Author(s)

Anil Saigal^*, Pandhita Pochanard

Department of Mechanical Engineering, Tufts University, Medford, MA, USA.

In this study, a numerical representative volume element (RVE) model was used to predict the mechanical properties of a Rice Husk Particulate (RHP)-Epoxy composite for use as an alternative material in non-critical applications. Seven different analytical models Counto, Ishai-Cohen, Halpin-Tsai, Nielsen, Nicolais, Modified Nicolais and Pukanszky were used as comparison tools for the numerical model. RHP-Epoxy biocomposite samples were fabricated with 0%, 10% and 30% RHP volume percentage and the experimental results benchmarked against the numerical and analytical projections. The mechanical properties estimated for 0%, 10% and 30% RHP-Epoxy composites using the numerical and analytical models were in general agreement. Using the analytical models, it was calculated that an increase in volume percentage of RHP to 30% led to continual reduction in elastic Young’s modulus and ultimate tensile strength of the composite. The numerical RVE models also predicted a similar trend between filler volume percentage and material properties. These projections were consistent with the experimental results whereby a 10% increase in RHP content led to 15% and 20% decrease in yield stress and tensile strength, but had no effect on the composite’s elastic property. Further increase in RHP volume percentage to 30% resulted in 8%, 21% and 28% reduction in Young’s modulus, yield stress and tensile strength, respectively. Overall, the results of this study suggest that RHP can be used to reduce the composite raw material costs by replacing the more expensive polymer content with agricultural waste products with limited compromise to the composite’s mechanical properties.

RHP-Epoxy Composites, RVE Model, Mechanical Properties

Saigal, A. and Pochanard, P. (2019) The Application of a Representative Volume Element (RVE) Model for the Prediction of Rice Husk Particulate-Filled Polymer Composite Properties. Materials Sciences and Applications, 10, 78-103. doi: 10.4236/msa.2019.101008.