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Birds perform astounding aerial maneuvers by actuating their shoulder, elbow, and wrist joints to morph their wing shape. This maneuverability is desirable for similar-sized uncrewed aerial vehicles (UAVs) and can be analyzed through the lens of dynamic flight stability. Quantifying avian dynamic stability is challenging as it is dictated by aerodynamics and inertia, which must both account for birds’ complex and variable morphology. To date, avian dynamic stability across flight conditions remains largely unknown. Here, we fill this gap by quantifying how a gull can use wing morphing to adjust its longitudinal dynamic response. We found that it was necessary to adjust the shoulder angle to achieve trimmed flight and that most trimmed configurations were longitudinally stable except for configurations with high wrist angles. Our results showed that as flight speed increases, the gull could fold or sweep its wings backward to trim. Further, a trimmed gull can use its wing joints to control the frequencies and damping ratios of the longitudinal oscillatory modes. We found a more damped phugoid mode than similar-sized UAVs, possibly reducing speed sensitivity to perturbations, such as gusts. Although most configurations had controllable short-period flying qualities, the heavily damped phugoid mode indicates a sluggish responsemore »to control inputs, which may be overcome while maneuvering by morphing into an unstable flight configuration. Our study shows that gulls use their shoulder, wrist, and elbow joints to negotiate trade-offs in stability and control and points the way forward for designing UAVs with avian-like maneuverability.« less

Abstract Some bird species exhibit a flight behavior known as whiffling, in which the bird flies upside-down during landing, predator evasion, or courtship displays. Flying inverted causes the flight feathers to twist, creating gaps in the wing’s trailing edge. It has been suggested that these gaps decrease lift at a potentially lower energy cost, enabling the bird to maneuver and rapidly descend. Thus, avian whiffling has parallels to an uncrewed aerial vehicle (UAV) using spoilers for rapid descent and ailerons for roll control. However, while whiffling has been previously described in the biological literature, it has yet to directly inspire aerodynamic design. In the current research, we investigated if gaps in a wing’s trailing edge, similar to those caused by feather rotation during whiffling, could provide an effective mechanism for UAV control, particularly rapid descent and banking. To address this question, we performed a wind tunnel test of 3D printed wings with a varying amount of trailing edge gaps and compared the lift and rolling moment coefficients generated by the gapped wings to a traditional spoiler and aileron. Next, we used an analytical analysis to estimate the force and work required to actuate gaps, spoiler, and aileron. Our results showedmore »that gapped wings did not reduce lift as much as a spoiler and required more work. However, we found that at high angles of attack, the gapped wings produced rolling moment coefficients equivalent to upwards aileron deflections of up to 32.7° while requiring substantially less actuation force and work. Thus, while the gapped wings did not provide a noticeable benefit over spoilers for rapid descent, a whiffling-inspired control surface could provide an effective alternative to ailerons for roll control. These findings suggest a novel control mechanism that may be advantageous for small fixed-wing UAVs, particularly energy-constrained aircraft.« less

Smooth camber morphing aircraft offer increased control authority and improved aerodynamic efficiency. Smart material actuators have become a popular driving force for shape changes, capable of adhering to weight and size constraints and allowing for simplicity in mechanical design. As a step towards creating uncrewed aerial vehicles (UAVs) capable of autonomously responding to flow conditions, this work examines a multifunctional morphing airfoil’s ability to follow commands in various flows. We integrated an airfoil with a morphing trailing edge consisting of an antagonistic pair of macro fiber composites (MFCs), serving as both skin and actuator, and internal piezoelectric flex sensors to form a closed loop composite system. Closed loop feedback control is necessary to accurately follow deflection commands due to the hysteretic behavior of MFCs. Here we used a deep reinforcement learning algorithm, Proximal Policy Optimization, to control the morphing airfoil. Two neural controllers were trained in a simulation developed through time series modeling on long short-term memory recurrent neural networks. The learned controllers were then tested on the composite wing using two state inference methods in still air and in a wind tunnel at various flow speeds. We compared the performance of our neural controllers to one using traditional position-derivativemore »feedback control methods. Our experimental results validate that the autonomous neural controllers were faster and more accurate than traditional methods. This research shows that deep learning methods can overcome common obstacles for achieving sufficient modeling and control when implementing smart composite actuators in an autonomous aerospace environment.

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Abstract Forpractical considerations reinforcement learning has proven to be a difficult task outside of simulation when applied to a physical experiment. Here we derive an optional approach to model free reinforcement learning, achieved entirely online, through careful experimental design and algorithmic decision making. We design a reinforcement learning scheme to implement traditionally episodic algorithms for an unstable 1-dimensional mechanical environment. The training scheme is completely autonomous, requiring no human to be present throughout the learning process. We show that the pseudo-episodic technique allows for additional learning updates with off-policy actor-critic and experience replay methods. We show that including these additional updates between periods of traditional training episodes can improve speed and consistency of learning. Furthermore, we validate the procedure in experimental hardware. In the physical environment, several algorithm variants learned rapidly, each surpassing baseline maximum reward. The algorithms in this research are model free and use only information obtained by an onboard sensor during training.

