Abstract
Nylon 66 has been widely used for numerous mechanical applications but its sliding wear mechanisms are not fully understood. In particular, limited attention has been paid to the generation of fatigue surface cracks under constant and cyclic load conditions. The present work focuses on the effect of load frequency on the wear behavior of a polymer with surface defects in dry sliding conditions. The defects were imposed vertical deep cracks perpendicular to the direction of sliding. Wear studies were conducted against a steel counterface at constant loads, and in cyclic loads at different frequencies. Artificial neural network (ANN) models were examined to identify one that optimally simulates wear under the applied load parameters.
Surface cracks were found to have a remarkable adverse effect on the wear behavior of the polymer. The wear rates were influenced by the number of cracks as well as the type of applied load. Furthermore, results suggest that the presence of surface cracks is attributable to the section B wear regime. Finally, acceptable predicted wear rate values were obtained by introducing the ANN wear model.
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References
Hutchings I M. Tribology: Friction and Wear of Engineering Materials. Asterix Press, 1992.
Clark D T, Feast W J. Polymer Surfaces. New York: John Wiley & Sons, 1978.
Suh N P. The delamination theory of wear. Wear25: 111–124 (1973)
Chen Y K, Kukureka S N, Hooke C J, Rao M. Surface topography and wear mechanisms in polyamide 66 and its composites. J Mat Sci35: 1269–1281 (2000)
Barbour P S M, Barton D C, Fisher J. The influence of contact stress on the wear of UHMWPE for total replacement hip prostheses. Wear181–183: 250–257 (1995)
Cooper J R, Dowson D, Fisher J. Macroscopic and microscopic wear mechanisms in UHMWPE. Wear162–164: 378–384 (1993)
Abdelbary A, Abouelwafa M N, El Fahham I, Gomaa A I. The influence of cyclic loading parameters on the wear of nylon 66. In Proc. 8th International Conference on Production Engineering and Control PEDAC, Egypt, 2004.
Abdelbary A, Abouelwafa M N, El Fahham I, Gomaa A I. A New reciprocating tribometer for wear testing under different fluctuating loading conditions. Alexandria Eng J43: 615–619 (2004)
Yap U J, Teoh S H, Chew C L. Effect of cyclic loading on occlusal contact area wear of composite restoratives. Dent Mater18: 149–158 (2002)
Furber K, Atkenson J R, Dowson D. The mechanisms for nylon 66: Paper II. In Proc. of the 3rd Leeds-Lyon Symposium on Tribology, 1976.
Atkinson J R, Brown K J, Dowson D. The wear of high molecular weight polyethlene. Part I: The wear of isotropic polyethylene against dry stainless steel in unidirectional motion. J Lub Tech100: 208–218 (1978)
Anderson J C, Robins E J. The influence of temperature generation on the wear of some polymers. In Proc. of the 3rd Leeds-Lyon Symposium on Tribology, 1976.
Frangu L, Ripa M. Artificial neural networks applications in tribology-A survey. In 2001 NATO Advanced Study Institute on Neural Networks for Instrumentation, Measurement, and Related Industrial Applications: Study Cases, Crema, Italy, 2001: 35–42.
