Gaseous hydrogen chemically reacting with air in lean premixed mode yields essentially water vapour enabling to decarbonise aeronautical propulsion systems. When hydrogen fuel is produced by electrolysis, the impact on Earth is neutral on a life-cycle basis. Hydrogen fuel, combined to swirled premixed combustion mode, is a sustainable method for thermal-powered aviation. Knowledge gaps have hindered progress in the field and no laboratory-scale demonstrations have been made to date in the specific 100% H2/Air swirled premixed regime. This study describes an experiment established to: (1) demonstrate this highly swirled lean fully premixed H2/Air combustion mode and (2) -describe the underlying flame stabilisation principle. Theoretical results enable pioneering the first-to-date experimental stabilisation for these flames. Measurements with optical diagnostics including chemiluminescence and shadowgraphy direct imaging provide insights into the flame position and the flame regime. This experimental demonstration confirms that the kinematic balance between the flame displacement speed and the flow velocity is critical along with the flame-wall interaction at the bluff-body. It is shown that flashback can be mitigated. The present experiment can be replicated and utilised for application in several scientific disciplines and for advancing technologies. The experimental demonstration, regime characterisation method and mechanism description documented here open the perspective to deploy clean hydrogen combustion to decarbonise aviation with low nitrogen oxides emissions. The combination of high-swirl fully premixed H2/Air experimental data and the theoretical results are unique.

As avionics systems become increasingly complex, traditional fault prediction methods are no longer sufficient to meet modern demands. This paper introduces four advanced fault prediction methods for avionics components, utilising a multi-step prediction strategy combined with a stacking regressor. By selecting various standard regression models as base regressors, these base regressors are first trained on the original data, and their predictions are subsequently used as input features for training a meta-regressor. Additionally, the Tree-structured Parzen Estimator (TPE) algorithm is employed for hyperparameter optimisation. The experimental results demonstrate that the proposed stacking regression methods exhibit superior accuracy in fault prediction compared to traditional single-model approaches.

Unmanned aerial vehicles (UAVs) with fully electric propulsion systems mainly use lithium-based batteries. However, using fuel cells, hybrid propulsion systems are created to improve the flight time and payload capacity of the UAVs. Energy management and energy-aware path planning are important aspects to be explored in hybrid-propulsion powered UAV configurations. These facilitate optimal power distribution among energy sources and motion planning considering energy consumption, respectively. In the literature, although there are many studies on the energy management of hybrid-powered UAVs and path planning of only battery-powered UAVs, there are research gaps in energy-aware path planning of hybrid-powered UAVs. Additionally, the energy management of hybrid-powered UAVs is usually considered independent of path planning in the literature. This paper thoroughly reviews recent energy-aware path planning for small UAVs to address the listed critical challenges above, providing a new perspective and recommendations for further research. Firstly, this study evaluates the recent status of path planning, hydrogen-based UAVs, and energy management algorithms and identifies some challenges. Later, the applications of hydrogen-powered UAVs are summarised. In addition, hydrogen-based hybrid power system topologies are defined for small UAVs. Then, the path-planning algorithms are classified, and existing studies are discussed. Finally, this paper provides a comprehensive and critical assessment of the status of energy-aware path planning of UAVs, as well as detailed future work recommendations for researchers.

The Water-Enhanced Turbofan is a promising aero engine propulsion concept that could reduce the climate impact of aviation significantly by combining the conventional Joule/Brayton cycle with a Clausius-Rankine steam cycle. One important component with a high impact on the overall performance is the condenser, a heat exchanger cooling the core exhaust for water recovery. The design conditions for the Water-Enhanced Turbofan condenser have not been analysed from a system perspective in previous studies. Therefore, these operating conditions, which can be decisive for the dimensioning of the condenser, are investigated in the present work. These operating conditions include ambient temperature variations, different cruise altitudes, maximum cruise thrust and contrail avoidance. A conceptual design engine model is set up in the Numerical Propulsion System Simulation (NPSS) framework, incorporating a multi-point design scheme. The heat exchangers are modelled using a neural network surrogate model. The results show a trade-off between engine fuel burn and the cold size frontal area of the condenser, the latter being an indication for the integrability. It is shown that high ambient temperatures pose a challenge to the condenser design, necessitating consideration of such operating conditions in new engine concepts based on heat exchange with the environment. The condenser designed for typical cruise at 15K above standard atmosphere at 35,000 ft cruise altitude, enables sustained water cycle operations down to 10,000 ft under standard day conditions. Additionally, the complete cruise segment of the design mission can be flown with sustained water cycle operations at 10K above standard atmosphere conditions. A positive side effect of the condenser sizing for hot day conditions is that the probability of contrail formation is reduced because the condenser design results in excess water recovery at colder ambient conditions.

A distributed cooperative guidance law without numerical singularities is proposed for the simultaneous attack a stationary target by multiple vehicles with field-of-view constraints. Firstly, the vehicle engagement motion model is transformed into a multi-agent model. Then, based on the state-constrained consensus protocol, a coordination control law with field-of-view (FOV) constraints is proposed. Finally, the cooperative guidance law has been improved to make it more suitable for practical application. Numerical simulations verified the effectiveness and robustness of the proposed guidance law in the presence of acceleration saturation, communication delays and measurement noise.

