So much has been written about Frederick W. Lanchester over the years, it is hard to imagine finding something new to discuss about his efforts in aerodynamics. Many of the previous Lanchester Memorial Lectures discussed topics such as wing aerodynamics, aircraft concepts and design, unsteady rotor aerodynamics, aerodynamics research and a wide variety of other related aerodynamic topics. However, there has never been a lecture about Lanchester’s book Aerodynamics as a tool for aerodynamics education in the early 20th century. The lecture will discuss his book relative to other aerodynamics books before and after 1907, and uncover how Lanchester’s book had a very distinct, and important, contribution to make for aerodynamic education.

The enhancement of jet engine components may result in the expansion of the established design space. In particular, the trend towards short and therefore highly aggressive inter compressor ducts (ICD) extends the traditional design space. The potential for fuel savings resulting from a reduction in engine weight is in contrast to the emergence of a more complex flow field. Many studies consider the secondary flow system of highly aggressive ICDs at the design point, but there is a lack of off-design considerations. To fill this gap, the present study investigates in detail the off-design performance of the new German Aerospace Center (DLR) test case. Firstly, computational fluid dynamics (CFD) simulations of different typical operating points allow detailed considerations of the flow field under off-design conditions. Secondly, a variation of the inlet conditions describes the sensitivity of highly aggressive ICDs to different low-pressure compressor operating points. Finally, the comparison of the CFD stagnation pressure loss with the loss predicted by a preliminary off-design method validates the use of traditional off-design prediction during the preliminary design of highly aggressive ICDs.

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.

This article presents a systematic review on the use of eye-tracking technology to assess the mental workload of unmanned aircraft system (UAS) operators. With the increasing use of unmanned aircraft in military and civilian operations, understanding the mental workload of these operators has become essential for ensuring mission effectiveness and safety. The review covered 26 studies that explored the application of eye-tracking to capture nuances of visual attention and assess cognitive load in real-time. Traditional methods such as self-assessment questionnaires, although useful, showed limitations in terms of accuracy and objectivity, highlighting the need for advanced approaches like eye-tracking. By analysing gaze patterns in simulated environments that reproduce real challenges, it was possible to identify moments of higher mental workload, areas of concentration and sources of distraction. The review also discussed strategies for managing mental workload, including adaptive design of human-machine interfaces. The analysis of the studies revealed a growing relevance and acceptance of eye-tracking as a diagnostic and analytical tool, offering guidelines for the development of interfaces and training that dynamically respond to the cognitive needs of operators. It was concluded that eye-tracking technology can significantly contribute to the optimisation of UAS operations, enhancing both the safety and efficiency of military and civilian missions.

Measuring the aerodynamics and stability characteristics of small unmanned aerial vehicles (sUAVs) operating at Reynolds numbers below $60,000$ is a challenge. Conventional measurement methods can be impractical and costly due to the vehicle’s size and the considerably low forces and moments involved. To overcome these limitations, the current study aims at utilising an existing motion tracking system to conduct off-board aerodynamic measurements of sUAVs. Six sUAVs, with varying wing aspect ratios, are investigated in un-powered, glide flight mode to establish the utility of the motion capture system as an aerodynamic characterisation system and understand the low Reynolds number effects on the flight dynamics. The trajectory tracking system was thoroughly validated through a series of static and dynamic tests to account for uncertainties and errors. Subsequently, flight trajectory data was collected and processed to extract the aircraft’s force and moment characteristics under quasi-steady conditions. The measured lift, drag and moment data compared well with existing literature and theoretical predictions. Longitudinal, lateral and dynamic stability derivatives were also accurately captured. Key findings from the current work included an inverse relationship between the wing aspect ratio and lift curve slope and substantially lower Oswald efficiency factors, both of which were attributed to low Reynolds number effects.

In recent times, there has been increased focus on the utilisation of virtual reality flight simulators in flight training, driven by their advantages compared to conventional methods. However, a paucity of empirical evidence has prevented their widespread introduction and regulatory approval. Existing research focuses on single-user simulators, leaving a gap in studies of collaborative training within virtual environments. Consequently, this paper investigates evidence-based simulator training within a collaborative virtual environment.

