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Abrasive Sensitivity of Engineering Polymers and a Bio-Composite under Different Abrasive Conditions

Two different test systems were designed to evaluate the tribological behavior of five engineering plastics (Polyamide—PA grades and Ultra High Molecular Weight Polyethylene—UHMW-PE) and a fully degradable bio-composite (Polylactic Acid—PLA/hemp fibers) targeted to agricultural machinery abrasive co...

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Detalles Bibliográficos
Autores principales: Muhandes, Hasan, Kalácska, Ádám, Székely, László, Keresztes, Róbert, Kalácska, Gábor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7699501/
https://www.ncbi.nlm.nih.gov/pubmed/33228186
http://dx.doi.org/10.3390/ma13225239
Descripción
Sumario:Two different test systems were designed to evaluate the tribological behavior of five engineering plastics (Polyamide—PA grades and Ultra High Molecular Weight Polyethylene—UHMW-PE) and a fully degradable bio-composite (Polylactic Acid—PLA/hemp fibers) targeted to agricultural machinery abrasive conditions. Pin-on-plate tests were performed with different loads, sliding velocity and abrasive particles. The material response was further investigated in a slurry containing abrasive test system with different sliding velocities and distances, abrasive media compositions and impact angles. The abrasive wear, the change of the 3D surface roughness parameters, the friction force and contact temperature evolution were also analyzed as a function of the materials’ mechanical properties ([Formula: see text] and the dimensionless numbers derived from them. Using the IBM SPSS 25 software, multiple linear regression models were used to statistically evaluate the measured data and to examine the sensitivity of the material properties and test system characteristics on the tribological behavior. For both test setups, the system and material characteristics influencing the dependent variables (wear, friction, heat generation) and the dimensionless numbers formed from the material properties were ranked using standardized regression coefficients derived from the regression models. The abrasion sensitivity of the tested materials were evaluated taking into account a wide range of influencing parameters.