Influence of Al2O3 Nanoparticles Addition in ZA-27 Alloy-Based Nanocomposites and Soft Computing Prediction
Authors
Vencl, AleksandarSvoboda, Petr
Klančnik, Simon
But, Adrian
Vorkapić, Miloš
Harničarova, Marta
Stojanović, Blaža
Article (Published version)
Metadata
Show full item recordAbstract
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 method...s showed that ANN is more efficient in predicting wear.
Keywords:
ZA-27 alloy / Al2O3 nanoparticles / nanocomposites / wear / response surface methodology / artificial neural networkSource:
Lubricants, 2023, 11, 1, 24-Publisher:
- Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)
Funding / projects:
- Ministry of Science, Technological Development and Innovation of the Republic of Serbia, institutional funding - 200105 (University of Belgrade, Faculty of Mechanical Engineering) (RS-MESTD-inst-2020-200105)
- Development of the tribological micro/nano two component and hybrid selflubricating composites (RS-MESTD-Technological Development (TD or TR)-35021)
- The Ministry of Education, Youth and Sports of the Czech Republic (project FSI-S-20-6443)
- The Slovenian Research Agency ( project BI-BA/21-23-036 )
- The Ministry of Education, Science, Research and Sport of the Slovak Republic (project VEGA 1/0236/21)
- The Republic of Serbia and the Republic of Austria ( project no. 337-00-577/2021-09/16 )
DOI: 10.3390/lubricants11010024
ISSN: 2075-4442
WoS: 000917744500001
Scopus: 2-s2.0-85146793938
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IHTMTY - JOUR AU - Vencl, Aleksandar AU - Svoboda, Petr AU - Klančnik, Simon AU - But, Adrian AU - Vorkapić, Miloš AU - Harničarova, Marta AU - Stojanović, Blaža PY - 2023 UR - https://cer.ihtm.bg.ac.rs/handle/123456789/5643 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. PB - Switzerland : Multidisciplinary Digital Publishing Institute (MDPI) T2 - Lubricants T1 - Influence of Al2O3 Nanoparticles Addition in ZA-27 Alloy-Based Nanocomposites and Soft Computing Prediction VL - 11 IS - 1 SP - 24 DO - 10.3390/lubricants11010024 ER -
@article{ author = "Vencl, Aleksandar and Svoboda, Petr and Klančnik, Simon and But, Adrian and Vorkapić, Miloš and Harničarova, 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.", publisher = "Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)", journal = "Lubricants", title = "Influence of Al2O3 Nanoparticles Addition in ZA-27 Alloy-Based Nanocomposites and Soft Computing Prediction", volume = "11", number = "1", pages = "24", doi = "10.3390/lubricants11010024" }
Vencl, A., Svoboda, P., Klančnik, S., But, A., Vorkapić, M., Harničarova, M.,& Stojanović, B.. (2023). Influence of Al2O3 Nanoparticles Addition in ZA-27 Alloy-Based Nanocomposites and Soft Computing Prediction. in Lubricants Switzerland : Multidisciplinary Digital Publishing Institute (MDPI)., 11(1), 24. https://doi.org/10.3390/lubricants11010024
Vencl A, Svoboda P, Klančnik S, But A, Vorkapić M, Harničarova 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, Harničarova, 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 . .