A mixed methods approach was adopted, where behaviours related to industry-standard competencies were observed in a virtual reality complex aircraft and thematic analysis applied to a post-experiment participant debrief. The findings showcase the feasibility of utilising a collaborative virtual environment for evidence-based training purposes in scenarios aligned to typical initial First Officer airline training programmes, which is a precursor to supplementing traditional professional pilot training techniques. In addition, the study found that the visual barriers imposed by head-mounted displays were overcome through the adoption of refined communication strategies, thus laying the groundwork for physically separated multi-crew pilot training.

Sixty uncrewed aerial vehicle (UAV) accident reports were analysed to identify causal and contributory factors leading to loss of control in flight – the most prominent category of UAV accident (36%). Design and manufacturing errors were dominant causal factors (22 events, 34%) and contributory factors (18 events, 22%). Recovery was not attempted in the majority of events (35 events, 55%). The relationship between operator age, total hours of experience, experience on type and recovery attempts were analysed. The number of accidents decreased as total hours of experience increased as well as attempted recovery. Using this data, existing accident analysis frameworks HFACS, AcciMap and Accident Route Matrix were applied to a sample of accidents and suitability compared. An adapted version of the Accident Route Matrix – Uncrewed Aerial Vehicle is proposed to assist current and future operators to understand causal and contributory factors to mitigate future loss of control in flight accidents and improve the likelihood of recovery. Using the results of the statistical analysis and the data gathered, a new definition for LOC-I for UAVs was defined by considering the different operating environment of UAVs.

Unmanned aerial vehicle (UAV) formations for bearing-only passive detection are increasingly important in modern military confrontations, and the array of the formation is one of the decisive factors affecting the detection accuracy of the system. How to plan the optimal geometric array in bearing-only detection is a complex nondeterministic polynomial problem, and this paper proposed the distributed stochastic subgradient projection algorithm (DSSPA) with layered constraints to solve this challenge. Firstly, based on the constraints of safe flight altitude and fixed baseline, the UAV formation is layered, and the system model for bearing-only cooperative localisation is constructed and analysed. Then, the calculation formula for geometric dilution of precision (GDOP) in the observation plane is provided, this nonlinear objective function is appropriately simplified to obtain its quadratic form, ensuring that it can be adapted and used efficiently in the system model. Finally, the proposed distributed stochastic subgradient projection algorithm (DSSPA) combines the idea of stochastic gradient descent with the projection method. By performing a projection operation on each feasible solution, it ensures that the updated parameters can satisfy the constraints while efficiently solving the convex optimisation problem of array planning. In addition to theoretical proof, this paper also conducts three simulation experiments of different scales, validating the effectiveness and superiority of the proposed method for bearing-only detection array planning in UAV formations. This research provides essential guidance and technical reference for the deployment of UAV formations and path planning of detection platforms.

Reynolds-Averaged Navier–Stokes (RANS) simulations, both steady and unsteady, are used to investigate supersonic, chemically reacting, flow fields inside a strut-stabilised supersonic combustion ramjet (scramjet) engine operating under different fuel flow rates. Fully supersonic, fully subsonic and mixed modes of operations inside the combustor, obtained at different fuel flow rates, are studied numerically through shock wave visualisations and top-wall static-pressure probing. The effect of changing fuel flow rates, imposed both suddenly and gradually, on the behaviour of shock waves and wall pressure profiles are studied in detail. For certain modes of combustion characterised by the presence of oblique shocks at the strut, shockwaves in the combustor respond predictably to an increase or decrease in fuel flow rate attaining the steady state flow fields as predicted by RANS simulations for those fuel flow rates. For certain other modes of combustion, characterised by the presence of shockwaves in the isolator and the absence of oblique shocks at the leading edge of the strut, shockwaves in the flow field appear unstable to fuel flow rate modulations. For such cases, any change in fuel flow rates, sudden or gradual, increase or decrease, causes the isolator shocks to immediately move upstream and eventually out of the isolator. A plausible physics-based explanation of the observed phenomena is presented.

