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Dehestani, Mahboubeh, Khayati, Gholam, Sharafi, Shahriar. (1400). Function finding via genetic expression programming to predict microhardness of Ni/Al2O3 nanocomposite coatings. , 54(1), 73-84. doi: 10.22059/jufgnsm.2021.01.08
Mahboubeh Dehestani; Gholam Reza Khayati; Shahriar Sharafi. "Function finding via genetic expression programming to predict microhardness of Ni/Al2O3 nanocomposite coatings". , 54, 1, 1400, 73-84. doi: 10.22059/jufgnsm.2021.01.08
Dehestani, Mahboubeh, Khayati, Gholam, Sharafi, Shahriar. (1400). 'Function finding via genetic expression programming to predict microhardness of Ni/Al2O3 nanocomposite coatings', , 54(1), pp. 73-84. doi: 10.22059/jufgnsm.2021.01.08
Dehestani, Mahboubeh, Khayati, Gholam, Sharafi, Shahriar. Function finding via genetic expression programming to predict microhardness of Ni/Al2O3 nanocomposite coatings. , 1400; 54(1): 73-84. doi: 10.22059/jufgnsm.2021.01.08

Function finding via genetic expression programming to predict microhardness of Ni/Al2O3 nanocomposite coatings

Journal of Ultrafine Grained and Nanostructured Materials
دوره 54، شماره 1، شهریور 2021، صفحه 73-84    اصل مقاله (2.88 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/jufgnsm.2021.01.08
نویسندگان
Mahboubeh Dehestani؛ Gholam Reza Khayati* ؛ Shahriar Sharafi
Department of Materials Science and Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
چکیده
A new proposing model based on gene expression programming (GEP) to predict the microhardness of Ni/Al2O3 nanocomposite coating was the subject of the present study. Accordingly, a series of the laboratory experiments was designed by the factorial D-optimal array. This was accomplished by considering the most effecting practical electrodeposition parameters including the amount of Al2O3 nanoparticles in the bath, current density, temperature, magnetic stirring rate, time of stirring, and plating time as the input and the microhardness of the coating as the output of model. Various performance criteria including determination (R2) coefficient, the mean absolute error (MAE), and the root relative squared error (RRSE) were utilized to evaluate the developed models. Finally, the model with R2 = 0.9752, MAE = 0.030 and RRSE = 0.158 was developed as the optimum proposed function. Also, the results of the sensitivity analysis confirmed that the current density was the most effective parameter, while the amount of Al2O3 nanoparticles in the bath, plating time, magnetic stirring rate, time of stirring, and temperature had relatively lower effect. In conclusion, the exclusive features of the GEP simulation have been approved to determine Ni/Al2O3 nanocomposite coatings microhardness.
کلیدواژه‌ها
Ni/Al2O3 nanocomposite؛ Microhardness؛ Electrodeposition؛ Gene expression programming
مراجع

1. Beltowska-Lehman E, Bigos A, Indyka P, Chojnacka A, Drewienkiewicz A, Zimowski S, et al. Optimisation of the electrodeposition process of Ni-W/ZrO 2 nanocomposites. Journal of Electroanalytical Chemistry. 2018;813:39-51.

2. Gurrappa I, Binder L. Electrodeposition of nanostructured coatings and their characterization-A review. Sci Technol Adv Mater. 2008;9(4):043001-.

3. Casati R, Vedani M. Metal Matrix Composites Reinforced by Nano-Particles—A Review. Metals. 2014;4(1):65-83.

4. Ibrahim IA, Mohamed FA, Lavernia EJ. Particulate reinforced metal matrix composites — a review. Journal of Materials Science. 1991;26(5):1137-56.

5. Grewal HS, Agrawal A, Singh H, Shollock BA. Slurry Erosion Performance of Ni-Al2O3 Based Thermal-Sprayed Coatings: Effect of Angle of Impingement. Journal of Thermal Spray Technology. 2013;23(3):389-401.

6. Jiang SW, Yang L, Pang JN, Lin H, Wang ZQ. Electrodeposition of Ni-Al2O3 composite coatings with combined addition of SDS and HPB surfactants. Surface and Coatings Technology. 2016;286:197-205.

7. Benea L, Danaila E, Celis J-P. Influence of electro-co-deposition parameters on nano-TiO2 inclusion into nickel matrix and properties characterization of nanocomposite coatings obtained. Materials Science and Engineering: A. 2014;610:106-15.

