TY  - JOUR
AU  - Vencl, Aleksandar
AU  - Svoboda, Petr
AU  - Klančnik, Simon
AU  - But, Adrian
AU  - Vorkapić, Miloš
AU  - Harničárová, Marta
AU  - Stojanović, Blaža
PY  - 2023
UR  - https://www.mdpi.com/2075-4442/11/1/24
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/7339
AB  - Three different and very small amounts of alumina (0.2, 0.3 and 0.5 wt. %) in two sizes (approx. 25 and 100 nm) were used to enhance the wear characteristics of ZA-27 alloy-based nanocomposites. Production was realised through mechanical alloying in pre-processing and compocasting processes. Wear tests were under lubricated sliding conditions on a block-on-disc tribometer, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and a sliding distance of 1000 m. Experimental results were analysed by applying the response surface methodology (RSM) and a suitable mathematical model for the wear rate of tested nanocomposites was developed. Appropriate wear maps were constructed and the wear mechanism is discussed in this paper. The accuracy of the prediction was evaluated with the use of an artificial neural network (ANN). The architecture of the used ANN was 4-5-1 and the obtained overall regression coefficient was 0.98729. The comparison of the predicting methods showed that ANN is more efficient in predicting wear.
T2  - Lubricants
T1  - Influence of Al2O3 nanoparticles addition in ZA-27 alloy-based nanocomposites and soft computing prediction
IS  - 1
SP  - 24
VL  - 11
DO  - 10.3390/lubricants11010024
ER  - 

@article{
author = "Vencl, Aleksandar and Svoboda, Petr and Klančnik, Simon and But, Adrian and Vorkapić, Miloš and Harničárová, Marta and Stojanović, Blaža",
year = "2023",
abstract = "Three different and very small amounts of alumina (0.2, 0.3 and 0.5 wt. %) in two sizes (approx. 25 and 100 nm) were used to enhance the wear characteristics of ZA-27 alloy-based nanocomposites. Production was realised through mechanical alloying in pre-processing and compocasting processes. Wear tests were under lubricated sliding conditions on a block-on-disc tribometer, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and a sliding distance of 1000 m. Experimental results were analysed by applying the response surface methodology (RSM) and a suitable mathematical model for the wear rate of tested nanocomposites was developed. Appropriate wear maps were constructed and the wear mechanism is discussed in this paper. The accuracy of the prediction was evaluated with the use of an artificial neural network (ANN). The architecture of the used ANN was 4-5-1 and the obtained overall regression coefficient was 0.98729. The comparison of the predicting methods showed that ANN is more efficient in predicting wear.",
journal = "Lubricants",
title = "Influence of Al2O3 nanoparticles addition in ZA-27 alloy-based nanocomposites and soft computing prediction",
number = "1",
pages = "24",
volume = "11",
doi = "10.3390/lubricants11010024"
}

Vencl, A., Svoboda, P., Klančnik, S., But, A., Vorkapić, M., Harničárová, M.,& Stojanović, B.. (2023). Influence of Al2O3 nanoparticles addition in ZA-27 alloy-based nanocomposites and soft computing prediction. in Lubricants, 11(1), 24.
https://doi.org/10.3390/lubricants11010024

Vencl A, Svoboda P, Klančnik S, But A, Vorkapić M, Harničárová M, Stojanović B. Influence of Al2O3 nanoparticles addition in ZA-27 alloy-based nanocomposites and soft computing prediction. in Lubricants. 2023;11(1):24.
doi:10.3390/lubricants11010024 .

Vencl, Aleksandar, Svoboda, Petr, Klančnik, Simon, But, Adrian, Vorkapić, Miloš, Harničárová, Marta, Stojanović, Blaža, "Influence of Al2O3 nanoparticles addition in ZA-27 alloy-based nanocomposites and soft computing prediction" in Lubricants, 11, no. 1 (2023):24,
https://doi.org/10.3390/lubricants11010024 . .

