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Insulating building walls provides a reliable approach to reduce heat losses in buildings. However, thermal insulation requires an appropriate selection of materials and understanding of their thermal properties e.g. thermal conductivity and density. This study presents a 3D model of fiber-concrete composite for thermal conductivity prediction. Composite materials properties were characterized by morphology structure that are often complicated to model, especially on fiber system. In order to understand thermal interaction of the wall for an insulating system, the model provides four level range of fibers number (100, 150, 200 and 250 fibers number) to analyze fiber network existing. The fibers are constructed by points neighbor derived from randomly launching order to perform spline. MATLAB software was reliable to generate a fibers structure algorithm before export to computer-aided design software. The natural fibers of oil palm, coconut and sugar cane were simulated using finite element method to study characteristic and thermal behavior of insulating material. Representative volume element and grid independence study was done to validate the model. The simulation demonstrated that improvement in insulating material about 0.65% can be achieved by using 250 coconut fibers number, which is much lower compared to plain concrete. A Morphology study was successful to understand fibers distribution and thermal absorption through the concrete. This model provides a promising solution in an understanding of thermal dispersion for concrete composite material application.

Natural Fibers Concrete Model Using Points Launching Algorithm in Thermal Conductivity Prediction