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A. Shalwan - One of the best experts on this subject based on the ideXlab platform.
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Correlation between Mechanical Properties with Specific Wear Rate and the Coefficient of Friction of Graphite/Epoxy Composites
Materials, 2015Co-Authors: S. Alajmi, A. ShalwanAbstract:The correlation between the mechanical properties of Fillers/Epoxy composites and their tribological behavior was investigated. Tensile, hardness, Wear, and friction tests were conducted for Neat Epoxy (NE), Graphite/Epoxy composites (GE), and Data Palm Fiber/Epoxy with or without Graphite composites (GFE and FE). The correlation was made between the tensile strength, the modulus of elasticity, elongation at the break, and the hardness, as an individual or a combined factor, with the Specific Wear Rate (SWR) and coefficient of friction (COF) of composites. In general, graphite as an additive to polymeric composite has had an eclectic effect on mechanical properties, whereas it has led to a positive effect on tribological properties, whilst date palm fibers (DPFs), as reinforcement for polymeric composite, promoted a mechanical performance with a slight improvement to the tribological performance. Statistically, this study reveals that there is no strong confirmation of any marked correlation between the mechanical and the Specific Wear Rate of filler/Epoxy composites. There is, however, a remarkable correlation between the mechanical properties and the friction coefficient of filler/Epoxy composites.
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correlation between mechanical properties with Specific Wear Rate and the coefficient of friction of graphite epoxy composites
Materials, 2015Co-Authors: Mahdi S Alajmi, A. ShalwanAbstract:The correlation between the mechanical properties of Fillers/Epoxy composites and their tribological behavior was investigated. Tensile, hardness, Wear, and friction tests were conducted for Neat Epoxy (NE), Graphite/Epoxy composites (GE), and Data Palm Fiber/Epoxy with or without Graphite composites (GFE and FE). The correlation was made between the tensile strength, the modulus of elasticity, elongation at the break, and the hardness, as an individual or a combined factor, with the Specific Wear Rate (SWR) and coefficient of friction (COF) of composites. In general, graphite as an additive to polymeric composite has had an eclectic effect on mechanical properties, whereas it has led to a positive effect on tribological properties, whilst date palm fibers (DPFs), as reinforcement for polymeric composite, promoted a mechanical performance with a slight improvement to the tribological performance. Statistically, this study reveals that there is no strong confirmation of any marked correlation between the mechanical and the Specific Wear Rate of filler/Epoxy composites. There is, however, a remarkable correlation between the mechanical properties and the friction coefficient of filler/Epoxy composites.
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Correlation between Frictional Force, Interface Temperature and Specific Wear Rate of Fibre Polymer Composites
Advanced Materials Research, 2013Co-Authors: Y.h. Arhaim, A. Shalwan, B. F. YousifAbstract:Friction is classified as the main dominant element having an adverse influence on materials' lifespan and performance. Friction between any sliding contacts is continually accompanied by heat generation and shear force. The surface deterioration produces destruction in the component and reduced the life expectancy of the components. The shear force and/or the frictional heat areseen to be the main reasonscausing occurrence of the Wear on surfaces and the Wear removal during adhesion Wear loading. In the current paper, a comprehensive experiments and observation were made to correlate the three main elements of tribology (friction, temperature, and weight loss) to epoxy and its composites based on glass and kenaf fibres. The tests were conducted in adhesive Wear loading conditions against stainless steel counterface under dry contact conditions. SEM was performed to categorize the damage features of both composites. The results revealed that the interface temperature has more influence on the Wear behaviour of both composites than the friction coefficient. Different destructive features were observed.
V.n. Gaitonde - One of the best experts on this subject based on the ideXlab platform.
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Wear resistance enhancement of titanium alloy (Ti–6Al–4V) by ball burnishing process
Journal of Materials Research and Technology, 2017Co-Authors: Goutam D. Revankar, Raviraj Shetty, Shrikantha S. Rao, V.n. GaitondeAbstract:Abstract The objective of the research was to improve the Wear resistance of titanium alloys by ball burnishing process. Burnishing process parameters such as burnishing speed, burnishing feed, burnishing force and number of pass were considered to minimize the Specific Wear Rate and coefficient of friction. Taguchi optimization results revealed that burnishing force and number of pass were the significant parameters for minimizing the Specific Wear Rate, whereas the burnishing feed and speed play important roles in minimizing the coefficient of friction. After burnishing surface microhardness increased from 340 to 405 Hv, surface roughness decreased from 0.45 to 0.12 μm and compressive residual stress were geneRated immediately below the burnished surface. The optimization results showed that Specific Wear Rate decreased by 52%, whereas coefficient of friction was reduced by 64% as compared to the turned surface. The results confirm that, an improvement in the Wear resistance of Ti–6Al–4V alloy has been achieved by the process of ball burnishing.
Jinu Gowthami Thankachi Raghuvaran - One of the best experts on this subject based on the ideXlab platform.