TY  - JOUR
AU  - Vencl, Aleksandar
AU  - Stojanović, Blaža
AU  - Gojković, Ranka
AU  - Klančnik, Simon
AU  - Czifra, Árpád
AU  - Jakimovska, Kristina
AU  - Harničárová, Marta
PY  - 2022
UR  - https://www.tribomat.net/archive/2022/2022-03/TM-2022-03-02.pdf
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4286
AB  - The objective of this work was to investigate the influence of the addition of a small amount of SiC nanoparticles on the mechanical characteristics and wear resistance of ZA-27 alloy. The ZA-27 alloy-based nanocomposites were produced by a relatively cheap compocasting process preceded by mechanical alloying. Reinforcing elements were the silicon carbide (SiC) nanoparticles with an average size lower than 50 nm and in very small amounts of 0.2, 0.3 and 0.5 wt. %. Wear tests were realized on a block-on-disc tribometer under lubricated sliding conditions, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and a sliding distance of 1000 m. Optimisation of the SiC amount was performed by applying the Taguchi method, showing that the SiC amount of 0.5 wt. % is optimal for the given testing conditions. Prediction of the results and wear maps were also conducted. The analysis of variance showed that the SiC amount has the greatest influence on wear rate (70.8 %), followed by the normal load (19.8 %), and the sliding speed (3.9 %), while the influences of all interactions between these factors did not have any significant influence.
PB  - Balkan Scientific Centre
T2  - Tribology and Materials
T1  - Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method
EP  - 105
IS  - 3
SP  - 96
VL  - 1
DO  - 10.46793/tribomat.2022.014
ER  - 

@article{
author = "Vencl, Aleksandar and Stojanović, Blaža and Gojković, Ranka and Klančnik, Simon and Czifra, Árpád and Jakimovska, Kristina and Harničárová, Marta",
year = "2022",
abstract = "The objective of this work was to investigate the influence of the addition of a small amount of SiC nanoparticles on the mechanical characteristics and wear resistance of ZA-27 alloy. The ZA-27 alloy-based nanocomposites were produced by a relatively cheap compocasting process preceded by mechanical alloying. Reinforcing elements were the silicon carbide (SiC) nanoparticles with an average size lower than 50 nm and in very small amounts of 0.2, 0.3 and 0.5 wt. %. Wear tests were realized on a block-on-disc tribometer under lubricated sliding conditions, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and a sliding distance of 1000 m. Optimisation of the SiC amount was performed by applying the Taguchi method, showing that the SiC amount of 0.5 wt. % is optimal for the given testing conditions. Prediction of the results and wear maps were also conducted. The analysis of variance showed that the SiC amount has the greatest influence on wear rate (70.8 %), followed by the normal load (19.8 %), and the sliding speed (3.9 %), while the influences of all interactions between these factors did not have any significant influence.",
publisher = "Balkan Scientific Centre",
journal = "Tribology and Materials",
title = "Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method",
pages = "105-96",
number = "3",
volume = "1",
doi = "10.46793/tribomat.2022.014"
}

Vencl, A., Stojanović, B., Gojković, R., Klančnik, S., Czifra, Á., Jakimovska, K.,& Harničárová, M.. (2022). Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method. in Tribology and Materials
Balkan Scientific Centre., 1(3), 96-105.
https://doi.org/10.46793/tribomat.2022.014

Vencl A, Stojanović B, Gojković R, Klančnik S, Czifra Á, Jakimovska K, Harničárová M. Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method. in Tribology and Materials. 2022;1(3):96-105.
doi:10.46793/tribomat.2022.014 .

Vencl, Aleksandar, Stojanović, Blaža, Gojković, Ranka, Klančnik, Simon, Czifra, Árpád, Jakimovska, Kristina, Harničárová, Marta, "Enhancing of ZA-27 alloy wear characteristics by addition of small amount of SiC nanoparticles and its optimisation applying Taguchi method" in Tribology and Materials, 1, no. 3 (2022):96-105,
https://doi.org/10.46793/tribomat.2022.014 . .