Multi-Objective Optimization of Carbonized False Banana Fiber/Fe3O4 Hybrid Composites for Lightweight Broadband Electromagnetic Absorption in UAV Applications

Nowadays, carbonized natural fiber composites are sustainable alternatives for electromagnetic wave absorption in unmanned aerial vehicles (UAVs). However, achieving a balance between electromagnetic performance, structural thickness, and weight is still difficult. This study, therefore, presents a multi-objective optimization framework for designing a lightweight radar-absorbing multilayer composite using a carbonized false banana fiber/Fe3O4 hybrid absorber. In this work, a four-layer sandwich panel was modeled in SOLIDWORKS 2017 and analyzed using full-wave electromagnetic simulation in ANSYS HFSS (R18.1) over the frequency range of 2–18 GHz. Layer thicknesses were optimized using a multi-objective particle swarm optimization (MOPSO) algorithm with three objectives: maximizing the frequency-averaged power absorptivity, minimizing panel mass, and minimizing total thickness. The objectives were handled simultaneously through Pareto dominance without predefined weighting coefficients, and a compromise solution was selected from the resulting Pareto-optimal set. The selected Pareto compromise was subsequently adjusted considering practical layer-thickness and manufacturability requirements, resulting in a 2/5/2/1 mm multilayer configuration with a total thickness of 10 mm. The resulting configuration achieved frequency-averaged power absorptivities of 0.6756 over 2–18 GHz and 0.8289 within the Ku-band, together with an effective absorption bandwidth of 3.2 GHz for power absorptivity above 90%. A minimum reflection coefficient magnitude of 0.0230 (corresponding to a peak power absorptivity of 99.95% at resonance) was obtained, with a minimum reflection loss of −32.75 dB. The optimized panel achieved a mass of 0.1725 kg, corresponding to a modest 1.42% reduction relative to an equal-footprint, equal-thickness monolithic carbon-fiber reference panel. These numerical results show the potential of combining a biomass-derived absorber with multi-objective optimization for the preliminary design of UAV-oriented radar-absorbing multilayer structures.