Predictive modeling and multi-objective optimization of mechanical properties of date palm fiber bio-composites

This study develops a comprehensive methodology to optimize the mechanical properties of epoxy-based bio-composites reinforced with date palm fibers. Thermal and morphological analyses characterized the fibers and composites, revealing their stability and micro structural features that contribute to reinforcement. Mechanical testing evaluated the influence of fiber size and fiber mass ratio on flexural modulus, impact strength, and surface hardness, showing that carefully selecting these parameters significantly enhances mechanical performance while moderately reducing hardness. Quadratic polynomial regression models were formulated as functions of fiber size and mass ratio, and their accuracy was verified through residual analysis and analysis of variance. The precision of these models, assessed by comparing predicted and experimentally measured values, remained within 6.5%, demonstrating reliable predictive capability. The models facilitated the formulation of a multi-objective optimization problem aimed at maximizing impact strength while minimizing hardness loss under a flexural modulus constraint. A multi-objective particle swarm optimization algorithm identified Pareto-optimal solutions, which were experimentally validated with deviations not exceeding 4.09% , confirming the trustworthiness of the predicted front. The optimization results highlighted the trade-offs between conflicting objectives and demonstrated the effectiveness of the methodology in achieving balanced mechanical performance.