Biocomposite materials for structural applications are often made in the form of a thin layer called a lamina. Structural elements such as bars, beams or plates are generally formed by stacking the layers to achieve their desired overall strength and stiffness. These elements are called laminates. Natural fibre orientation in each lamina and stacking sequence of the layers in the laminate can be chosen to achieve the desired strength and stiffness for a specific application. It is therefore very important to model the experimental loading conditions as realistically as possible. One of the numerical calculations applied in various physical problems is the finite element model which plays a major role in calculating the stress and deformation of the structure, however, to validate the results obtained from this model, experimental results such as internal delamination and dissipated energies must be quantified. The single-layer equivalent model on the other side is usually adopted to simulate a multiply biocomposite laminate. The results obtained from this model reveal which stacking can cause the highest stiffness, and they describe the regions where higher stresses happened in the laminate biocomposites. It is important to find the better fibre direction and stacking sequence of the biocomposites. Moreover, fatigue modeling strategies are classified in four major categories: the macroscopic strength fatigue criteria, criteria based on residual strength, criteria based on residual stiffness, and finally criteria based on actual damage mechanisms, which describes the deterioration of biocomposite material in direct relation with specific damage such as transverse matrix cracks and delamination size, and quantitatively analyse the progression of actual damage mechanisms. These and the other forms of modeling will be discussed in details in this chapter.
CITATION STYLE
Linganiso, L. Z., Motaung, T. E., & Mochane, M. J. (2017). Modeling. In Biocomposites: Properties, Performance and Applications (pp. 299–308). Nova Science Publishers, Inc. https://doi.org/10.4018/jaeis.2010101301
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