Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization

Open Access

Year : 2024 | Volume : | : | Page : –
By

Jai Rajesh.P

V.Balambica

M.Achudhan

  1. Research Scholar Department of Mechatronics, Bharath Institute of Higher Education and Research, Selaiyur, Chennai Tamil Nadu India
  2. Professor Department of Mechanical, Bharath Institute of Higher Education and Research, Selaiyur Tamil Nadu India
  3. Associate Professor Department of Mechanical, Bharath Institute of Higher Education and Research, Selaiyur, Chennai Tamil Nadu India

Abstract

This work aims to provide an optimization of meta-heuristic algorithms in order to improve the dynamic behavior of composite materials utilized in various practical engineering tasks. Based on the Comprehensive literature review it has been observed that composite sandwich panels with PVC foam cores accomplished mechanical characteristics superior than those ones that were produced on PU foam core mainly in flexural, compression, and impact tests Thus the study establishes the basis of the current work on the best possible machining parameters for PVC foam so as to boost its mechanical properties. The results of testing PVC foam using mechanical tests showed higher values for flexural strength, compression strength, and impact resistance of PVC over that of PU foams. On the other hand, the random forest regression had the best fitting models for machining parameters, with its unbiased mean squared error (MSE) and the highest R2 (coefficient of determination) of all the algorithms. Along with the meta heuristic algorithms like Particle Swarm Optimization (PSO), Firefly Algorithm, Cuckoo Search, Grey Wolf Optimizer (GWO), Multi Objective Teaching Learning based Optimization Algorithm (MOTLBO), and Salp Swarm Algorithm that were used to optimize machining parameters, the GWO (Grey Wolf Optimizer) method appeared to have the best results. The uniqueness of this research is due to the advent of its holistic strategy which integrate data obtained from the earlier works and experimental study to arrive at the machining parameters for PVC foam. Through the application of the advanced regression analysis methods and meta heuristic optimization algorithms, the study achieves a great impact on the predictive effectiveness and efficiency of the composite materials dynamics optimization, resulting in a more effective improvement of the dynamic performance. The main aim of this research work is the promotion of composite material design techniques by offering practical guidelines and approaches for dynamic performance superiority which also enable the manufacturing of the lightest and sturdy with the highest performance engineering materials.

Keywords: Composite materials, Meta heuristic algorithms, PVC foam, Polyurethane foam, Machining parameters, Random forest, Grey Wolf Optimizer, Optimization, Engineering materials

How to cite this article: Jai Rajesh.P, V.Balambica, M.Achudhan. Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization. Journal of Polymer and Composites. 2024; ():-.
How to cite this URL: Jai Rajesh.P, V.Balambica, M.Achudhan. Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization. Journal of Polymer and Composites. 2024; ():-. Available from: https://journals.stmjournals.com/jopc/article=2024/view=146445

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Ahead of Print Open Access Original Research
Volume
Received March 31, 2024
Accepted April 16, 2024
Published May 16, 2024
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