2012
DOI: 10.1016/j.msea.2012.03.066
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An experimental and statistical study of interaction effects of matrix particle size, reinforcement particle size and volume fraction on the flexural strength of Al–SiCp composites by P/M using central composite design

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Cited by 64 publications
(30 citation statements)
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“…Table 1 presents the effect of mass fraction distribution on the weight loss of Al-SiC composites. As listed in Table 1, although wear loss decreased with increase in surface mass fraction, this trend significantly declined for F 13 , because high-fraction SiC can negatively affect the mechanical behavior since particle clustering occurs as SiC fraction increases [23,24]. This trend is in agreement with the results reported in other researches [25,26].…”
Section: Tensile Propertiessupporting
confidence: 90%
“…Table 1 presents the effect of mass fraction distribution on the weight loss of Al-SiC composites. As listed in Table 1, although wear loss decreased with increase in surface mass fraction, this trend significantly declined for F 13 , because high-fraction SiC can negatively affect the mechanical behavior since particle clustering occurs as SiC fraction increases [23,24]. This trend is in agreement with the results reported in other researches [25,26].…”
Section: Tensile Propertiessupporting
confidence: 90%
“…The number of runs by the CCD method is given by: [2 k +2k + n c ], where 2 k refers to the full factorial design, 2k are the axial points and n c are the central points (usually three to five points are used) [41].…”
Section: Statistical Approach Methodsmentioning
confidence: 99%
“…Among different approaches, central composite design (CCD) is an appropriate experimental design method which provides high quality predictions in studying linear, quadratic and interaction effects of parameters that influence a system. Furthermore, one of the efficient techniques for obtaining the optimum conditions in a multivariable system is response surface methodology (RSM) [13]. Furthermore, one of the efficient techniques for obtaining the optimum conditions in a multivariable system is response surface methodology (RSM) [14].…”
Section: Archivos De Medicina Issn 1698-9465mentioning
confidence: 99%