Wing UAV Research Articles

Rationale for choosing the airfoil of a UAV wing using a dynamic ground effect principle

Vehicles that use the principle of dynamic ground effect principle are innovative vehicles that have prospects for use as high-speed unmanned vehicles. It is known that when an aircraft moves near the ground, the phenomenon of increasing lift occurs, which allows for contactless movement at high speeds. However, the effectiveness of this ground effect depends on the airfoil shape. The object of this study is the aerodynamic processes that occur during the movement of an unmanned aerial vehicle near the ground. The influence of the effect of approaching the ground on the aerodynamic characteristics of four airfoil of different shapes has been considered: Clark YH-12, NACA-M6, USA-35B, TsAGI-721, which are used in subsonic high-speed aircraft, including unmanned aerial vehicles. The aim of the work is to evaluate the performance of these aerodynamic airfoils in near-surface operation and to determine the most promising shape for use in small unmanned WIGs. CFD modeling methods were used as a research tool. The pressure and velocity fields around the wing airfoils were determined and the influence of the distance to the ground and the angle of attack on the aerodynamic characteristics was established. It was found that the best aerodynamic quality for all airfoils is achieved at angles of attack of 4–6°. It is not recommended to use airfoils with angles of attack close to 0° as the ground may have a negative effect on lift. The USA-35B airfoil demonstrated the greatest increase in aerodynamic quality when approaching the surface, with a maximum increase of 67 %. This makes it possible to recommend USA-35B as small unmanned aerial vehicles with a dynamic ground effect principle

Building Footprint Extraction from Fixed-Wing UAV Imagery using Mask R-CNN and Object-based Image Analysis Methods (Case Study: Banturejo Village, Malang Regency)

Abstract As a developing area in Malang Regency, Banturejo Village has many potencies since its location near the tourism area of Selorejo Dam. To maximally the harness of potencies while maintaining efficient land use in Banturejo village, mapping the built area in large scale should be carried out. The photogrammetric techniques using fixed-wing UAV could be a good alternative for large-scale mapping in this village area because of its capability to quickly acquire high resolution image with highly customizable mission specifications. But the problem arises in interpreting these imagery into meaningful cartographic representation which often requires cautious manual digitization in much slower rate that its acquisition. In this research the automatic image analysis method for building footprint extraction using Mask R-CNN algorithm and Object-Based Image Analysis was performed. The fixed wing UAV imagery was captured in 2023 and the structure from motion algorithm was employed for photogrammetric processing which produced 10-cm resolution orthophoto. Manually digitized building polygons from the same imagery serve as the gold standard for accuracy analysis, and small proportion of the data was used as training samples for the algorithm. The results shows that 1447 buildings with total area of 180,595 m2 was generated with Mask R-CNN algorithm, while OBIA-Mask R-CNN produced 572 buildings and total area of 201,932 m2. The confusion matrices reveal precision value of 77.94%, recall 51.54%, F1 Score 62.02% by Mask R-CNN method, and precision value of 35.95%, recall 9.21%, F1 Score 14.66% by OBIA-Mask RCNN method. Mask R-CNN method generated slightly lower accuracy of total building area, but in terms of precision the OBIA-Mask RCNN method produces lower number of building polygons.

Modeling and Transition Flight Control of Distributed Propulsion–Wing VTOL UAV with Induced Wing Configuration

The integration of propulsion and wing in distributed propulsion–wing UAVs (DPW UAVs) introduces significant propulsion-aerodynamic coupling, complicating dynamic modeling and flight control. This complexity is heightened by using induced wing surfaces for vertical takeoff and landing, requiring controllers to adapt to configuration changes and disturbances during transition flight. This paper develops a propulsion-aerodynamic coupling model for a medium-sized DPW UAV with induced wings (DPW-IW), enabling real-time aerodynamic performance calculations. Furthermore, a unified flight-control framework is proposed to avoid controller scheduling and switching during flight mode transitions. The proposed control framework employs the time-scale separation principle, divided into an outer loop and an inner loop. The outer loop uses a fuzzy controller to adjust allocation parameters, while the inner loop applies incremental nonlinear dynamic inversion (INDI) and control allocation (INCA) methods, providing robustness to nonlinear changes during flight transitions. Finally, simulations under various conditions demonstrate the controller’s effectiveness in ensuring smooth and robust transitions.

