Publication: Attaining material sustainability by incorporating nanoparticles additives to improve the mechanical properties of polypropylene composites: Data driven modelling
Date
2021
Authors
Alsaffar M.A.
Ali J.M.
Abdel Ghany M.A.
Ayodele B.V.
Journal Title
Journal ISSN
Volume Title
Publisher
IOP Publishing Ltd
Abstract
Polypropylene is commonly employed in several industrial applications such as packaging, cable insulation and automotive. Research interest has focused on how to improve its mechanical properties to reduce the effect of low impact toughness of polypropylene. One of the sustainable ways to achieve this is by incorporating graphene nanoplatelets to form a composite. This study investigates the application of a hybrid support vector machine (SVM) and artificial neural networks (ANN) model to predict the effect of incorporating graphene on the mechanical properties of polyproline composites. The effect of parameters such as maleic anhydride grafted polypropylene (MAPP), Talc, and exfoliated graphene nanoplatelets on the tensile strength and modulus of the polypropylene composites was modelled by using ANN. Testing various topologies was accomplished. An optimized ANN structure of 3-7-2 indicating 3 input-layer, 7 hidden layer, and 2 output-layer was tested. Both the SVM and the ANN predict well the mechanical properties of polyproline composites. However, the ANN with R2 of 0.999 offers the best predictions. � Published under licence by IOP Publishing Ltd.
Description
Additives; Forecasting; Graphene; Graphene Nanoplatelets; Neural networks; Planning; Plastic products; Support vector machines; Sustainable development; Tensile strength; Toughness; Cable insulation; Data driven modelling; Effect of parameters; Hybrid support vector machines; Maleic anhydride grafted polypropylene; Nanoparticles additives; Polypropylene composite; Research interests; Polypropylenes