To address the challenges of high-manoeuver targets and limited line-of-sight from the interceptor’s side window, this paper proposes a three-dimensional target manoeuver compensation control (TMCC) guidance law based on compensation function observe (CFO) and a method for studying the terminal guidance handover region. First, a relative model of the missile-target engagement is established. Secondly, the CFO is used to estimate the target manoeuver state, and the estimated information is fed back to the controller of the orbit control engine to make the interception more accurate. Considering the limited line of sight of the side window, the body line of sight angle is constrained by controlling the attitude control engine. Then, the problem description for solving the handover area and the definition of the terminal guidance handover area were provided, and the algorithm design for the handover area was conducted, simplifying the solving process through the concept of area substitution. Simulation results indicate that the proposed terminal guidance law offers higher interception accuracy compared to traditional proportional guidance, and effectively validates the accuracy of the handover region calculation.

With the rapid increase in the use of drones in various applications, including commercial and governmental, and the increasing probability of communication failures and contingencies, research becomes critical to ensure the safety and efficiency of their operations. The aim of this research is to develop adaptive drone flight control algorithms capable of operating effectively under conditions of limited communication and incomplete information to ensure reliable and safe autonomous operation of these systems. The applied methods include computer modelling and simulation, analytical, statistical, functional, deductive and descriptive methods. The study found that the use of performance evaluation methods for complex systems enables the identification of safety and performance criteria for drones, and drone flight control provides basic principles and methods that can be adapted for drones, including autopiloting and navigation. In addition, analyses of satellite communication and navigation prove the need to consider the limitations of this technology when developing drone control algorithms. The combination of these techniques allows for more robust and adaptive drone control systems that can function effectively in complex environments such as communication limitations and incomplete information. Additionally, it was found that the integration of adaptive control algorithms based on these methods allows drones to effectively adapt to variable environmental conditions and make decisions quickly even when communication is lost or information is limited.

This paper presents a study of the effects of the durability and level of energy storage technology on energy management strategies and the performance of hybrid electric turboprops. The results highlight the key role of battery energy density on the durability of the battery pack and the viability of the concept of hybrid electric aircraft. Additionally, the trade-off between zero-day environmental compatibility and battery lifetime is identified, caused by the size of the pack. The effective energy density would decrease with the aging of the cells, leaving a significant inert mass and increasing fuel consumption. Optimal energy management strategies are suggested in light of this new information. Higher specific energy of the pack would mitigate this aspect, along with a reduction in fuel consumption and ${\rm{N}}{{\rm{O}}_{\rm{x}}}$ emissions. Indeed, the improvement of environmental compatibility was found to be nonlinear with a positive rate, suggesting high returns in investing in great improvements in energy density over a gradual increase. This result relates to the results of the statistical technological forecast presented in this study, which, without an increase in funding, predicts the availability of the specific energy required to match the fuel-only baseline in the 2040–2050 decade.

If an aircraft’s initial mass, the variation of true airspeed, true rate of climb, wind speed and wind direction with time and the relationship between barometric altitude and local temperature are known, the performance along the entire flight path can be determined. Previously published work has provided the building blocks for a simple, fast, open-source and transparent method to estimate the instantaneous fuel flow rate and the engine overall efficiency, plus several other performance characteristics for turbofan powered, civil transport aircraft. The flight phases of primary interest are the climb, cruise, descent and holding, when the flaps and undercarriage are fully retracted and the engine is providing significant, positive thrust. However, for completeness, an approximate relation is provided for the engine’s ‘flight idle’ condition, together with simple estimates for fuel use during take-off and landing, plus a factor to allow for in-service deterioration. Detailed consideration is also given to the operating limits and relations are developed for the estimation of their location in Mach number and flight level space. To apply the method, a series of characteristic coefficients and constants must be known. Estimates for these quantities have been progressively improved and extended over time. Initially, results were published for 53 aircraft types and variants. The data base has now been extended to 67 entries and this is given in tabular form. Finally, to demonstrate the method’s accuracy, estimates of fuel flow rate are compared with flight data recorder values for 20 complete flights of six different aircraft types.

