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Modeling the mechanical properties of Composites Reinforced bySilica nanoparticles through Response Surface Method &Regression Tree Method

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Modeling the mechanical properties of Composites Reinforced bySilica nanoparticles through Response Surface Method &Regression Tree Method
نوع فایل:PDF
تعداد صفحات :15
سال انتشار : 1395
چکیده
An experimental study has been conducted on fracture toughness (KIC) and fracture energy(GIC) of composites reinforced by silica nanoparticles in this article. Three different diametersof 23, 74, and 170 nanometer nanoparticles were added to epoxy resin by up to 30 volumepercent. Two parameters, the size of the particles and the volume percent, have beenconsidered as the parameters affecting the above- mentioned properties. Moreover, these twoparameters have been considered as the input parameters for the purpose of modeling theresults through the response surface model method & regression tree method. Theexperimental results and the results of modeling indicate that adding silica nanoparticles has asignificant effect on Youngs modulus, fracture toughness and fracture energy in such amanner that these parameters increase when the silica nanoparticle content is added howeverthe size of the particles does not have a significant effect on them. Also the experimentalresults and the modeling results show that the second order response surface model makes thebest predictions. Additionally, the best value for Youngs modulus is 5.801 GPa when theparticle size is 170 nm and volume percent is 30. The best value for fracture toughness isequal to 2.852MPa m , when the particle size is 112 nm and the volume percent is 30. Alsothis method shows that the best value for fracture energy is equal to 1270 J/m2 when the sizeof the particle is 112 nanometers and the volume percent is 30. Also, compare the resultobtained from Regression tree method and RSM method show that still the results obtained from RSMmethod is much more suitable from Regression Tree method
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