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Prediction of Specific Wear Rate for LM25/ZrO2 composites using Levenberg–Marquardt backpropagation algorithm
Journal of Materials Research and Technology, 2020Co-Authors: Mathi Kannaiyan, Govindan Karthikeyan, Jinu Gowthami Thankachi RaghuvaranAbstract:Abstract In this study, the Wear estimation capability of RSM and artificial neural network (ANN) modelling techniques are examined and compared in this study. Though both RSM and ANN model performed well, ANN-based approach is found to be better in fitting to measure output response in comparison with the RSM model. The comparison of the productive capacity of RSM and LMBP (Levenberg–Marquardt backpropagation) neural network architecture for modelling the output, as well as output, predicted for the Wear samples in terms of various statistical parameters such as coefficient of determination (R2), etc., has been done. The coefficient of determination (R2) is higher for which the evaluated value shows that the ANN models have a higher modelling ability than the RSM model. The comparison between the experimental value and predicted value obtained by the ANN and RSM models reveals the coefficient of model determination (R2) for the ANN and RSM model is close to unity. The results obtained from the comparison of Specific Wear Rate values using ANN and RSM were proved to be close to the reading recorded experimentally with a 99% confidence level.
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prediction of Specific Wear Rate for lm25 zro2 composites using levenberg marquardt backpropagation algorithm
Journal of materials research and technology, 2020Co-Authors: Mathi Kannaiyan, Govindan Karthikeyan, Jinu Gowthami Thankachi RaghuvaranAbstract:Abstract In this study, the Wear estimation capability of RSM and artificial neural network (ANN) modelling techniques are examined and compared in this study. Though both RSM and ANN model performed well, ANN-based approach is found to be better in fitting to measure output response in comparison with the RSM model. The comparison of the productive capacity of RSM and LMBP (Levenberg–Marquardt backpropagation) neural network architecture for modelling the output, as well as output, predicted for the Wear samples in terms of various statistical parameters such as coefficient of determination (R2), etc., has been done. The coefficient of determination (R2) is higher for which the evaluated value shows that the ANN models have a higher modelling ability than the RSM model. The comparison between the experimental value and predicted value obtained by the ANN and RSM models reveals the coefficient of model determination (R2) for the ANN and RSM model is close to unity. The results obtained from the comparison of Specific Wear Rate values using ANN and RSM were proved to be close to the reading recorded experimentally with a 99% confidence level.
Narongrit Sombatsompop - One of the best experts on this subject based on the ideXlab platform.
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Effects of wood constituents and content, and glass fiber reinforcement on Wear behavior of wood/PVC composites☆
Composites Part B: Engineering, 2012Co-Authors: Supreeda Jeamtrakull, Apisit Kositchaiyong, Teerasak Markpin, Vichai Rosarpitak, Narongrit SombatsompopAbstract:Abstract In flooring applications, experimental data and insight from scientific investigations on Wear properties of wood/polymer composites (WPCs) are important for engineers to understand how to design and formulate WPC materials with high resistance to Wear. In this work, three different types of wood flour – namely Xylia kerrii Craib & Hutch., Hevea brasiliensis Linn., and Mangifera indica Linn. – were utilized and incorpoRated into poly(vinyl chloride) (PVC) with a fixed content (10 phr) of E-chopped strand glass fiber. The physical, mechanical and Wear properties, in terms of Specific Wear Rate, were then assessed as a function of wood content and sliding distance. The experimental results suggested that the addition of wood flour increased the flexural modulus and strength up to 40 phr; beyond this concentration, the flexural properties decreased. Hardness was not affected by the addition of wood flour. The mechanical and Wear properties of WPVC composites were found to improve with the addition of the E-glass fiber. Xylia kerrii Craib & Hutch. wood exhibited the lowest Specific Wear Rate for non-reinforced WPVC composites, whereas Hevea brasiliensis Linn. wood showed the lowest Specific Wear Rate for the glass fiber reinforced WPVC composites. The longer the sliding distance, the greater the Specific Wear Rate in all cases.
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Effect of h-BN content on Tribological Behavior of PEEK Composite Coating
2011Co-Authors: Jirasak Tharajak, Tippaban Palathai, Narongrit SombatsompopAbstract:Low velocity oxy-fuel (LVOF) spraying technique was used to deposit PEEK and h-BN/PEEK powders onto the low carbon steel substRate. The effect of h-BN contents on surface roughness, hardness, degree of crystallinity, Specific Wear Rate and friction coefficient was investigated. It can be found that top-surface roughness, hardness and degree of crystallinity increased with an increase in h-BN contents. The Specific Wear Rate of the h-BN/PEEK composite coatings decreased as compared with the PEEK coatings. Increased h-BN content at 8 wt% exhibited the lowest friction coefficient.
Goutam D. Revankar - One of the best experts on this subject based on the ideXlab platform.
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Wear resistance enhancement of titanium alloy (Ti–6Al–4V) by ball burnishing process
Journal of Materials Research and Technology, 2017Co-Authors: Goutam D. Revankar, Raviraj Shetty, Shrikantha S. Rao, V.n. GaitondeAbstract:Abstract The objective of the research was to improve the Wear resistance of titanium alloys by ball burnishing process. Burnishing process parameters such as burnishing speed, burnishing feed, burnishing force and number of pass were considered to minimize the Specific Wear Rate and coefficient of friction. Taguchi optimization results revealed that burnishing force and number of pass were the significant parameters for minimizing the Specific Wear Rate, whereas the burnishing feed and speed play important roles in minimizing the coefficient of friction. After burnishing surface microhardness increased from 340 to 405 Hv, surface roughness decreased from 0.45 to 0.12 μm and compressive residual stress were geneRated immediately below the burnished surface. The optimization results showed that Specific Wear Rate decreased by 52%, whereas coefficient of friction was reduced by 64% as compared to the turned surface. The results confirm that, an improvement in the Wear resistance of Ti–6Al–4V alloy has been achieved by the process of ball burnishing.