Search results

The purpose of this research paper is to recover the autonomous flight performance of a mini unmanned aerial vehicle (UAV) via stochastically optimizing the wing over certain parameters (i.e. wing taper ratio and wing aspect ratio) while there are lower and upper constraints on these redesign parameters.

A mini UAV is produced in the Iskenderun Technical University (ISTE) Unmanned Aerial Vehicle Laboratory. Its complete wing can vary passively before the flight with respect to the result of the stochastic redesign of the wing while maximizing autonomous flight performance. Flight control system (FCS) parameters (i.e. gains of longitudinal and lateral proportional-integral-derivative controllers) and wing redesign parameters mentioned before are simultaneously designed to maximize autonomous flight performance index using a certain stochastic optimization strategy named as simultaneous perturbation stochastic approximation (SPSA). Found results are used while composing UAV flight simulations.

Using stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV over previously mentioned wing parameters and FCS, it obtained a maximum UAV autonomous flight performance.

Permission of the directorate general of civil aviation in the Republic of Türkiye is essential for real-time UAV autonomous flights.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach is very useful for improving any mini UAV autonomous flight performance cost index.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach succeeds confidence, highly improved autonomous flight performance cost index and easy service demands of mini UAV operators.

Creating a new approach to recover autonomous flight performance cost index (e.g. satisfying less settling time and less rise time, less overshoot during flight trajectory tracking) of a mini UAV and composing a novel procedure performing simultaneous mini UAV having passively morphing wing over certain parameters while there are upper and lower constraints and FCS design idea.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

The “Germanwings” air crash in 2015 in which 150 people were killed highlighted the challenges pilots working in the aviation industry face. Pilots regularly work for extensive periods in inhospitable and high-pressure operational conditions, exposing them to considerable work-related stress. This has raised calls for a more systemic cultural change across the aviation industry, championing a more holistic perspective of pilot health and well-being. The study aims to explore how peer coaching (PC) can promote an inclusive psychosocial safety climate enhancing pilot well-being and can mitigate hazardous attitudes and dysfunctional behaviours.

Adopting an interpretative phenomenological analysis (IPA), semi-structured interviews and questionnaires were conducted with military and civilian peer coach/coachee pilots and key industry stakeholders, totalling 39 participants. The research provided significant insights into the perceived value of PC in promoting both pilot health and mental well-being (MW) and flight safety across the aviation industry.

The study highlights four key PC superordinate themes, namely, coaching skills, significance of well-being, building of peer relationships and importance of confidentiality and autonomy. Such combined themes build reciprocal trust within peer conversations that can inspire engagement and effectively promote personal well-being. The contagious effect of such local interventions can help stimulate systemic cultural change and promote a positive psychosocial safety climate throughout an organisation and, in this case, across the aviation industry. This study provides a PC conceptual framework “Mutuality Equality Goals Autonomy Non-evaluative feedback, Skill Confidentiality Voluntary Supervisory (MEGANS CVS),” highlighting the salient features of PC in promoting MW.

The study highlights the salient features of PC and its role in promoting peer conversations that enable personal transition, openness and acceptance. This study also highlights how PC and well-being can be used to encourage inclusivity and engagement, thereby strengthening institutional resilience.

This study highlights how PC that can assist HRM/HRD professionals to embed a more inclusive and salutogenic approach to MW that can reshape organisational cultures. This study highlights the significance and link of workplace stress to hazardous attitudes and dysfunctional behaviours. It further notes that whilst the MEGANS CVS peer coaching framework has been applied to pilots, it can also be applied across all sectors and levels.

This study highlights the value of PC as an inexpensive means to engage at the grassroots level, which not only improves personal performance, safety and well-being but by building peer relationships can also act as a catalyst for positive and deep organisational cultural change.

This study offers the MEGANS CVS framework that exposes insights into PC practice that can assist HRM/HRD professionals embed a more inclusive and salutogenic approach to health and well-being that can reshape organisational cultures. This study highlights the significance and link of workplace stress to hazardous attitudes and dysfunctional behaviours, and whilst this framework has been applied to pilots, it can also have relevance across all sectors and levels. This study calls for a “salutogenic turn,” employing MW and PC to transform organisational capabilities to be more forward-thinking and solution-focused, promoting an inclusive “just culture” where leaders positively lead their people.

This paper aims to assess the impact of electrifying the environmental control system (ECS) and ice protection system (IPS), the primary pneumatic system consumers in a conventional commercial transport aircraft, on aircraft weight, range, and fuel consumption.

The case study was carried out on Airbus A321-200 aircraft. Design, modelling and analysis processes were carried out on Pacelab SysArc software. Conventional and electrical ECS and IPS architectures were modelled and analysed considering different temperature profiles.

The simulation results have shown that the aircraft model with ±270 VDC ECS and IPS architecture is lighter, has a more extended range and has less relative fuel consumption. In addition, the simulation results showed that the maximum range and relative fuel economy of all three aircraft models increased slightly as the temperature increased.