Rutherford K L, Hatto P W, Davies C, Hutchings I M. Abrasive wear resistance of TiN/NbN multi-layers: Measurement and neural network modelling. Surf Coat Tech86–87: 472–479 (1996)
Jones S P, Jansen R, Fusaro R L. Preliminary investigations of neural network techniques to predict tribological properties. Tribol Trans40: 312–320 (1997)
Velten K, Reinicke R, Friedrich K. Wear volume prediction with artificial neural networks. Tribol Int33: 731–736 (2000)
Zhang Z, Friedrich K. Artificial neural networks applied to polymer composites: A review. Comp Sci Tech63: 2029–2044 (2003)
Zhu J, Shi Y, Feng X, Wang H, Lu X. Prediction on tribological properties of carbon fiber and TiO2 synergistic reinforced polytetrafluoroethylene composites with artificial neural networks. Mater Des30: 1042–1049 (2009)
Kranthi G, Satapathy A. Evaluation and prediction of wear response of pine wood dust filled epoxy composites using neural computation. Comp Mater Sci49: 609–614 (2010)
Lada A, Friedrich K. Artificial neural networks for predicting sliding friction and wear properties of polyphenylene sulfide composites. Tribol Int44: 603–609 (2011)
Abdelbary A, Abouelwafa M N, El Fahham I, Hamdy A H. Modeling the wear of Polyamide 66 using artificial neural network. Mater Des41: 460–469 (2012)
Goto K, Kagawa Y, Nojima K, Iba H. Effect of crack fibre interactions on crack growth rate in fibre-reinforced brittle matrix composite under cyclic loading. Mater Sci EngA212: 69–74 (1996)
Abdelbary A, Abouelwafa M N, El Fahham I, Hamdy A H. The influence of surface crack on the wear behaviour of polyamide 66 under dry sliding condition. Wear271: 2234–2241 (2011)
Zang Z, Friedrich K, Velten K. Prediction on tribological properties of short fibre composites using artificial neural networks. Wear252: 668–675 (2002)
Jiang Z, Zhang Z, Friedrich K. Prediction on wear properties of polymer composites with artificial neural network. Comp Sci Tech67: 168–176 (2007)
Lada A, Gyurova L A, Minino P, Schlorb A K. Modeling the sliding wear and friction properties of polyphenylene sulfide composites using artificial neural networks. Wear268: 708–714 (2010)
Jiang Z, Gyurova L A, Schlarb A K, Friedrich K, Zhang Z. Study on friction and wear behavior of polyphenylene sulfide composites reinforced by short carbon fibers and sub-micro TiO2 particles. Comp Sci Tech68: 734–742 (2008)
Liu X, Davim P, Cardoso R. Prediction on tribological behaviour of composite PEFK-CF30 using artificial neural networks. J Mat Proc Tech189: 374–378 (2007)
Jiang Z, Gyurova L, Zhang Z, Friedrich K, Schlarb K. Neural networks based prediction on mechanical and wear properties of short fibers reinforced polyamide composites. Mater Des29: 628–637 (2008)
Helmy A. Neural network wear prediction models for the polymethylmethacrylate PMMA. Alexandria Eng J43: 401–407 (2004)
Dowson J R, Atkinson K, Brown K. The wear of high molecular weight polyethylene with particular reference to its use in artificial human joints. In Advances in Polymeric Function and Wear, Vol. 5B, Lee L H Ed. New York: Plenum Press, 1976: 533–551.
Terheci M. Microscopic investigation on the origin of wear by surface fatigue in dry sliding. Mater Char45: 1–15 (2000)
Fam H, Keer L M, Chang W, Cheng H S. Competition between fatigue crack propagation and wear. J Tribol115: 141–145 (1993)
Yu S R, Hu H X, Zhang Y, Liu Y H. Effect of transfer film on tribological behavior of polyamide 66-based binary and ternary nanocomposites. Polym Int57: 454–462 (2008)
Zalisz Z, Vroegop P H, Bosma R. A running-in model for the reciprocating sliding of nylon 6.6 against stainless steel. Wear121: 71–93 (1988)
Franklin S E, de Kraker A. Investigation of counterface surface topography effect on the wear and transfer behaviour of a POM-20%PTFE composite. Wear225: 766–773 (2003)
Lamethe J F, Sergot P, Chateauminois A, Briscoe B J. Contact fatigue behaviour of glassy polymers with improved toughness under fretting wear conditions. Wear255: 758–765 (2003)
Osgood C C. Fatigue Design. Pergamon Press, 1970.
Brown K J, Atkinson J R, Dowson D. The wear of UHMWPE: Part II. J Lub Tech104: 17–22 (1982)
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Ahmed ABDELBARY. He has received his BS degree in the Mechanical Engineering from Military Technical College in Cairo, MS and PhD degree from Alexandria University, Egypt. He has an academic research experience in wear of polymers since 1999. He is a full member of the Egyptian Society of Tribology EGTRIB. His areas of technical expertise extend to design and manufacture of many mechanical systems. He has published several research papers on tribology of polymers, in well-reputed engineering journals.
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Abdelbary, A., Abouelwafa, M.N. & El Fahham, I.M. Evaluation and prediction of the effect of load frequency on the wear properties of pre-cracked nylon 66. Friction 2, 240–254 (2014). https://doi.org/10.1007/s40544-014-0044-4
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DOI: https://doi.org/10.1007/s40544-014-0044-4