Abstract
Mechanical properties of nanoclay filled epoxy-polyurethane blended resins were experimentally investigated as they are proved to be very good materials for shape memory applications such as actuators, water and oil pipelines and aircrafts components like bearings, valve seat and floor etc. The mechanical properties such as tensile strength, compressive strength, flexural strength, shear strength etc. are become poor when the shape memory properties such as strain rate, strain recovery rate and strain fixidity ratio are good in polyurethane based nanocomposites. Therefore, polyurethane blended with epoxy is prepared as it is exhibiting interpenetrating network and the nanoclay is reinforced to improve the mechanical as well as functional properties. Therefore, there is absolute necessity for process modeling and parameter modeling of these materials in order to arrive at the optimum composition to have better mechanical properties. Mathematical modeling and empirical modeling are the effective ways for cost reduction methodology and stepping-stone to do optimization of the process parameters and properties of the materials developed. This paper initially analyses glass transition temperature and degradation temperatures by Differential Scanning Calorimetry. Then the different empirical model results are discussed for the selecting a suitable model and a simplified approach to analyse the mechanical properties of randomly distributed particulate composites. Finally, the analytical results are compared with tensile test results to identify the model, which gives good correlations. Further, the experimental results and the theoretical calculations using the empirical models showed that the strength of the composites is closer to the strength of the weaker constituent matrix material, for all the composites tested and shows improvement over the unblended polyurethane based composites. Also improvement in the thermal properties is also evidenced from the test results.