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Evaluation of some thermophysical properties of sn500 lubrication oil blended with SIO2, AL2O3 and TIO2 nano-additives, using fuzzy logic

100%

Sankar E. , Duraivelu K.

Acta Mechanica et Automatica

2024

tom Vol. 18, no. 2

352--360

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.

Visualization of Fire in Space and Time on the Basis of the Method of Spatial Location of Fire-Dangerous Areas

86%

Нavrys A. , Yakovchuk R. , Pekarska O. , Tur N.

Ecological Engineering & Environmental Technology

2023

tom Vol. 24, iss. 2

28--37

The subject of the study is the forecasting of fires, on the example of Australian events in the winter of 2013, using the spatial location of fire-hazardous areas. To do this, several approaches were used to visualize data in space and time. A temporary map has been created showing the points of fires using a color scheme linked to the date. A series of small multiple visualizations has been developed. A time series has been created in which the regularity of the brightness of points is distributed depending on the date of origin and animated maps that allow you to view data in space and time. In this case, the geographic information system was used as the main tool when working with maps, as it is one of the best ways to process georeferenced data displayed on the map. A space-time cube is displayed, which displays data in 3D format, or rather, fire points, symbolized by the average temperature of the fire (displayed in different colors) in accordance with the day of the month. Finally, clusters of focal points were created using the space-time framework in the ArcGIS software environment. The described results of using the method of spatial location of fire hazardous zones, in addition to the direct task – localization of fire points (fires), this method makes it possible to study patterns in spatial and temporal scales, with the possibility of further visualization of the spatio-temporal cube in 3D format in the ArcScene program, which will allow more efficient predict fire hazardous periods and areas in the study area. The method of spatial location of fire hazardous areas can be used for any investigated area for which there are statistical and spatial data, both for the purpose of localizing fires, and for the purpose of studying patterns in selected space-time scales.