Considering the findings in this paper, it is seen that the electrification of the conventional pneumatic system in aircraft has positive contributions in terms of weight, power consumption and fuel consumption.

The positive contributions in terms of weight, power consumption and fuel consumption in aircraft will be direct environmental and economic contributions.

Apart from the conventional ECS and IPS of the aircraft, two electrical architectures, 230 VAC and ±270 VDC, were modelled and analysed. To see the effects of the three models created in different temperature profiles, analyses were done for cold day, ISA standard day and hot day temperature profiles.

This 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.

A 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.

By 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.

Approval of Directorate General of Civil Aviation in Republic of Türkiye is essential for real-time rotary wing mini UAV autonomous flights.

Stochastic 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.

Establishing 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.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

This study aims to study the thermal identification issue by harvesting both solar energy and atmospheric thermal updraft for a solar-powered unmanned aerial vehicle (SUAV) and its electric energy performance under continuous soaring conditions.

The authors develop a specific dynamic model for SUAVs in both soaring and cruise modes. The support vector machine regression (SVMR) is adopted to estimate the thermal position, and it is combined with feedback control to implement the SUAV soaring in the updraft. Then, the optimal path model is built based on the graph theory considering the existence of several thermals distributed in the environment. The procedure is proposed to estimate the electricity cost of SUAV during flight as well as soaring, and making use of dynamic programming to maximize electric energy.

The simulation results present the integrated control method could allow SUAV to soar with the updraft. In addition, the proposed approach allows the SUAV to fly to the destination using distributed thermals while reducing the electric energy use.

Two simplified dynamic models are constructed for simulation considering there are different flight mode. Besides, the data-driven-based SVMR method is proposed to support SUAV soaring. Furthermore, instead of using length, the energy cost coefficient in optimization problem is set as electric power, which is more suitable for SUAV because its advantage is to transfer the three-dimensional path planning problem into the two-dimensional.

This study aims to find the characteristics of supercritical airfoil in helicopter rotor blades for hovering phase using numerical analysis and the validation using experimental results.

Using numerical analysis in the forward phase of the helicopter, supercritical airfoil is compared with the conventional airfoil for the aerodynamic performance. The multiple reference frame method is used to produce the results for rotational analysis. A grid independence test was carried out, and validation was obtained using benchmark values from NASA data.

From the analysis results, a supercritical airfoil in hovering flight analysis proved that the NASA SC rotor produces 25% at 5°, 26% at 12° and 32% better thrust at 8° of collective pitch than the HH02 rotor. Helicopter performance parameters are also calculated based on momentum theory. Theoretical calculations prove that the NASA SC rotor is better than the HH02 rotor. The results of helicopter performance prove that the NASA SC rotor provides better aerodynamic efficiency than the HH02 rotor.

The novelty of the paper is it proved the aerodynamic performance of supercritical airfoil is performing better than the HH02 airfoil. The results are validated with the experimental values and theoretical calculations from the momentum theory.

In this study, an indoor sensor information fusion positioning system of the quadrotor unmanned aerial vehicle (UAV) was investigated to solve the problem of unstable indoor flight positioning.

The presented system was built on Light Detection and Ranging (LiDAR), Inertial Measurement Unit (IMU) and LiDAR-Lite devices. Based on this, one can obtain the aircraft's current attitude and the position vector relative to the target and control the attitudes and positions of the UAV to reach the specified target positions. While building a UAV positioning model relative to the target for indoor positioning scenarios under limited Global Navigation Satellite Systems (GNSS), the system detects the environment through the NVIDIA Jetson TX2 (Transmit Data) peripheral sensor, obtains the current attitude and the position vector of the UAV, packs the data in the format and delivers it to the flight controller. Then the flight controller controls the UAV by calculating the posture to reach the specified target position.

The authors used two systems in the experiment. The first is the proposed UAV, and the other is the Vicon system, our reference system for comparison purposes. Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

Designing new aircraft that are state-of-the-art and beyond always requires the development of new technologies. This paper aims to present lessons learned while designing, building and testing new UAVs in the configuration of the flying wing. The UAV contains a number of aerodynamic devices that are not obvious solutions and use the latest manufacturing technology achievements, such as 3D printing.

The design solutions were applied on an airworthy aircraft and checked during test flights. The process was first conducted on the smaller UAV, and based on the test outcomes, improvements were made and then applied on the larger version of the UAV, where they were verified.

A number of practical findings were identified. For example, the use of 3D printing technology for manufacturing integrated pressure ports, investigation of the adverse yaw effect on the flying wing configuration and the effectiveness of winglet rudders in producing yawing moment.

All designed devices were tested in practice on the flying aircraft. It allowed for improved aircraft performance and handling characteristics. Several of the technologies used improved the speed and quality of aerodynamic device design and manufacturing, which also influences the reliability of the aircraft.

The paper presents how 3D printing technology can be utilized for manufacturing of aerodynamic devices. Specially developed techniques for control surface design, which can affect adverse yaw problem and aircraft handling characteristics, were described.