8. Góral A. Nanoscale structural defects in electrodeposited Ni/Al 2 O 3 composite coatings. Surface and Coatings Technology. 2017;319:23-32.

9. Lajevardi SA, Shahrabi T, Szpunar JA. Synthesis of functionally graded nano Al2O3–Ni composite coating by pulse electrodeposition. Applied Surface Science. 2013;279:180-8.

10. Gül H, Kılıç F, Aslan S, Alp A, Akbulut H. Characteristics of electro-co-deposited Ni–Al2O3 nano-particle reinforced metal matrix composite (MMC) coatings. Wear. 2009;267(5-8):976-90.

11. Borkar T, Harimkar SP. Effect of electrodeposition conditions and reinforcement content on microstructure and tribological properties of nickel composite coatings. Surface and Coatings Technology. 2011;205(17-18):4124-34.

12. Coşkun Mİ, Karahan İH. Modeling corrosion performance of the hydroxyapatite coated CoCrMo biomaterial alloys. Journal of Alloys and Compounds. 2018;745:840-8.

13. Mehdizadeh S, Behmanesh J, Khalili K. Application of gene expression programming to predict daily dew point temperature. Applied Thermal Engineering. 2017;112:1097-107.

14. Muzzammil M, Alama J, Danish M. Scour Prediction at Bridge Piers in Cohesive Bed Using Gene Expression Programming. Aquatic Procedia. 2015;4:789-96.

15. Ferreira C. The Basic Gene Expression Algorithm. Gene Expression Programming: Springer Berlin Heidelberg. p. 55-120.

16. Güllü H. Function finding via genetic expression programming for strength and elastic properties of clay treated with bottom ash. Engineering Applications of Artificial Intelligence. 2014;35:143-57.

17. Ebrahimzade H, Khayati GR, Schaffie M. A novel predictive model for estimation of cobalt leaching from waste Li-ion batteries: Application of genetic programming for design. Journal of Environmental Chemical Engineering. 2018;6(4):3999-4007.

18. Abdellahi M, Bahmanpour H, Bahmanpour M. The best conditions for minimizing the synthesis time of nanocomposites during high energy ball milling: Modeling and optimizing. Ceramics International. 2014;40(7):9675-92.

19. Ebrahimi-Kahrizsangi R, Abdellahi M, Bahmanpour M. Ignition time of nanopowders during milling: A novel simulation. Powder Technology. 2015;272:224-34.

20. Mahdavi Jafari M, Khayati GR. Prediction of hydroxyapatite crystallite size prepared by sol–gel route: gene expression programming approach. Journal of Sol-Gel Science and Technology. 2018;86(1):112-25.

21. Mansouri I, Chacón R, Hu JW. Improved predictive model to the cross-sectional resistance of CFT. Journal of Mechanical Science and Technology. 2017;31(8):3887-95.

22. Mansouri I, Hu J, Kisi O. Novel Predictive Model of the Debonding Strength for Masonry Members Retrofitted with FRP. Applied Sciences. 2016;6(11):337.

23. Saha RK, Khan TI. Effect of applied current on the electrodeposited Ni–Al2O3 composite coatings. Surface and Coatings Technology. 2010;205(3):890-5.

24. García-Lecina E, García-Urrutia I, Díez JA, Morgiel J, Indyka P. A comparative study of the effect of mechanical and ultrasound agitation on the properties of electrodeposited Ni/Al2O3 nanocomposite coatings. Surface and Coatings Technology. 2012;206(11-12):2998-3005.

25. Khandelwal M, Armaghani DJ, Faradonbeh RS, Ranjith PG, Ghoraba S. A new model based on gene expression programming to estimate air flow in a single rock joint. Environmental Earth Sciences. 2016;75(9).

26. Baykasoglu A, Gullu H, Canakci H, Ozbakir L. Prediction of compressive and tensile strength of limestone via genetic programming. Expert Systems with Applications. 2008;35(1-2):111-23.

27. Ferreira C, Gepsoft, U. What is gene expression programming; 2008.

28. Mollahasani A, Alavi AH, Gandomi AH. Empirical modeling of plate load test moduli of soil via gene expression programming. Computers and Geotechnics. 2011;38(2):281-6.

29. Góral A, Nowak M, Berent K, Kania B. Influence of current density on microstructure and properties of electrodeposited nickel-alumina composite coatings. Journal of Alloys and Compounds. 2014;615:S406-S10.

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