Numerical Investigation of Advanced Composite Materials for Enhanced Structural Performance and Aerodynamic Efficiency of UAV Wings

In this research, the deficiencies in structural performance and aerodynamic performance of UAV wings fabricated with conventional materials have been investigated to identify how composite material can improve them. A quantitative study using CFD, FSI, and modal analysis is used to evaluate the AAI Shadow-200 RQ-7 UAV wings performance. With SOLIDWORKS for the geometry of the structures and ANSYS for the simulations, the performance of Epoxy Carbon UD Prepreg and Epoxy/glass fiber UD prepreg QI composites are compared to that of the conventional aluminum. The results reveal that the use of Epoxy/glass fiber UD prepreg QI offers the best safety factor, least deformation, and a greatly enhanced load carrying capacity. This research has added significant knowledge into the improvement of UAV wing design, the enhancement of the use of composite material in aerospace engineering, and has given a sound framework for the design of the next generation UAVs.

Aeroelastic wave attenuation of UAV wing with smart metamaterial resonators

This paper proposes a UAV wing based on smart metamaterial resonators (smart meta-wing), and studies its vibration wave attenuation under aerodynamic loads. A novel aeroelastic transfer matrix, incorporating aerodynamic effects, is developed to analyze the wave propagation. The study examines the influence of smart resonators on the coupled flexural-torsional wave attenuation with and without aerodynamic effects. The findings reveal that a new bandgap (aeroelastic bandgap) is formed along with local bandgap (SR bandgap), effectively attenuating both flexural and torsional waves. Additionally, the bandgap behavior can be actively tuned by varying the control gain of smart resonators. The proposed smart meta-wing model and aeroelastic transfer matrix offer a novel approach for actively attenuating the aeroelastic vibration waves of UAV wings for desired frequency range.

Advanced Cooperative Formation Control in Variable-Sweep Wing UAVs via the MADDPG–VSC Algorithm

UAV technology is advancing rapidly, and variable-sweep wing UAVs are increasingly valuable because they can adapt to different flight conditions. However, conventional control methods often struggle with managing continuous action spaces and responding to dynamic environments, making them inadequate for complex multi-UAV cooperative formation control tasks. To address these challenges, this study presents an innovative framework that integrates dynamic modeling with morphing control, optimized by the multi-agent deep deterministic policy gradient for two-sweep control (MADDPG–VSC) algorithm. This approach enables real-time sweep angle adjustments based on current flight states, significantly enhancing aerodynamic efficiency and overall UAV performance. The precise motion state model for wing morphing developed in this study underpins the MADDPG–VSC algorithm’s implementation. The algorithm not only optimizes multi-UAV formation control efficiency but also improves obstacle avoidance, attitude stability, and decision-making speed. Extensive simulations and real-world experiments consistently demonstrate that the proposed algorithm outperforms contemporary methods in multiple aspects, underscoring its practical applicability in complex aerial systems. This study advances control technologies for morphing-wing UAV formation and offers new insights into multi-agent cooperative control, with substantial potential for real-world applications.

Prediction method for 4D trajectory of large fixed wing UAV under multi-layer convolution and bidirectional gating model

Abstract With the increase of low-altitude flight tasks, the importance of research on low-altitude flight safety and efficient operation has gradually become prominent. Therefore, it is necessary to try to establish a low-altitude airspace flight path pre-planning method based on 4D trajectory prediction, which can effectively support the above research. In order to improve the integrity, accuracy and reliability of the long-range trajectory prediction results of large fixed wing UAV (LFW UAV), based on the standard neural network as the basic concept to form a fusion model of improved convolutional neural network (CNN) and bidirectional gated recurrent neural network (BIGRU). At the same time, the flight trajectory fitting preprocessing is added to build the completed multilayer cyclic convolutional improvement model (MCCI). The experimental results show that the MCCI model has obvious advantages in terms of prediction accuracy, deviation range and predictable duration when dealing with the LFW UAV 4D trajectory prediction problem, and better reflects the characteristics of 3D position and spatiotemporal elements. The comparative analysis shows that the error values of the MCCI model are smaller than those of the comparison prediction models in any dimension, and the prediction results have better fit and model performance.

