DIGVIJAY G. BHOSALE, POONAM BHOSALE, AMRUT BHOSALE, YOGESH INGALE, HITESH VASUDEV, T. RAM PRABHU
{"title":"ANN SUPPORTED STUDY ON THE PERFORMANCE AND SLURRY EROSION RESISTANCE OF THERMAL SPRAYED WC20CR<sub>3</sub>C<sub>2</sub>7NI COATINGS","authors":"DIGVIJAY G. BHOSALE, POONAM BHOSALE, AMRUT BHOSALE, YOGESH INGALE, HITESH VASUDEV, T. RAM PRABHU","doi":"10.1142/s0218625x24020013","DOIUrl":null,"url":null,"abstract":"The thermal spray coatings are commonly employed in slurry pump components and hydrodynamic turbine blades, where wear progression is an intricate phenomenon. In this research work, the performance analysis of HVOF and APS sprayed WC20Cr 3 C 2 7Ni coatings for slurry erosion wear is carried out by using artificial neural networks (ANN). The influence of time, particle size, impact angle, speed, and slurry concentration on wear performance of coatings and turbine steel substrate are evaluated. Under the experimental settings, slurry erosion wear rates and mass loss for both coatings and substrate were determined. When ASTM A743 steel was coated with thermal sprayed WC20Cr 3 C 2 7Ni coatings, the slurry erosion wear resistance of the steel was enhanced by 2 and 3.5 times for APS and HVOF coatings, respectively. The design of ANN made it possible to examine the interactions between the seven input variables. A robust model was formed by the two outputs that followed. This model enables the prediction of slurry erosion wear rate and mass loss of WC20Cr 3 C 2 7Ni coatings and substrate.","PeriodicalId":22011,"journal":{"name":"Surface Review and Letters","volume":"61 1","pages":"0"},"PeriodicalIF":1.2000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Surface Review and Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0218625x24020013","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The thermal spray coatings are commonly employed in slurry pump components and hydrodynamic turbine blades, where wear progression is an intricate phenomenon. In this research work, the performance analysis of HVOF and APS sprayed WC20Cr 3 C 2 7Ni coatings for slurry erosion wear is carried out by using artificial neural networks (ANN). The influence of time, particle size, impact angle, speed, and slurry concentration on wear performance of coatings and turbine steel substrate are evaluated. Under the experimental settings, slurry erosion wear rates and mass loss for both coatings and substrate were determined. When ASTM A743 steel was coated with thermal sprayed WC20Cr 3 C 2 7Ni coatings, the slurry erosion wear resistance of the steel was enhanced by 2 and 3.5 times for APS and HVOF coatings, respectively. The design of ANN made it possible to examine the interactions between the seven input variables. A robust model was formed by the two outputs that followed. This model enables the prediction of slurry erosion wear rate and mass loss of WC20Cr 3 C 2 7Ni coatings and substrate.
期刊介绍:
This international journal is devoted to the elucidation of properties and processes that occur at the boundaries of materials. The scope of the journal covers a broad range of topics in experimental and theoretical studies of surfaces and interfaces. Both the physical and chemical properties are covered. The journal also places emphasis on emerging areas of cross-disciplinary research where new phenomena occur due to the presence of a surface or an interface. Representative areas include surface and interface structures; their electronic, magnetic and optical properties; dynamics and energetics; chemical reactions at surfaces; phase transitions, reconstruction, roughening and melting; defects, nucleation and growth; and new surface and interface characterization techniques.