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Erosion rate of AA6082-T6 aluminum alloy subjected to erosive wear determined by the meta-heuristic (SCA) based ANFIS method

  • Serhat Yılmaz

    Assoc. Prof. Dr. Serhat Yılmaz, is currently working in University of Kocaeli, Faculty of Engineering, Department of Electronics and Communications Engineering. He obtained his BSc, MSc and PhD degrees in Kocaeli University. His research interests include the areas of Marine Science and Technology, Control and Systems Engineering and Fuzzy Logic and Engineering Applications.

         , Aygen Ahsen Yıldırım

    MSc Aygen Ahsen Yıldırım, was born in 1993, graduated from Kocaeli University in 2015 with a degree in Mechanical Engineering. She received her MSc degree from Kocaeli University in the same department. She has been working as production engineer in Ford Otosan since 2017. Her research interests include the areas of tribology, automotive and battery technologies.

         and Erol Feyzullahoğlu

    Prof. Dr. Erol Feyzullahoğlu, was born in 1969, is presently working in the Department of Mechanical Engineering, Kocaeli University, Turkey. He obtained his undergraduate and graduate degrees in Mechanical Engineering Department of Yıldız Technical University and his doctoral degree in Mechanical Engineering Department of Kocaeli University. He has lectured in different engineering disciplines including Mechanical Engineering. His research interests include the areas of tribology, wear, machine elements and transport technique.

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Published/Copyright: January 8, 2024
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Materials Testing
From the journal Materials Testing Volume 66 Issue 2

Abstract

AA6082-T6 aluminum alloy is used in different engineering applications. The erosive wear takes places in many machine parts. The prediction of wear amounts for aluminum alloy materials is complicated and nonlinear phenomena. The fuzzy inference systems (FIS) and the artificial neural networks (ANNs) have a series of properties on modeling nonlinear systems. In this study, it was aimed to determine the optimum erosive wear parameters in terms of wear resistance. This study suggests a meta-heuristic (sine–cosine algorithm-SCA) Based ANFIS prediction model for prediction of wear behavior of AA6082-T6 aluminum alloy within various impingement pressure, impact velocity, impingement angle and particle sizes. In this study, a model is developed that determines the optimum erosive wear parameters to achieve the minimum wear rate. The erosion rate-SCA Based ANFIS prediction model extracted reasonable results. Estimation capability has been achieved to 99.81 % by the proposed model.

Keywords: aluminum alloy; erosive wear; ANNs; ANFIS; SCA
Corresponding author: Erol Feyzullahoğlu, Mechanical Engineering Department, Faculty of Engineering, Kocaeli University, 41380 Kocaeli, Türkiye, E-mail:

About the authors

Serhat Yılmaz

Assoc. Prof. Dr. Serhat Yılmaz, is currently working in University of Kocaeli, Faculty of Engineering, Department of Electronics and Communications Engineering. He obtained his BSc, MSc and PhD degrees in Kocaeli University. His research interests include the areas of Marine Science and Technology, Control and Systems Engineering and Fuzzy Logic and Engineering Applications.

Aygen Ahsen Yıldırım

MSc Aygen Ahsen Yıldırım, was born in 1993, graduated from Kocaeli University in 2015 with a degree in Mechanical Engineering. She received her MSc degree from Kocaeli University in the same department. She has been working as production engineer in Ford Otosan since 2017. Her research interests include the areas of tribology, automotive and battery technologies.

Erol Feyzullahoğlu

Prof. Dr. Erol Feyzullahoğlu, was born in 1969, is presently working in the Department of Mechanical Engineering, Kocaeli University, Turkey. He obtained his undergraduate and graduate degrees in Mechanical Engineering Department of Yıldız Technical University and his doctoral degree in Mechanical Engineering Department of Kocaeli University. He has lectured in different engineering disciplines including Mechanical Engineering. His research interests include the areas of tribology, wear, machine elements and transport technique.

  1. Research ethics: Not applicable.

  2. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. The details are presented at the end of the article.

  3. Competing interests: The authors state no conflict of interest.

  4. Research funding: None declared.

  5. Data availability: Not applicable.

Appendix
Figure A1: SCA pseudocode [28].
Figure A1:

SCA pseudocode [28].

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Published Online: 2024-01-08
Published in Print: 2024-02-26

© 2023 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. User independent tool for the analysis of data from tensile testing for database systems
  3. Evaluation of corrugated core configuration effects on low-velocity impact response in metallic sandwich panels
  4. Effect of total heat input on coaxiality of rotor shaft in laser cladding
  5. Determination of characteristic properties of Co3O4 loaded LaFe x Al12−x O19 hexaaluminates
  6. Investigation on quasi-static axial crushing of Al/PVC foam-filled Al6063-T5 tubes
  7. Experimental analysis of the effects of different production directions on the mechanical characteristics of ABS, PLA, and PETG materials produced by FDM
  8. Interfacial microstructure and mechanical properties of Si3N4/Invar joints using Ag–Cu–In–Ti with Cu foil as an interlayer
  9. Properties of chemically foamed polypropylene materials for application to automobile interior door panels
  10. Tribological and thermal characteristics of copper-free brake friction composites
  11. Dry tribological behaviour of microwave-assisted sintered AA2024 matrix hybrid composites reinforced by TiC/B4C/nano-graphite particles
  12. Erosion rate of AA6082-T6 aluminum alloy subjected to erosive wear determined by the meta-heuristic (SCA) based ANFIS method
  13. Mechanical properties of elevator ropes and belts exposed to corrosion and elevated temperatures
  14. Variants of friction stir based processes: review on process fundamentals, material attributes and mechanical properties
  15. Performance of conventional and wiper CBN inserts under various cooling conditions in hard turning of AISI 52100 steel
https://doi.org/10.1515/mt-2023-0154
Keywords for this article
aluminum alloy; erosive wear; ANNs; ANFIS; SCA

Articles in the same Issue

  1. Frontmatter
  2. User independent tool for the analysis of data from tensile testing for database systems
  3. Evaluation of corrugated core configuration effects on low-velocity impact response in metallic sandwich panels
  4. Effect of total heat input on coaxiality of rotor shaft in laser cladding
  5. Determination of characteristic properties of Co3O4 loaded LaFe x Al12−x O19 hexaaluminates
  6. Investigation on quasi-static axial crushing of Al/PVC foam-filled Al6063-T5 tubes
  7. Experimental analysis of the effects of different production directions on the mechanical characteristics of ABS, PLA, and PETG materials produced by FDM
  8. Interfacial microstructure and mechanical properties of Si3N4/Invar joints using Ag–Cu–In–Ti with Cu foil as an interlayer
  9. Properties of chemically foamed polypropylene materials for application to automobile interior door panels
  10. Tribological and thermal characteristics of copper-free brake friction composites
  11. Dry tribological behaviour of microwave-assisted sintered AA2024 matrix hybrid composites reinforced by TiC/B4C/nano-graphite particles
  12. Erosion rate of AA6082-T6 aluminum alloy subjected to erosive wear determined by the meta-heuristic (SCA) based ANFIS method
  13. Mechanical properties of elevator ropes and belts exposed to corrosion and elevated temperatures
  14. Variants of friction stir based processes: review on process fundamentals, material attributes and mechanical properties
  15. Performance of conventional and wiper CBN inserts under various cooling conditions in hard turning of AISI 52100 steel
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