Robust optimization of aerodynamic loadings for airfoil inverse designs

Abstract

For the modern design of more realistic aerodynamic shapes, disturbances caused by uncertain operating conditions must be conveniently considered, since they can affect significantly the performance of the designed systems. In this situation, the concept of robust design in conjunction with optimization tools is strongly recommended, since the interest is to maximize the performance and its robustness, simultaneously. Clearly, the great number of exact evaluations normally required to compute the robustness makes the robust optimization in aerodynamics computationally prohibitive, particularly when direct methods are chosen. To overcome this drawback, inverse methods appear as an interesting option, provided a robust aerodynamic loading can be furnished previously at low computational costs. However, few works have been dedicated to this subject in the open literature, which motivates the present study. The focus is to apply the robustness concept to optimize the velocity (or pressure) distributions for airfoil inverse designs, using a boundary layer method to predict the aerodynamic coefficients prior to the knowledge of the final airfoil shape. Here, the velocity distribution is parameterized using B-spline polygons with a set of control points, where the design variables are the ordinates of these points in the parameterization. The resulting robust multiobjective optimization problem involves the performance of the airfoil as a first objective function and its robustness introduced as additional objective to be optimized simultaneously. To illustrate the usefulness of the proposed robust design method, an example of drag minimization for an isolated airfoil is addressed and the aerodynamic coefficients for the optimal airfoils are compared with the corresponding obtained by experiments from the open literature.

Multi-network collaborative lift-drag ratio prediction and airfoil optimization based on residual network and generative adversarial network

“…The airfoil structure significantly influences the energy efficiency of wind power generation Sharma, Gupta, Pandey, Sharma, & Mishra (2021) . Due to the high cost of CFD calculation Koziel & Leifsson (2013) , - The aerodynamic performance optimization Bedon et al (2016) ; Chen and Li (2019) ; Kallath et al (2021) ; Mukesh et al (2012) ; Saleem and Kim (2020) ; Tang et al (2017) and robustness optimization Reis et al (2019) of Airfoil Based on CFD are limited. Therefore, optimizing the efficiency of airfoil structures has been a focus of research community.…”

Robust project of resonant shunt circuit for passive vibration control of composite structures

“…A natural extension of the deterministic modeling procedure is to account for the uncertainties in physical and/or Technical Editor: José Roberto de França Arruda. geometrical parameters, aiming at evaluating the degree of influence of variability on the performance predictions [10]. Such uncertainty propagation analysis becomes especially interesting for application involving shunt circuits, since the performance of such passive control strategy is strongly dependent on a certain number of parameters, among which, resistors and inductors are considered to be the most important and sensitive to small variations [11][12][13].…”

Application of reliability-based robust optimization in spacecraft attitude control with PWPF modulator under uncertainties

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