A Cost-Effective Solution for Measuring Vibration and Impact on Small Twin Engine Electric Fixed Wing UAV

A Cost-Effective Solution for Measuring Vibration and Impact on Small Twin Engine Electric Fixed Wing UAV

UAV Wing leading edge crashworthiness behaviour under bird strike events: The added value of CF/PA additive solutions versus traditional metallic wing structures

In recent years, an increasing interest in innovative solutions design of aircraft structural components has been raised through both research and industrial fields, aimed at optimising weight and enhancing the ability to withstand both static and dynamic loads. This study compares the structural response to a bird strike phenomenon of a vertical tail of a UAV in standard metallic configuration with the one obtained from an innovative solution, equal in volume but with an internally designed architecture for an additive approach and manufactured by employing a carbon fibre reinforced filament engineered for metal replacement applications (carbon fibre, CF/polyamide, PA). The additive solution proposes the use of a 10 % infill and a lattice structure that completely replaces the traditional aircraft structure concept. This approach leads to a significant weight reduction, approximately 45 % compared to the traditional metallic configuration. The investigation was conducted through explicit numerical simulations considering different impact angles. The numerical model of the bird strike has been assessed by numerical-experimental comparison, simulating the impact of a bird with a flat plate. For this study, the Coupled Eulerian-Lagrangian (CEL) approach has been adopted to perform the simulation. The results were compared in terms of stress distribution, failure analysis, displacements, and energy-time and force-time diagrams. The work demonstrated that using innovative manufacturing processes, such as additive manufacturing, can significantly improve the bird strike resistance of aerospace structures. This improvement is achieved though the production of lighter, structurally collaborative geometries, by reducing the load transferred to the rest of the UAV by about 47 % and decreasing the displacement on the impact area by 53 %.

Aerodynamic Assessment of Flying Wing UAV and Impact of Dimples on its Performance

Aerodynamic Assessment of Flying Wing UAV and Impact of Dimples on its Performance

Attitude Control of Small Fixed−Wing UAV Based on Sliding Mode and Linear Active Disturbance Rejection Control

Attitude Control of Small Fixed−Wing UAV Based on Sliding Mode and Linear Active Disturbance Rejection Control

Low-velocity impact localization on a full composite wing of UAV using fiber optic sensors under operating environments

In this paper, low-velocity impact localization algorithms were suggested using fiber optic sensing system. In order to obtain high frequency signals due to low-velocity impact, a commercial high speed fiber Bragg grating (FBG) sensing system (a sampling speed of 100 kHz) was adopted. The test article is a full-scale composite wing box structure as the main wing of an unmanned aerial vehicle. The multiplexed FBG sensor array was attached on the lower surface of the upper skin. Low-velocity impact experiments were performed to obtain the impact signals for the reference data set. The reference data set is composed of the impact signals from the impacts on the reference points. The suggested algorithm in this study is based on the comparisons between impact signals and the reference signals in the database set. The main idea is to determine the reference point which has the most similar data set as the impact location. This idea was validated from the experiments of the non-reference points. As the next step, operational environments were considered to enhance the reliability of the suggested algorithm. The considered environments are the static loads and vibrations. These days, most of UAVs use the electric motors and propellers as the main propulsion system. Thus, harsh vibrations inherently occur and affect the performance of impact localization algorithms. From the experiments under these operating environments, it can be checked that the suggested algorithm has sufficient robustness to such environments.

Vibration-based Damage Diagnosis for a Population of Composite Structures Under Uncertainty via Hyper-Sphere and Transfer Component Analysis Based Methods

The problem of vibration-based damage diagnosis, including the detection and type characterization of damages in a population of nominally identical composite structures under operational uncertainty is investigated. This is an important problem for various types of fleets, such as aircraft, drones, fixed wing UAVs and others, which becomes highly challenging if the variability in the composite materials and the manufacturing of the population is significant, while the diagnosis of early-stage damages is pursued. Such a population of 27 composite coupons subjecting to operating variability due to alterations in the temperature, the excitation and the experimental setup is considered in this study. Furthermore, early-stage delamination and impact-induced damages are implemented in 10 of the coupons. Damage diagnosis is herein attempted via two data-driven methods that may account for various types of uncertainty, which are founded on a number of stochastic Multiple-Input Single-Output Transmittance Function AutoRegressive with eXogenous pseudo-eXcitation (MISO-TF-ARX) models. The first employs Hyper Spheres for the representation of the healthy subspace under uncertainty using the parameters of the MISO-TF-ARX models and thus abbreviated as HS-MISO-TF, while the other is based on the Transfer Component Analysis of these parameters, abbreviated as TCA-MISO-TF. The methods’ damage diagnosis performance is experimentally assessed using the above composite coupons and a high number of 7 500 inspection test cases for damage detection, whereas damage characterization is based on 450 test cases. The damage detection and characterization results are presented through Receiver Operating Characteristics curves and confusion matrices, respectively. The obtained results indicate adequate damage detection with the HS-MISO-TF method to achieve 82.1% correct detection for 5% of false alarms, with the TCA-MISO-TF following with 76.4% correct detection. Damage characterization is remarkable with the HS-MISO-TF to correctly characterizing the considered damage type for the 100% of the considered test cases and the TCA-MISO-TF following with 92.2%.

