting experiments for ‘n’ number of samples with different proportions of mixture of nano-additives is a cumbersome, expensive and time-consuming process, in order to determine the optimum mix of nano-additives for the desirable level of characteristics of interest. In this research, attempt has been made to apply fuzzy logic to simulate a greater number of samples with different proportions of a mixture of three nano-additives with the respective outcomes of characteristics of three thermophysical properties. Out of the numerous samples simulated using fuzzy logic, the sample with the optimum mix of three nano-additives of SiO2, Al2O3 and TiO2 blended with the base oil is identified for the desirable level of characteristics of interest of density, flash point and fire point. The values of the identified sample are found to be at the desirable level of 0.9008 gm/ml, 231°C and 252°C, respectively.

Evaluation of Some Thermophysical Properties of SN500 Lubrication Oil Blended with SIO2, AL2O3 and TIO2 Nano-Additives, Using Fuzzy Logic

Acta Mechanica et Automatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Nano-additives are generally blended with the base lubricant oil, to enhance the lubricant characteristics such as wear, coefficient of friction (CoF), thermal...

Evaluation of Some Thermophysical Properties of SN500 Lubrication Oil Blended with SIO2, AL2O3 and TIO2 Nano-Additives, Using Fuzzy Logic

Pubblicato online: 26 giu 2024

Pagine: 352 - 360

Ricevuto: 14 set 2023

Accettato: 06 dic 2023

DOI: https://doi.org/10.2478/ama-2024-0039

Parole chiave
nano-additives, density, flash and fire points, fuzzy logic

© 2024 Sankar E et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Evaluation of Some Thermophysical Properties of SN500 Lubrication Oil Blended with SIO2, AL2O3 and TIO2 Nano-Additives, Using Fuzzy Logic

Pubblicato online: 26 giu 2024

Pagine: 352 - 360

Ricevuto: 14 set 2023

Accettato: 06 dic 2023

DOI: https://doi.org/10.2478/ama-2024-0039

Parole chiavenano-additives, density, flash and fire points, fuzzy logic

© 2024 Sankar E et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
nano-additives, density, flash and fire points, fuzzy logic