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Regression modeling and particle swarm optimization of mechanical properties of potassium hydroxide pretreated Dharbai fiber-reinforced polyester composites

This paper aims at improving the mechanical properties of Dharbai fiber-reinforced polyester composites through surface modification of Dharbai fibers using potassium hydroxide alkali treatment. The fibers were subjected to alkali treatment as per full factorial design, and the composites were fabricated by reinforcing the treated fibers in polyester matrix. The response surface methodology was employed to study the effect of treatment parameters namely solution concentration (%) and soaking time (h) on the mechanical properties of Dharbai fiber-reinforced composites. The regression model was developed for correlating the interactions between solution concentrations and soaking time on the tensile, flexural, and impact strength of the composites. The results obtained confirmed that both solution concentration (%) and soaking time (h) play critical role in influencing the mechanical properties of Dharbai fiber-reinforced composites. The better treatment conditions for optimum mechanical properties were determined using heuristic optimization method called particle swarm optimization. The optimized value obtained using particle swarm optimization technique was validated using confirmation test, and the results were found to be significant.