Structural and Fatigue Analysis of a UAV Wing

In this study, the structural and fatigue analyses of an unmanned aerial vehicle wing are investigated together. The spar, which is the main load carrier of the wing, and the ribs, which are the structural support parts that give the wing its aerodynamic shape, are analyzed using different numbers. Accordingly, 5 cases with different rip and spar numbers were examined with the finite element method. Additionally, aluminium and carbon epoxy materials were considered for the wing material in the simulations. The wall thickness for the wing is 0.5 mm and 1 mm, and the applied loads are 80 N, 150 N, and 250 N, respectively. As a result of these inputs, total deformation, maximum principal elastic strain, and fatigue analyses were performed.

ANALISIS KEKUATAN STRUKTUR PADA SAYAP MORPHING UAV MENIRU PESAWAT CESSNA 172

Nowadays, UAVs are widely used in various sectors including military, agricultural, social and other fields. There are two types of UAV control, the first uses remote control or remote control and the second the aircraft is flown independently or on autopilot. The results of the MBKM research at the Yogyakarta College of Aerospace Technology campus in 2022 resulted in several shortcomings, including having a heavier mass than a UAV wing made from balsa wood with a weight difference of 874 grams and another problem, namely that the wing's straight geometric shape will cause more resistance. so big that it needs to be changed to a morphing wing. Based on the shape of the wing and the problems, the researchers tried to correct these deficiencies by forming a new geometry. The design of this research uses CFD and FEA methods to determine deformation and pressure values. With research results. Pressure distribution on the wing surface using CFD simulation displays contour velocity and contour pressure. For contour pressure, use a velocity of 21 m/s, 22 m/s, 23 m/s, 24 m/s, 25 m/s which flows through the front of the airfoil. At a speed of 21 m/s the maximum value is 26.89 m/s, then if the speed increases then the maximum value will also increase. At a speed of 25 m/s the maximum value is 32.03 m/s. At a speed of 21 m/s the maximum value of deformation is 0.33164 mm, at a speed of 22 m/s the maximum value of deformation is 0.3515 mm, at a speed of 23 m/s the maximum value of deformation is 0.37107 mm, at a speed of 24 m/s the maximum value of deformation is 0.55469 mm, and at a speed of 25 m/s the maximum value of deformation is 0.56883 mm.

Computational investigations for topology optimization of UAV and small-scale aircraft wings

This study was conducted under the 4R-UAV project. The project is funded by the Latvian Council of Science with the goal of creating an innovative, aerodynamically improved, environmentally friendly, zero waste, and zero emission UAV. For the Circular Aviation 4R (Reduce, Recycle, Reuse, Redesign) concept, this paper covers two Rs (Reduce and Redesign) aspects of the 4R-UAV project. Topology optimization of structures has gained enormous potential with the advances in additive manufacturing techniques. However, it is still challenging when it comes to conventional manufacturing. Aircraft/UAV wings are conventionally hollow structures and leave almost little or no space for further material removal. It becomes even more complicated when conventional manufacturing limitations are further imposed. Nevertheless, topology optimization is indeed an excellent way of reducing the mass of the structures by keeping the mechanical strength intact. This computational study attempts to implement topology optimization on a small-scale aircraft aluminum alloy wing as well as on a carbon composite UAV wing. In order to ensure the feasibility of not only additive manufacturing but also conventional manufacturing, controlled/limited topology optimization was applied only to the ribs of the wings. It was found that topology optimized wing ribs (aluminum and carbon composite) demonstrated a 20% mass reduction while up to 10% overall mass reduction of the wings was achieved. Moreover, after the topology optimization, the wings demonstrated improved mechanical characteristics and factor of safety. The knowledge learned from this study will be implemented for the topology optimization of the future small-scale 4R-UAV wings which will be mainly manufactured using additive manufacturing.

