Mathematical Modeling and MOPSO-Based Simulation of Natural Fiber Reinforced Polypropylene Composites for Damping Performance Validation

Polymer composites reinforced with natural fibers are increasingly being used due to their environmental friendliness, cost-effectiveness and superior damping properties. But the task of determining the best balance between stiffness and vibration damping presents a complex multi-objective problem. In this paper, a mathematical modeling and Multi-Objective Particle Swarm Optimization (MOPSO)-driven simulation approach is proposed to determine the optimal composition of Polypropylene (PP) composites reinforced with Jute, Sisal and Banana natural fibers. The developed model assesses the effects of different weight fractions on two contradictory objectives, Young's modulus and damping. The MOPSO algorithm is used to obtain a diversified set of Pareto-optimal solutions to determine the best compromise between stiffness and damping. The outcomes reveal that polypropylene plays a crucial role in improving the stiffness of the structure while the natural fibres, especially Jute and Banana, improve the damping factor as they dissipate energy, and Sisal contributes to both. Convergence studies and particle movements validate the stability, robustness and effectiveness of the optimization process. The results underline the role of hybrid composite design and multi-objective optimization in the development of composite materials with desired properties for engineered systems. The methodology offers a robust and scalable process for the development of sustainable and high-performance composites for vibration control and other applications.