Mechanical properties of starch-grafted-polypropylene/kenaf fibers (KF) composites were investigated and compared to different theoretical models. In this work, the composites were prepared via melt compounding and compression molding processes at different KF loadings, that is, 10, 20, and 30 wt%. Tensile, fracture toughness and fatigue tests were performed. Generally, the mechanical properties increased with increasing kenaf fiber loadings. This is attributed to the good filler-matrix interactions between KF and starch-grafted-polypropylene, as observed by scanning electron microscopy. Tensile properties were modeled using the rule of mixture, the Kelly-Tyson and the Halpin-Tsai models. Fatigue data were also modeled using different theoretical models to fit both S–N and normalized S–N curves with simple linear model and Boltzmann sigmoidal function. © 2017 Society of Plastics Engineers
Experimental analysis and theoretical modeling of the mechanical behavior of starch-grafted-polypropylene/kenaf fibers composites / Phua, Y. J.; Pegoretti, A.; Mohd Ishak, Z. A.. - In: POLYMER COMPOSITES. - ISSN 0272-8397. - STAMPA. - 39:11(2018), pp. 3289-3299. [10.1002/pc.24344]
Experimental analysis and theoretical modeling of the mechanical behavior of starch-grafted-polypropylene/kenaf fibers composites
Phua, Y. J.;Pegoretti, A.;
2018-01-01
Abstract
Mechanical properties of starch-grafted-polypropylene/kenaf fibers (KF) composites were investigated and compared to different theoretical models. In this work, the composites were prepared via melt compounding and compression molding processes at different KF loadings, that is, 10, 20, and 30 wt%. Tensile, fracture toughness and fatigue tests were performed. Generally, the mechanical properties increased with increasing kenaf fiber loadings. This is attributed to the good filler-matrix interactions between KF and starch-grafted-polypropylene, as observed by scanning electron microscopy. Tensile properties were modeled using the rule of mixture, the Kelly-Tyson and the Halpin-Tsai models. Fatigue data were also modeled using different theoretical models to fit both S–N and normalized S–N curves with simple linear model and Boltzmann sigmoidal function. © 2017 Society of Plastics EngineersFile | Dimensione | Formato | |
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