Predicting thermal conductivity and mechanical property of bamboo fibers/polypropylene nonwovens reinforced composites based on regression analysis. (November 2020) - Wang, Chunhong; Zuo, Qi; Lin, Tianyang; Anuar, Noor Intan Saffinaz; Mohd Salleh, Kushairi; Gan, Sinyee; Yousfani, Sheraz Hussain Siddique; Zuo, Hengfeng; Zakaria, Sarani
Abstract: The bamboo fibers (BF) reinforced polypropylene (PP) composites with different mass fractions of BF were prepared via needle punching non-woven process and compression molding process. The effects of mass fractions of BF on the mechanical properties, gas permeability, thermal conductivity of BF/PP needle punched non-woven fabrics were investigated. The relationship between the thermal conductivity of non-woven fabrics and the properties of composites was predicted by regression analysis. The results showed that the breaking strength of transversal and longitudinal non-woven fabrics both decreased with the increase of BF contents. The opposite trend was observed concerning the gas permeability and the thermal conductivity of non-woven fabrics. The best thermal conductivity of composite was found at 70% mass fraction of BF. The tensile and flexural strength of composites were first increased and then decreased with the increase of the mass fraction of BF. The regression analysis demonstrated that shear strength and thermal conductivity of the BF reinforced PP composites increased linearly up to the thermal conductivity of non-woven fabrics through a linear fitting. It was proven that the prediction model has great potential application as the technical guidance of producing the non-woven fabrics and their composites in the automotive industry. Highlights: PP composites were prepared from BF via nonwoven and compression molding process. Effect of BF fractions on thermal conductivity of nonwoven and composites. Mechanical properties of BF/PP nonwoven fabrics and composites were reported. Gas permeability of BF/PP nonwoven fabrics and composites were revealed. Relationship between sample properties was predicted by regression analysis.