Green Aircraft Morphing Elevator Aero Optimization through Evolutionary Algorithm and Radial Basis Functions

  • Romano, Diego Giuseppe (C.I.R.A. SCpA)
  • Quagliarella, Domenico (C.I.R.A. SCpA)
  • Minervino, Mauro (C.I.R.A. SCpA)
  • Montella, Nicolina (C.I.R.A. SCpA)

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This work presents the bi-dimensional (2D) aerodynamic design, based on numerical optimization, of a morphing elevator for the horizontal tailplane (HTP) of a future green aircraft, conceived to enhance aircraft efficiency across multiple flight conditions (cruise and low speed). The study focuses on developing a morphing concept to adapt its camber distribution, thereby improving efficiency characteristics, reducing trim drag for cruise condition, and improving lifting coefficient for low speed conditions. The aerodynamic analysis was carried-out using a 2D viscous–inviscid interaction code coupling an Euler solver for the inviscid outer flow, a boundary-layer solver for laminar, transitional, and turbulent regions, and a strong viscous–inviscid interaction scheme to ensure consistency between the two. The optimization tool uses a CMA-ES evolutionary algorithm [1] to drive geometry update made via Radial Basis Functions (RBFs) algorithm [2]. The results demonstrate that the optimized HTP achieves up to more than 110% efficiency improvement in cruise and over than 9% improvement in lift coefficient in low speed conditions, exhibiting delayed flow separation and improved pressure recovery, confirming aerodynamic benefits of continuous shape adaptation. The conclusions highlight that morphing technologies, when properly integrated into tailplane design, offer a promising pathway toward next generation aircraft with enhanced aerodynamic performance. The optimized designs will be used as target shape for structural analysis and optimization of the structural mechanism actuating the elevator. The activities described in this paper have been carried out within HERFUSE (Hybrid-Electric Regional FUSelage & Empennages) project; which has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101140567. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or of the granting authority. Neither the European Union nor the granting authority can be held responsible for them.