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Modeling and predicting abrasive wear behaviour of poly oxy methylenes using response surface methodolgy and neural networks

A. Sagbas ; Tarsus Technical Education Faculty, Mersin University, Tarsus, Turkey
F. Kahraman ; Tarsus Technical Education Faculty, Mersin University, Tarsus, Turkey
U. Esme ; Tarsus Technical Education Faculty, Mersin University, Tarsus, Turkey

Puni tekst: engleski, pdf (656 KB) str. 117-120 preuzimanja: 1.423* citiraj
APA 6th Edition
Sagbas, A., Kahraman, F. i Esme, U. (2009). Modeling and predicting abrasive wear behaviour of poly oxy methylenes using response surface methodolgy and neural networks. Metalurgija, 48 (2), 117-120. Preuzeto s https://hrcak.srce.hr/32000
MLA 8th Edition
Sagbas, A., et al. "Modeling and predicting abrasive wear behaviour of poly oxy methylenes using response surface methodolgy and neural networks." Metalurgija, vol. 48, br. 2, 2009, str. 117-120. https://hrcak.srce.hr/32000. Citirano 16.09.2019.
Chicago 17th Edition
Sagbas, A., F. Kahraman i U. Esme. "Modeling and predicting abrasive wear behaviour of poly oxy methylenes using response surface methodolgy and neural networks." Metalurgija 48, br. 2 (2009): 117-120. https://hrcak.srce.hr/32000
Harvard
Sagbas, A., Kahraman, F., i Esme, U. (2009). 'Modeling and predicting abrasive wear behaviour of poly oxy methylenes using response surface methodolgy and neural networks', Metalurgija, 48(2), str. 117-120. Preuzeto s: https://hrcak.srce.hr/32000 (Datum pristupa: 16.09.2019.)
Vancouver
Sagbas A, Kahraman F, Esme U. Modeling and predicting abrasive wear behaviour of poly oxy methylenes using response surface methodolgy and neural networks. Metalurgija [Internet]. 2009 [pristupljeno 16.09.2019.];48(2):117-120. Dostupno na: https://hrcak.srce.hr/32000
IEEE
A. Sagbas, F. Kahraman i U. Esme, "Modeling and predicting abrasive wear behaviour of poly oxy methylenes using response surface methodolgy and neural networks", Metalurgija, vol.48, br. 2, str. 117-120, 2009. [Online]. Dostupno na: https://hrcak.srce.hr/32000. [Citirano: 16.09.2019.]

Sažetak
In this study, abrasive wear behaviour of poly oxy methylenes (POM) under various testing conditions was investigated. A central composite design (CCD) was used to describe response and to estimate the parameters in the model. Response surface methodology (RSM) was adopted to obtain an empirical model of wear loss as a function of applied load and sliding distance. Also, a neural network (NN) model was developed for the prediction and testing of the results. Finally, a comparison was made between the results obtained from RSM and NN.

Ključne riječi
abrasive wear; poly oxy methylene; neural network; responce surface methodology

Hrčak ID: 32000

URI
https://hrcak.srce.hr/32000

[hrvatski]

Posjeta: 1.786 *