Autonomous flight performance maximization for slung load carrying rotary wing mini unmanned aerial vehicle

PurposeThis research study aims to minimize autonomous flight cost and maximize autonomous flight performance of a slung load carrying rotary wing mini unmanned aerial vehicle (i.e. UAV) by stochastically optimizing autonomous flight control system (AFCS) parameters. For minimizing autonomous flight cost and maximizing autonomous flight performance, a stochastic design approach is benefitted over certain parameters (i.e. gains of longitudinal PID controller of a hierarchical autopilot system) meanwhile lower and upper constraints exist on these design parameters.Design/methodology/approachA rotary wing mini UAV is produced in drone Laboratory of Iskenderun Technical University. This rotary wing UAV has three blades main rotor, fuselage, landing gear and tail rotor. It is also able to carry slung loads. AFCS variables (i.e. gains of longitudinal PID controller of hierarchical autopilot system) are stochastically optimized to minimize autonomous flight cost capturing rise time, settling time and overshoot during longitudinal flight and to maximize autonomous flight performance. Found outcomes are applied during composing rotary wing mini UAV autonomous flight simulations.FindingsBy using stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads over previously mentioned gains longitudinal PID controller when there are lower and upper constraints on these variables, a high autonomous performance having rotary wing mini UAV is obtained.Research limitations/implicationsApproval of Directorate General of Civil Aviation in Republic of Türkiye is essential for real-time rotary wing mini UAV autonomous flights.Practical implicationsStochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads is properly valuable for recovering autonomous flight performance cost of any rotary wing mini UAV.Originality/valueEstablishing a novel procedure for improving autonomous flight performance cost of a rotary wing mini UAV carrying slung loads and introducing a new process performing stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads meanwhile there exists upper and lower bounds on design variables.

Design and Analysis of a Micro Class UAV Integrating Zimmerman Configuration

This document describes the design and analysis processes followed by team to build a micro class UAV. Through this opportunity our team has gotten a chance to test and enhance our skills by developing a design and fabricate flying wing UAV of Zimmerman configuration. Integrating this flying wing into the blended body micro classed UAV, allowed the team members to push limits further and work extra hard to make the ends meet, with the final design of a lightweight UAV following all the constrains for the SAE ADC 2020.

Lateral-Directional Aerodynamic Optimization of a Tandem Wing UAV Using CFD Analyses

This paper presents the second stage of a tandem fixed-wing unmanned aerial vehicle (UAV) aerodynamic development. In the initial stage, the UAV was optimized by analyzing its characteristics only in symmetrical flight conditions. Posted requirements were that both wings should produce relevant positive lift, the initial stall must occur on the front wing first, the center of pressure should be close to the center of gravity, and longitudinal static stability should be in the optimum range. Computational fluid dynamic (CFD) analyses were performed, where the applied calculation model was derived from the authors’ previous successful projects. The eighth version TW V8 has satisfied all longitudinal requirements. Lateral-directional CFD analyses of V8 showed that the ratio of the lateral and directional stability at the nominal cruising regime was optimal, but both lateral and directional static stabilities were too high. On further development versions, the lower vertical tail was eliminated, a negative dihedral was implemented on the front wing, and four inverted blended winglets were added. Version TW V14 has largely improved lateral and directional stability characteristics, while their optimum ratio at the cruising regime was preserved. Longitudinal characteristics were also well preserved. Maximum lift coefficient and lift-to-drag ratio were increased, compared to the V8.

Kriging and Radial Basis Function Models for Optimized Design of UAV Wing Fences to Reduce Rolling Moment

In the present study, the effects of the wing fence on the wing tip vortices and control surfaces located at the tip of the wing in a flying wing aircraft have been investigated using a numerical method. For the size of the fences, the average dimensions extracted from the wing tip vortices at different angles of attack are used. The basic determining parameter is the rolling torque coefficient, which is tried to be shown by employing a parametric study of the flow behavior in different situations of fence placement. These effects on the rolling torque of the aircraft are measured due to the presence of the split drag rudder control system. In this study, the fences were installed at three different heights and three different positions along the length of the wing, which were investigated at angles of attack of 7 to 16 degrees. The next stage of the research is to design the dimensions of the fence using the single-objective optimization method (a method to find the best solution for a problem with a specific goal). The designing of the fences at three points based on the dimensions of the wing tip vortex is carried out with the computational fluid dynamics (CFD) method (CFD is a computational method that uses physical laws to predict the behavior of fluids.). The aim of this research is to achieve the best design that converges to an optimal solution with minimum time and cost (CFD solution is long). However, CFD analysis requires a lot of computational time. To address this challenge, we employed a hybrid learning model comprising the radial basis function (RBF), a type of artificial neural network, and Kriging, a Gaussian process-based interpolation technique. The dataset for training the hybrid model was obtained from numerical solutions of CFD simulations involving a fence placed at various locations on the wing. Additionally, a genetic algorithm was employed as the optimization method in all instances where it was required. Using the power of machine learning techniques helped us identify the optimal placement of the fence to prevent it from being engulfed by the vortex and to optimize the utilization of the split drag system, yielding significant improvements.