Structural health monitoring of fiber reinforced composites is an extensive field of research that aims to reduce maintenance costs through in-situ damage detection. However, the need for externally bonded sensor systems and complicated fabrication processes limit the widespread application of most current structural health monitoring techniques. This work introduces a novel multifunctional fiber reinforced composite that relies on a ferroelectric prepreg fabricated using dehydrofluorinated (DHF) polyvinylidene fluoride (PVDF), which exhibits a thermally stable piezoelectric response. The self-sensing material presented in this work requires minimal external components, as the piezoelectric sensing mechanism is fully contained within the composite. This is accomplished by fabricating a ferroelectric prepreg consisting of DHF PVDF infused woven fiberglass, which is sandwiched between woven carbon fabric layers that act as electrodes, thus forming a piezoelectric sensor fabricated with entirely structural composite materials. Notably, the sensing material is a fully distributed prepreg rather than discretely embedded sensors which enables simplified monitoring of complex structures. As the composite experiences damage under flexural and tensile loading, the internal change in strain results in a charge separation that is detectable as a voltage emission across the sample electrodes. The self-sensing capabilities of this material are explored using traditional mechanical testing techniques,more »showing comparable performance to common damage detection methods, all while eliminating the need for external bonding of sensors to the structure.« less

The continuous monitoring of strain in fiber-reinforced composites while in service typically requires bonding a network of sensors to the surface of the composite structure. To eliminate such needs, and to reduce bulk and limit additional weight, this work utilizes the transfer printing of laser induced graphene (LIG) strain gauges onto the surface of commercial fiberglass prepreg for the in situ self-sensing of strain. The resultant embedded strain sensor is entirely integrated within the final composite material, therefore reducing weight and eliminating limitations due to external bonding compared to current alternatives. Additionally, the simple printing process used here allows for the customization of the size and sensing requirements for various applications. The LIG strain sensor is shown to be capable of tracking monotonic cyclic strain as shown during tensile loading and unloading of the host composite, while also proving capable of tracking the dynamic motion of the composite which is characterized via frequency response and sinusoidal base excitation. The LIG strain gauge in this work can thus be used for tracking either quasi-static or dynamic variations in strain for the determination of the deformation experienced by the material, as well as the frequency content of the material for structural healthmore »monitoring purposes.« less

Fiberglass-reinforced composite materials are commonly used in engineering structures subjected to dynamic loading, such as wind turbine blades, automobiles, and aircraft, where they experience a wide range of unpredictable operating conditions. The ability to monitor these structures while in operation and predict their remaining structural life without requiring their removal from service has the potential to drastically reduce maintenance costs and improve reliability. This work exploits piezoresistive laser induced graphene (LIG) integrated into fiberglass-reinforced composites for in-situ fatigue damage monitoring and lifespan prediction. The LIG is integrated within fiberglass composites using a transfer-printing process that is scalable with the potential for automation, thus reducing barriers for widespread application. The addition of the conductive LIG within the traditionally insulating fiberglass composites enables direct in-situ damage monitoring through simple passive resistance measurements during tension-tension fatigue loading. The accumulation and propagation of structural damage are detected throughout the fatigue life of the composite through changes to the electrical resistance measurements, and the measurement trends are further used to predict the onset of catastrophic composite failure. Thus, this work results in a scalable and multifunctional composite material with self-sensing capabilities for potential use in high-performing, dynamic, and flexible composite structures.

Gliding birds perform feats that challenge even our most advanced similar-sized unmanned aerial vehicles (UAV). Their ostensible skill supports a pervasive belief that birds are highly efficient gliders that outperform modern UAVs. which led us to ask: are gliding birds truly more efficient than UAVs? Avian flight efficiency a well-studied topic and often cited as the inspiration for novel UAV designs. Despite the multitude of studies that have quantified the aerodynamic efficiency of gliding birds, there is no comprehensive summary of their findings. This is problematic because differing methodologies have inconsistent levels of uncertainty. As such, the lack of consolidated information on gliding bird efficiency inhibits a true comparison to UAVs. To fill this gap, we surveyed published theoretical and experimental estimates of avian aerodynamic efficiency and investigated the uncertainty of each method. We found that there was substantial variation in the aerodynamic efficiency predicted by different methods, which can lead to disparate conclusions on gliding bird efficiency. Our survey showed that measurements on live birds gliding in wind tunnels provide a reliable minimum estimate on a birds’ aerodynamic efficiency and allows the quantification of the wing configurations used in flight. Next, we surveyed the aeronautical literature to collect allmore »published aerodynamic efficiencies of similar-sized, non-copter UAVs. The consolidated information allowed a direct comparison of modern UAVs and gliding birds. Contrary to our expectation, we found that there is no definitive evidence that any gliding bird species is either more or less efficient than a similar-sized UAV. This non-result highlights a critical need for new technology and analytical advances that can reduce the uncertainty associated with estimating a gliding bird’s aerodynamic efficiency. Nevertheless, our survey indicated that UAV designs informed by species flying within subcritical regimes may extend their operational range into lower Reynolds number regimes.« less

Current in situ piezoresistive damage detection techniques for fiberglass-reinforced composites are limited in widespread application as they require complex processing techniques which inhibit the scalability of the methods. To eradicate such challenges and expand the use of piezoresistive monitoring of fiberglass composites, this work utilizes a simple, scalable process to coat electrically insulating commercial fiberglass prepreg with piezoresistive laser induced graphene (LIG) for the detection and localization of damage. Recently, LIG has attracted substantial research attention due to the simplicity of the methodology and the piezoresistance of the LIG. Here, the LIG is transfer printed onto commercial fiberglass prepreg which is subsequently used to localize damage in all three dimensions of the resultant fiberglass-reinforced composites while also maintaining the structural properties of the composites. A combination of in situ and ex-situ resistance measurements are used to accomplish this objective: First, in situ measurements are used to determine the relative location of damage in one-dimension under tensile loading. Subsequently, separate in situ measurements are used to locate damage through the thickness under flexural loading. Finally, ex-situ methods are used to calculate the two-dimensional location of a hole in a plate. The LIG is found to reliably and accurately localize the damagemore »to the composite in each case thus demonstrating for the first time that transfer printed LIG enables self-sensing of damage location in fiberglass composites. The result of this work is thus a multifunctional material capable of locating damage in all three-dimensions which is notably fabricated using commercial materials and scalable methodology.« less