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

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.

Design of the ONERA M6 wing by shape optimization under uncertainty

“…Geleneksel yöntemlerde sabit uçuş koşulları kullanılarak optimizasyon gerçekleştirilmektedir [7]. Fakat tasarımcının kontrol edebildiği veya kontrol edemediği durumlardan ötürü sabit kabul edilen uçuş koşullarında farklılıklar oluşmaktadır [16]. Bu durum da çözüm üretilen problem için belirsizliklerin oluşmasına sebebiyet vermektedir.…”

Toward the feasible solution of a long-lasting dynamic similitude problem

“…Most of the published literature on airfoil optimization deal with the problem of maximizing airfoil performance at a given flight condition. Fusi et al 23 compare the deterministic and robust optimization approaches to improve the aerodynamic design of helicopter airfoils with the goal of maximizing their lift to drag ratio. The robust approach shows the capability to reach the same mean performance of the deterministic one, but with a lower degradation of performance in other conditions considered through the uncertainty.…”

Robust optimization of the aerodynamic design of a helicopter rotor blade based on multi-fidelity meta-models

“…It has been observed in several works that MFMBO can reduce significantly the computational cost while keeping a satisfactory accuracy. [17][18][19][20] For instance, Gano et al 19 showed that MFMBO can save resources by 60%; Park et al 21 reported a cost saving of 86%. When analyzing MFMBO studies, we find that this treatment is related to three factors, namely, the type of fidelity, the multi-fidelity model, and the MFMBO strategy.…”