Ali Dadrasi - Technical Engineering Faculty of Islamic Azad University, Shahrood Branch
Abdolreza Alavi Gharebagh - Computer and Electrical Engineering Faculty of Islamic Azad University, Shahrood Branch
Sasan Fooladpanjeh - Master’s students in Islamic Azad University, Shahrood Branch

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 Young's 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 Young's 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

Nano composite, Silica, Fracture toughness, Response surface method