STRUCTURAL DESIGN OF NEXT-GENERATION REGIONAL GREEN AIRCRAFT

The aviation industry is increasingly focused on developing next-generation green aircraft to mitigate environ- mental impacts. This study addresses the limitations of traditional weight estimation methods (Class I & II) in the context of innovative aircraft designs, particularly focusing on the wing-box structure. The conceptual design of three distinct aircraft configurations, a reference regional aircraft, a hybrid-electric aircraft, and a full-electric aircraft, utilizes HEAD (Hybrid-Electric Aircraft Design), an internally developed software at the University of Naples Federico II. This study introduces a novel Class III weight estimation approach, developed at Sapienza University of Rome, integrating Finite Element Analysis (FEA) capabilities. This method facilitates rapid generation of detailed FEM models, crucial for Multidisciplinary Design Optimization (MDO) loops. Automated aeroelastostatic and buck- ling analyses are conducted to ensure structural integrity under varied flight conditions, while accurate modeling of composite materials like Carbon Fiber Reinforced Plastic (CFRP) enhances realistic weight predictions. Utilizing the developed Class III approach, this study optimizes the wing-box structure of the concepts devel- oped with HEAD and emphasizes the differences in terms of structural weight. Results demonstrate significant weight reductions in optimized wing-box structures while maintaining structural integrity compared to the initial guess oversized FEM. Key optimization strategies include exploring design variables (e.g., ply thickness, spar cap width, stringer dimensions) using a genetic algorithm. Notably, tapering thickness along the wing-box’s spanwise direction is crucial in achieving these weight reductions. Comparison with HEAD software’s structural mass estimations reveals good correlation for the wing-box, with differences noted in lighter (ICE and ICE+BAT) and heavier (PEMFC+BAT) configurations. Larger discrepan- cies are evident in unoptimized components like the fuselage and tail, highlighting areas for future refinement.