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Assessment of robust optimization for design of rotorcraft airfoils in forward flight

Francesca Fusi 1 Pietro Marco Congedo 2, 3 Alberto Guardone 1 Giuseppe Quaranta 1
2 PLATON - Uncertainty Quantification in Scientific Computing and Engineering
CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique, Inria Saclay - Ile de France
3 DeFI - Shape reconstruction and identification
Inria Saclay - Ile de France, CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique
Abstract : The paper compares the deterministic and robust approaches to improve the aerodynamic design of helicopter airfoils. The two formulations are different due to the characteristics of each approach. In the deterministic case, the objective of optimization is the minimization of drag while maintaining a level of lift that guarantees satisfaction of trimming condition. In the case of robust design, a range of angles of attack and not a single trim condition is considered. Thus, the robust optimization takes the lift-to-drag ratio as a measure of the performance of the airfoil, imposing at the same time inequality constraint on the lift coefficient to guarantee a sufficient level of lift, and then checking after optimization that the trimming condition can be satisfied. The two approaches are compared showing pros and cons of the robust framework. In general, the robust approach shows the capability to reach the same mean performance of the deterministic one, but with a lower degradation of performances in off-design situations considered through the uncertainty. On the other side, the difficulties in imposing the lift trim condition for the robust formulation may lead to results of limited use.
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Submitted on : Tuesday, December 8, 2020 - 10:38:05 AM
Last modification on : Saturday, May 1, 2021 - 3:38:56 AM
Long-term archiving on: : Tuesday, March 9, 2021 - 6:31:36 PM


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Francesca Fusi, Pietro Marco Congedo, Alberto Guardone, Giuseppe Quaranta. Assessment of robust optimization for design of rotorcraft airfoils in forward flight. Aerospace Science and Technology, Elsevier, 2020, 107, pp.106355. ⟨10.1016/j.ast.2020.106355⟩. ⟨hal-03045531⟩



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