INTERFACIAL AND TENSILE PROPERTIES OF HYBRID FRP COMPOSITES USING DNN STRUCTURE WITH OPTIMIZATION MODEL

Ahmed Abdul Baseer (), D. V. Ravi Shankar and M. Manzoor Hussain
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Ahmed Abdul Baseer: Jawaharlal Nehru Technological University, Hyderabad, India
D. V. Ravi Shankar: TKR College of Engineering & Technology, India
M. Manzoor Hussain: Department of Mechanical Engineering, JNTUH College of Engineering, India

Surface Review and Letters (SRL), 2020, vol. 27, issue 02, 1-11

Abstract: Fiber reinforced polymer (FRP) composites are appealing for use in structural building applications because of their high strength-to-weight and stiffness-to-weight proportions, corrosion resistance, lightweight, possibly high durability, along with free design characteristics. The aim of this research work was to develop high strength natural fiber-based composite plates for the possible application in the shear strengthening of the reinforced concrete structure. In the experimental modeling, the composites were fabricated using glass, flax and kenaf fibers in treated and untreated conditions. This paper studied and analyzed the interfacial and tensile properties of fiber reinforced hybrid composites such as flax/glass and kenaf/glass by using the simulation approach, i.e. Deep Neural Network (DNN) with weight optimization. For optimizing the weights in DNN, Oppositional based FireFly Optimization (OFFO) is proposed. All the optimal results exhibit in the way that the accomplished error values between the output of the experimental values and the predicted qualities are firmly equivalent to zero in the designed system.

Keywords: Fiber reinforced polymer; hybrid fiber composites; tensile and interfacial; FFBN and FFSO algorithm (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0218625X19500999

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