Optimizing of Wear Performance on Elevated Temperature of ZrO2 Reinforced AMCs Using Weighted Superposition Attraction Algorithm

Simsek D., Ozyurek D., Ileri E., AKPINAR Ş., Karaoglan D.

JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH, vol.81, no.5, pp.462-474, 2022 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 81 Issue: 5
  • Publication Date: 2022
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aquatic Science & Fisheries Abstracts (ASFA), INSPEC, Directory of Open Access Journals
  • Page Numbers: pp.462-474
  • Keywords: Aluminium matrix composites, Hot Wear, Mechanical alloying, Zirconia reinforced composite, SWARM INTELLIGENCE ALGORITHM, IN-SITU COMPOSITES, OPTIMIZATION, BEHAVIOR, MICROSTRUCTURE, PARAMETERS, WSA
  • Dokuz Eylül University Affiliated: Yes


In the current study, the zirconium oxide (ZrO2) reinforced Aluminium Matrix Composites (AMCs) was designed as a brake lining and produced by mechanical alloying (MA) method. Wear tests of AMCs were performed according to ASTM G-99 at different sliding distance, operating temperatures and load in the range of 53 to 94 m, 20 to 340 degrees C and 10 to 30 N respectively. Optimum wear performance parameters were determined using the Weighted Superposition Attraction (WSA) algorithm. Firstly, to formulize the problem as an optimization problem through the guidance of the regression modelling, an experimental design has been constructed, and the wear tests have been done at different reinforced rates, operating temperature and loads. Secondly, WSA algorithm has been adapted to tackle the formulated optimization problem. According to the results of WSA algorithm, the optimum rate of zirkonium oxide (ZrO2), load and operating temperature was determined as 12%, 206.33 degrees C and 21.20 N respectively while keeping the friction coefficient between 0.15-0.24.