2007
DOI: 10.1016/j.matdes.2005.05.004
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Modelling the effect of particle size and iron content on forming of Al–Fe composite preforms using neural network

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Cited by 20 publications
(9 citation statements)
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“…Material improvements can be made in most cases, through this technology [17]. Usually, this technology consists of production of controlled blend in metal powders, by pressing suitable die in the mixture, and heating subsequently compacted powder at controlled atmosphere, along with temperature so as to obtain the required strength and density.…”
Section: T Judson Durai M Sivapragash and M Edwin Sahayarajmentioning
confidence: 99%
“…Material improvements can be made in most cases, through this technology [17]. Usually, this technology consists of production of controlled blend in metal powders, by pressing suitable die in the mixture, and heating subsequently compacted powder at controlled atmosphere, along with temperature so as to obtain the required strength and density.…”
Section: T Judson Durai M Sivapragash and M Edwin Sahayarajmentioning
confidence: 99%
“…Material improvements can be made in most cases, through this technology [7]. Effective sintering can improve the powders bonding and reduce porosity.…”
Section: Introductionmentioning
confidence: 99%
“…Neural networks have been proven to be highly flexible modelling tools, for learning the mathematical model between input variables and output responses for nonlinear systems [14]. The neural network was extensively used by many researchers to predict the physical, mechanical and the tribological properties of composite materials [15][16]. Many literatures pointed out that the ANN approach is a successful analytical tool that can be used to predict the wear behavior of new materials and composites, and concluded that the ANN is a good analytical tool to predict the wear properties [17][18].…”
Section: Introductionmentioning
confidence: 99%