With developing technology, the usage areas of aircraft are constantly expanded. In aircraft designed for different missions, it is an important issue to evaluate many design possibilities and make optimum designs by taking into account many parameters that are not directly connected to each other with equal importance. In this context, issues such as safety and performance come to the fore in aircraft designs. One of the critical situations affecting flight safety is the takeoff and landing phases of the aircraft. The speed changes that occur in these stages are an important issue. In this study, takeoff speed was predicted with different machine learning algorithms using takeoff speed data of the Boeing B-737-300 type aircraft. Linear regression, support vector regression, classification and regression trees, random forest regression, Extreme Gradient Boosting algorithms were selected from machine learning algorithms for takeoff speed prediction. Base models were created with these selected algorithms and the takeoff speed was predicted by training the data. Considering the obtained results, feature engineered was applied to minimise the error values of the proposed base models. In models developed by applying feature engineered, error values were reduced and better performance was observed in takeoff speed prediction. Takeoff speed values obtained with the developed models and actual flight speed values are presented comparatively for the first time in the literature. The simulation results emphasise that the developed models can be used as an effective and alternative method for takeoff speed prediction.

In this article, we delve into the optimal scheduling challenge for many-to-many on-orbit services, taking into account variations in target accessibility. The scenario assumes that each servicing satellite is equipped with singular or multiple service capabilities, tasked with providing on-orbit services to multiple targets, each characterised by distinct service requirements. The mission’s primary objective is to determine the optimal service sequence, orbital transfer duration and on-orbit service time for each servicing satellite, with the ultimate goal of minimising the overall cost. We frame the optimal scheduling dilemma as a time-related colored travelling salesman problem (TRCTSP) and propose an enhanced firefly algorithm (EFA) to address it. Finally, experimental results across various scenarios validate the effectiveness and superiority of the proposed algorithm. The principal contribution of this work lies in the modeling and resolution of the many-to-many on-orbit service challenge, considering accessibility variations — a domain that has, until now, remained unexplored.

In this study, measurements and numerical analyses of the temperature distribution of exhaust gas passing through two types of mixers using a micro turbojet engine were performed to investigate the flow mixing performance based on the shape of the mixer, which mixes the bypass air and core air in a gas turbine turbofan engine. To study the mixing characteristics of the mixer, compressed air was supplied through an external duct mounted on a micro turbojet engine to simulate bypass flow, and a system in which hot gas and compressed air were mixed and ejected into the atmosphere was fabricated. A confluent-type mixer and a mixer with 8-lobed mixer channels in the form of a sine wave were used for the experiment. The exhaust gas temperature was measured based on the distance from the nozzle outlet at bypass ratios of 0.5, 1.0 and 1.4. The results showed that the lobed mixer is more effective than the confluent mixer in lowering the exhaust gas temperature as the bypass ratio increased. Numerical analysis results indicated that, in the case of the confluent mixer, flow mixing is primarily performed by shear flow owing to the velocity difference between the core gas and the bypass air. In contrast, in the case of a lobed mixer, flow mixing is achieved through rotational motion and transverse flow. In addition, when the number of lobe channels increased from 8 to 12, the rotational motion increased and the mixing performance improved. Furthermore, infrared signal calculation results confirmed that, as the number of lobe channels increased, improved flow mixing effectively reduced the infrared signal. We conclude that this study helps understand the mixing characteristics of the flow according to the shape of the mixer at various bypass ratios and determine their effect on the characteristics of the infrared signal.

This paper considers the guidance issue for attackers against aircraft with active defense in a two-on-two engagement, which includes an attacker, a protector, a defender and a target. A cooperative line-of-sight guidance scheme with prescribed performance and input saturation is proposed utilising the sliding mode control and line-of-sight guidance theories, which guarantees that the attacker is able to capture the target with the assistance of the protector remaining on the line-of-sight between the defender and the attacker in order to intercept the defender. A fixed-time prescribed performance function and first-order anti-saturation auxiliary variable are designed in the game guidance strategy to constrain the overshoot of the guidance variable and satisfy the requirement of an overload manoeuver. The proposed guidance strategy alleviates the influence of external disturbance by implementing a fixed-time observer and the chattering phenomenon caused by the sign function. Finally, nonlinear numerical simulations verify the cooperative guidance strategies.

The presented research investigates the impact of interference on the performance of aircraft Global Navigation Satellite System (GNSS) receivers with a specific focus on the behaviour of Automatic Dependent Surveillance-Broadcast (ADS-B) position quality indicators. Several experiments were performed with different aircraft types, such as Airbus, Boeing, Beechcraft King Air B350 or Tecnam, and using various intensities of GNSS jamming. The behaviour of various quality indicators, such as the Navigation Integrity Category, Navigation Accuracy Category, Source Integrity Level and System Design Assurance transmitted in different types of ADS-B messages, is analysed. We investigate not only situations where the quality indicators drop to zero, but also the complete evolution of the changes in the indicators as a function of the increasing power of the jamming signal. Based on the analysis of changes in the ADS-B quality indicators, the estimation of the most likely interference signal power required to discontinue the tracking of an already acquired GPS L1 Coarse/Acquisition signal is made. Additionally, the interference signal power to prevent re-acquisition is also estimated. The findings improve the understanding of interference effects and can support the development of robust interference mitigation techniques in aviation applications.

