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Bio-inspired flow control strategies can provide a new paradigm of efficiency and adaptability to overcome the operational limitations of traditional flow control. This is particularly useful to small-scale uncrewed aerial vehicles since their mission requirements are rapidly expanding, but they are still limited in terms of agility and adaptability when compared to their biological counterparts, birds. One of the flow control strategies that birds implement is the deployment of covert feathers. In this study, we investigate the performance characteristics and flow physics of torsionally hinged covert-inspired flaps mounted on the suction side of a NACA2414 airfoil across different Reynolds numbers, specifically 200,000 and 1,000. These two Reynolds numbers are representative of different avian flight regimes where covert feathers have been observed to deploy during flight, namely cruising and landing/perching. We performed experiments and simulations where we varied the flap location, the hinge stiffness, and the moment of inertia of the flap to investigate the aerodynamic performance and describe the effects of the structural parameters of the flap on the aerodynamic lift improvements. Results of the study show up to 12% lift improvement post-stall for the flapped cases when compared to the flap-less baseline. The post-stall lift improvement is sensitive to the flap’s structural properties and location. For instance, the hinge stiffness controls the mean deflection angle of the flap, which governs the resulting time-averaged lift improvements. The flap moment of inertia, on the other hand, controls the flap dynamics, which in turn controls the flap’s lift-enhancing mechanism and how the flap affects the instantaneous lift. By examining the time-averaged and instantaneous lift measurement, we uncover the mechanisms by which the covert-inspired flap improves lift and highlights similarities and differences across Reynolds numbers. This article highlights the feasibility of using covert-inspired flaps as flow control across different flight missions and speeds.

 

A bio-inspired, passively deployable flap attached to an airfoil by a torsional spring of fixed stiffness can provide significant lift improvements at post-stall angles of attack. In this work, we describe a hybrid active–passive variant to this purely passive flow control paradigm, where the stiffness of the hinge is actively varied in time to yield passive fluid–structure interaction of greater aerodynamic benefit than the fixed-stiffness case. This hybrid active–passive flow control strategy could potentially be implemented using variable-stiffness actuators with less expense compared with actively prescribing the flap motion. The hinge stiffness is varied via a reinforcement-learning-trained closed-loop feedback controller. A physics-based penalty and a long–short-term training strategy for enabling fast training of the hybrid controller are introduced. The hybrid controller is shown to provide lift improvements as high as 136 % and 85 % with respect to the flapless airfoil and the best fixed-stiffness case, respectively. These lift improvements are achieved due to large-amplitude flap oscillations as the stiffness varies over four orders of magnitude, whose interplay with the flow is analysed in detail. 

Covert feathers are a set of self-actuating, passively deployable feathers located on the upper surfaces of wings that augment lift at post-stall angles of attack. Due to these benefits, the study of covert-inspired passive flow control devices is becoming an increasingly active area of research. In this work, we numerically investigate the aerodynamic benefits of torsionally mounting five covert-inspired flaps on the upper surface of a NACA0012 airfoil. Two-dimensional high-fidelity simulations of the flow past the airfoil–flap system at low Re=1000 and a high angle of attack of 20∘ were performed. A parametric study was conducted by varying the flap moment of inertia and torsional hinge stiffness to characterize the aerodynamic performance of this system. Lift improvements as high as 25% were attained. Two regimes of flap dynamics were identified that provided considerable aerodynamic benefits. A detailed investigation of the flow physics of both these regimes was conducted to understand the physical mechanisms by which the passively deployed flaps augmented the lift of the airfoil. In both regimes, the flap was found to act as a barrier in preventing the upstream propagation of reverse flow due to flow separation and trailing edge vortex. The torsional spring and flap inertia yielded additional flap dynamics that further modulated the surrounding flow and associated performance metrics. We discuss some of these fluid–structure interaction effects in this article. 

State estimation is key to both analysing physical mechanisms and enabling real-time control of fluid flows. A common estimation approach is to relate sensor measurements to a reduced state governed by a reduced-order model (ROM). (When desired, the full state can be recovered via the ROM.) Current methods in this category nearly always use a linear model to relate the sensor data to the reduced state, which often leads to restrictions on sensor locations and has inherent limitations in representing the generally nonlinear relationship between the measurements and reduced state. We propose an alternative methodology whereby a neural network architecture is used to learn this nonlinear relationship. A neural network is a natural choice for this estimation problem, as a physical interpretation of the reduced state–sensor measurement relationship is rarely obvious. The proposed estimation framework is agnostic to the ROM employed, and can be incorporated into any choice of ROMs derived on a linear subspace (e.g. proper orthogonal decomposition) or a nonlinear manifold. The proposed approach is demonstrated on a two-dimensional model problem of separated flow around a flat plate, and is found to outperform common linear estimation alternatives.