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

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.