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Statistical Analysis and Predictive Learning of Mechanical Parameters for TiO2 Filled GFRP Composite

Authors: S. Srinivasa Moorthy, K. Manonmani

Abstract:

The new, polymer composites consisting of e-glass fiber reinforcement with titanium oxide filler in the double bonded unsaturated polyester resin matrix were made. The glass fiber and titanium oxide reinforcement composites were made in three different fiber lengths (3cm, 5cm, and 7cm), filler content (2 wt%, 4 wt%, and 6 wt%) and fiber content (20 wt%, 40 wt%, and 60 wt%). 27 different compositions were fabricated and a sequence of experiments were carried out to determine tensile strength and impact strength. The vital influencing factors fiber length, fiber content and filler content were chosen as 3 factors in 3 levels of Taguchi’s L9 orthogonal array. The influences of parameters were determined for tensile strength and impact strength by Analysis of variance (ANOVA) and S/N ratio. Using Artificial Neural Network (ANN) an expert system was devised to predict the properties of hybrid reinforcement GFRP composites. The predict models were experimentally proved with the maximum coincidence.

Keywords: Polymer composites, artificial neural network (ANN), Analysis of Variance (ANOVA), Taguchi’s orthogonal array

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1090713

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References:


[1] Shao - Yun Fu. "Effects of particle size, particle / matrix interface adhesion and particle loading on mechanical properties of particulate–polymer composites,” Science direct, composites part B, 2008, pp. 933-961.
[2] Srinivasa Moorthy. S, Manonmani. K. "Preparation and Characterization of Glass Fiber Reinforced Composite with TiO2 Particulate,” Sen-I Gakkaishi, Society of Fiber Science and Technology, Japan, Vol. 69, No. 8, 2013, pp. 154-158.
[3] Reynaud E, Jouen T, Gauthier C, Vigier G, Varlet J. "Nanofillers in polymeric matrix: a study on silica reinforced,” Polymer, Vol. 42, No. 87, 2001, pp. 59–68.
[4] Sabeel Ahmed, K. Vijayaranga, S. and Rajput, C. "Mechanical behavior of isothalic polyester based untreated woven jute and glass fabric hybrid composites,” Journal of Reinforced Plastics & Composites, Vol. 25, No. 15, 2006, pp. 1549-1569.
[5] Venkata Reddy, G., Venkata Naidu, S., Shobha Rani, T. and Subha, M.C.S. "Polyester composites compressive, chemical resistance, and thermal studies on kapok/sisal fabrics,” Journal of Reinforced Plastics & Composites, Vol. 28, 2009, pp. 1485-1494
[6] Panthapulakkal S. and Sain M. "Injection molded short hemp fiber/glass fiber-reinforced polypropylene hybrid composites-mechanical, water absorption and thermal properties,” Journal of Applied Polymer Science, Vol. 103, 2007,pp. 2432-2441.
[7] Tsaoa.C.C and Hocheng.H. "Taguchi analysis of de lamination associated with various drill bits in drilling of composite material,” International Journal of Machine Tools and Manufacture, 2004, pp. 1085-1090.
[8] Balamurugan Gopalsamy, Biswanathmondal, Sukumalghosh. "Taguchi method and ANOVA, an approach for process parameter optimization of hard machining,” Journal of Scientific and Industrial Research, Vol. 68, 2009,pp. 08.
[9] Dobrzanski. L. A, Domagala. J, Silva. J.F. "Application of Taguchi method in the optimization of filament winding of thermoplastic composites,” Archives of Material Science and Engineering, Vol. 28, 2007, pp. 133-140.
[10] Chang – chiunhuang and Tsanntay tang. "Parameter optimization in melt spinning by neural networks and genetic algorithms,” International Journal of Advanced Manufacturing Technology, Vol. 27, 2006, pp. 1113-1118.
[11] Lee.J.A, Almond D.P, Harris.B. "The use of neural networks in the prediction of the fatigue life of different composite materials,” Composites Part A:Applied science and Manufacturing, Vol. 30, 1999, pp. 1159-1169.
[12] Rajendraboopathy. S, Sasi Kumar. T., Usha. K. M, Vasudev. E.S. "Neural network prediction of failure strength of composite tensile specimens using acoustic emission Counts,” Journal of Non destructive Testing and Evaluation, Vol. 7, 2008, pp. 21-26.