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Modeling Elastic Constants of Keratin-Based Hair Fiber Composite Using Response Surface Method and Optimization Using Grey Taguchi Method

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Advanced Engineering Optimization Through Intelligent Techniques

Abstract

Tensile modulus is an important mechanical property of any material which is responsible for the stiffness of the material. In the present study, experimental testing is done to know Young’s modulus and Poisson’s ratio of human hair-fiber-reinforced polyester composite. Response surface methodology (RSM) technique is used to obtain empirical relations for Young’s modulus and Poisson’s ratio in terms of fiber weight fraction and fiber length. ANOVA is carried out to check the significance of the developed models. Results showed that predictions made by RSM models are in good concurrence with experimental results. Optimization of fiber weight fraction and length is carried out using RSM, and highest Young’s modulus value of 4.062 GPa was observed at 19.95% fiber volume fraction and 29.32 mm fiber length. Multi-response optimization is carried using grey Taguchi method. Optimized factor levels using grey Taguchi method are obtained as 20% and 30 mm for fiber weight fraction and fiber length respectively.

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Acknowledgements

My sincere gratitude to Dr. P. Ravinder Reddy, Professor and Principal, CBIT, Hyderabad, India, for providing laboratory support. Grateful acknowledgments are made to Stat-Ease for providing software support to carry out RSM.

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Correspondence to P. Divakara Rao .

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Divakara Rao, P., Udaya Kiran, C., Eshwara Prasad, K. (2020). Modeling Elastic Constants of Keratin-Based Hair Fiber Composite Using Response Surface Method and Optimization Using Grey Taguchi Method. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_26

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