Station-keeping control is a critical technology for stratospheric aerostats. For those aerostats that utilise wind field environments to achieve trajectory control, the station-keeping capability of a single aerostat is inherently limited. This limitation can lead to instances of the aerostat flying outside the designated task area, thereby diminishing the effectiveness of station-keeping control. To ensure continuous monitoring of the restricted area for long endurance, dynamic adjustments and cooperative coverage among multiple aerostats are necessary. This paper introduces an optimal coverage algorithm based on Voronoi diagrams and presents a formation control method for stratospheric aerostats that employs the virtual force method and the ${A^{\rm{*}}}$ algorithm, respectively. In a real wind field environment, ten aerostats are deployed to optimally cover the restricted area. Simulation results indicate that the coverage rate of the stratospheric aerostats within the restricted area can exceed 70%, while the network connectivity rate among the aerostats can reach 80% following guidance control during return flights. Furthermore, the stratospheric aerostats that flying out of the restricted area can return through path planning and optimal coverage algorithm, and the networking connectivity rate between aerostats is higher than that using the virtual force method.

Safe and efficient flight operations depend on effective air traffic management and the decision-making skills of air traffic control officers (ATCOs). However, managing air traffic in terminal control areas (TMAs), especially in approach control units, is challenging due to the complexity of the airspace. This is particularly evident in metroplex airspaces like the Istanbul TMA, which features multiple civil and military airports, diverse approach systems, and heavy traffic volumes, all contributing to an exceptionally complex operational environment. This study examines how experienced ATCOs perceive airspace complexity, focusing on approach control units within TMAs. Using Istanbul TMA as a case study, the research combines qualitative and quantitative methods to analyse the factors contributing to complexity. In the first phase, the Content Validity Method (CVM) is used to identify and confirm the key factors influencing airspace complexity. In the second phase, the Best-Worst Method (BWM) is applied to measure the importance of these factors. The study involves two groups of ATCOs: 40 in the first group and 20 in the second. The results reveal that ‘conflicts’ are the most critical factor affecting airspace complexity, highlighting the importance of conflict resolution in air traffic control. Other significant factors include rules and procedures, airspace design and traffic density. This study provides clear insights into the challenges of managing TMA, especially in metroplex airspace. Identifying and analysing the key factors offers valuable guidance for improving air traffic management and supporting ATCOs in making better decisions.

In recent years, the rapid convergence of artificial intelligence (AI) and low-altitude flight technology has driven significant transformations across various industries. These advancements have showcased immense potential in areas such as logistics distribution, urban air mobility (UAM) and national defense. By adopting the AI technology, low-altitude flight technology can achieve high levels of automation and operate in coordinated swarms, thereby enhancing efficiency and precision. However, as these technologies become more pervasive, they also raise pressing ethical or moral concerns, particularly regarding privacy, public safety, as well as the risks of militarisation and weaponisation. These issues have sparked extensive debates. In summary, while the integration of AI and low-altitude flight presents revolutionary opportunities, it also introduces complex ethical challenges. This article will explore these opportunities and challenges in depth, focusing on areas such as privacy protection, public safety, military applications and legal regulation, and will propose strategies to ensure that technological advancements remain aligned with ethical or moral principles.

A numerical simulation of a two-dimensional rectangular supersonic intake has been performed in a steady-state condition to understand the effect of separation bubble size and its position on the intake performance. Diverse characteristics of separation bubbles in terms of their position, size and quantity have been systematically investigated under varying cowl deflections ranging between $\alpha $ = 0${{\rm{\;}}^ \circ }$ and 4${{\rm{\;}}^ \circ }$ within the intake system. The study encompasses a range of Mach numbers, specifically between M = 1.5 and 3, allowing for comprehensive comparisons of pressure recovery and flow distortions associated with each configuration. The flow field is generated using compressible Reynolds-averaged Navier-Stokes equations along with k-$\omega $ turbulence model. The numerical model is validated using previous experimental and numerical results. Intake unstart is observed when a large separation bubble forms on the ramp surface. The separation bubble shifts from the ramp and moves towards the exit as the Mach number and cowl angle change, resulting in the intake restart. The performance of the intake is observed to be degrading as separation size increases with changes in Mach number and cowl angles. At fixed Mach number, pressure recovery of the intake is observed to be improving with increase in cowl deflection owing to the reduction in net separation bubble size. Maximum TPR of 0.772 is observed at M = 2.2 with 4${{\rm{\;}}^ \circ }$ cowl deflection characterised by net separation of 1.65 mm. Flow distortion is found to be dependent on separation size, position and number of separation bubbles.