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Computational Thermal Sciences: An International Journal
ESCI SJR: 0.249 SNIP: 0.434 CiteScore™: 0.7

ISSN Print: 1940-2503
ISSN Online: 1940-2554

Computational Thermal Sciences: An International Journal

DOI: 10.1615/ComputThermalScien.2012004213
pages 107-114

COMPUTATIONAL AND EXPERIMENTAL INVESTIGATION ON THERMAL INSULATION CAPABILITIES OF RICE-HUSK FILLED EPOXY COMPOSITES

Arun Kumar Rout
Department of Production Engineering, VSSUT, Burla,768018, India
Alok Satapathy
Department of Mechanical Engineering, National Institute of Technology, Rourkela 769008, India

ABSTRACT

The finite-element method (FEM) is a powerful computational technique for approximate solutions to a variety of engineering problems having complex domains subjected to general boundary conditions. In this paper FEM is implemented to determine the effective thermal conductivity of rice-husk filled polymer composites and is validated by experimentation. A commercially available finite-element package (ANSYS) is used to for this numerical analysis. Three-dimensional spheres-in-cube lattice array models are constructed to simulate the microstructure of composite materials for various filler concentrations ranging from about 0 to 6.5 vol. %. Composites with similar filler contents are fabricated by the hand layup technique by reinforcing microsized rice husk in epoxy resin. The guarded heat flow meter test method is used to measure the thermal conductivity of these composites using the instrument UnithermTMmodel 2022 as per ASTM-E1530. This study shows that the incorporation of rice husk results in reduction of conductivity of epoxy resin and thereby improves its thermal insulation capability. With the addition of 6.5 vol. % of filler, the thermal conductivity of epoxy is found to decrease by about 8.26%. The experimentally measured conductivity values are compared with the numerically calculated ones and also with the existing theoretical and empirical models. The values obtained using finite-element analysis (FEA) are found to be in reasonable agreement with the experimental values.