EXAMINATION OF THE WEAR BEHAVIOR OF CU-BASED BRAKE PADS USED IN HIGH-SPEED TRAINS AND PREDICTION THROUGH STATISTICAL AND NEURAL NETWORK MODELS

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dc.contributor.authorEkinci, Serafettin
dc.contributor.authorAsilturk, Ilhan
dc.contributor.authorAkkus, Harun
dc.contributor.authorMahammadzade, Akshin
dc.date.accessioned2024-02-23T14:26:25Z
dc.date.available2024-02-23T14:26:25Z
dc.date.issued2023
dc.departmentNEÜen_US
dc.description.abstractThe aim of this study is to provide insights into the performance of copper-based brake pads used in high-speed trains and contribute to a more predictable braking system by leveraging mathematical and artificial intelligence (AI) models. The wear behavior of Cu-based brake pads in high-speed trains was investigated using a pin-on-disc test setup under different speeds, temperatures, and loads with a constant sliding distance. Additionally, mathematical and AI models were developed to predict the friction coefficient and wear rate values obtained from the experiments. This innovative approach initiates a significant discussion in line with a current need, and the sharing and publication of the obtained results are currently essential to address the knowledge gap in this field. The results revealed that an increase in temperature led to an increase in both the friction coefficient and wear rate. Conversely, an increase in load resulted in a decrease in both the friction coefficient and wear rate. The transition from abrasive wear to adhesive wear occurred due to the softening of copper between friction surfaces, leading to material transfer. According to the results obtained from the models, both the artificial neural network (ANN) and multiple regression models demonstrated comparable accuracy, predicting the friction coefficient with approximately 94% accuracy in both cases, indicating reliable predictions. For the wear rate, the models achieved approximately 90% and 92% accuracy, respectively.en_US
dc.description.sponsorshipScientific Research Projects Coordination Office of Selcuk University [22201032]en_US
dc.description.sponsorshipThe authors acknowledge the support of the Scientific Research Projects Coordination Office of Selcuk University, Project Number: 22201032.en_US
dc.identifier.doi10.1142/S0218625X24500628
dc.identifier.issn0218-625X
dc.identifier.issn1793-6667
dc.identifier.scopus2-s2.0-85181454582en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1142/S0218625X24500628
dc.identifier.urihttps://hdl.handle.net/20.500.12452/14173
dc.identifier.wosWOS:001134399300003en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWorld Scientific Publ Co Pte Ltden_US
dc.relation.ispartofSurface Review And Lettersen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAnnen_US
dc.subjectCu-Based Brake Paden_US
dc.subjectFriction Coefficienten_US
dc.subjectMathematical Modelen_US
dc.subjectSemen_US
dc.subjectWear Rateen_US
dc.titleEXAMINATION OF THE WEAR BEHAVIOR OF CU-BASED BRAKE PADS USED IN HIGH-SPEED TRAINS AND PREDICTION THROUGH STATISTICAL AND NEURAL NETWORK MODELSen_US
dc.typeArticleen_US

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