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.

This paper quantifies the impacts of the airframe configuration change on the performance differences between a tube-and-wing and a blended wing body aircraft. Both are sized for a 5,000 nmi design range carrying 225 passengers, initially using the same engine. Parametric geometry is created for both concepts based on relevant public information. The tube-and-wing notional geometry is derived from the existing Boeing 767-300ER, whereas JetZero’s concept inspires the blended wing body. These geometries are optimised using computational fluid dynamics and gradient-free approaches. Drag polars for each optimised model, spanning the expected operating envelope, are generated using computational fluid dynamics simulations and multi-fidelity surrogate models. Mission analysis is performed for the blended wing body, a conventional tube-and wing variant with metallic structures, and an advanced tube-and-wing with composite structures. The results show that the blended wing body operates with 15-20% higher lift-over-drag during the cruise, 24% lower fuel burn for the design mission, and 15% reduction in ramp weight relative to the conventional tube-and-wing. These differences drop to 20% for the design mission fuel burn and 10% for the ramp weight relative to the advanced tube-and-wing. When the engines are re-sized and optimised separately for each configuration, the blended wing body demonstrates a 25% improvement in block fuel and 16% reduction in ramp weight relative to the conventional tube-and-wing, which decreases to 21% and 10% relative to the advanced tube-and-wing. In both comparisons, the fuel efficiency advantage of the blended wing body decreases as the mission range is reduced.

Rapid and comprehensive fighter optimisation is an important part of modern combat decision-making. However, due to the numerous influencing factors, it is difficult for decision-makers to consider comprehensively and specify the optimal decision, and it is highly subjective, which leads to different decision conclusions from person to person. Therefore, to solve the above deficiencies in fighter selection, this paper proposes a sequential decision-making framework that comprehensively considers the effectiveness, maintenance, support capability and health status of the fighter aircraft. Based on the multi-dimensional state, it provides comprehensive and credible auxiliary support for commanders. The sequential decision-making framework (called GRA-VIKOR-IFNs) uses the combination of equation and fuzzy multi-criteria decision-making (FMCDM) to evaluate the effectiveness, support capability and health in turn, to complete the step-by-step selection of fighter models, troops and sorties. The evaluation equation is for the effectiveness evaluation and a hybrid method using the extended grey correlation analysis (GRA) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method based on intuitionistic fuzzy numbers (IFNs) is for the support capability and health evaluation. The proposed strategy is in line with the logic and demand of actual combat and training decision-making and takes into account the influence of uncertain factors. Finally, a comparison with some classical methods is carried out, such as the full consistency method (FUCOM), the technique for order of preference by similarity to ideal solution (TOPSIS) and so on. The GRA-VIKOR-IFNs method is consistent with the results of other methods and the result sort resolution is 0.0619 and at least 40% higher than other methods, which can lead the commanders to a more reliable and clear decision.

The axisymmetric nozzle mechanism is the core part for thrust vectoring of aero engine, which contains complex rigid-flexible coupled multibody system with joints clearance and significantly reduces the efficiency in modeling and calculation, therefore the kinematics and dynamics analysis of axisymmetric vectoring nozzle mechanism based on deep neural network is proposed. The deep neural network model of the axisymmetric vector nozzle is established according to the limited training data from the physical dynamic model and then used to predict the kinematics and dynamics response of the axisymmetric vector nozzle. This study analyses the effects of joint clearance on the kinematics and dynamics of the axisymmetric vector nozzle mechanism by a data-driven model. It is found that the angular acceleration of the expanding blade and the driving force are mostly affected by joint clearance followed by the angle, angular velocity and position of the expanding blade. Larger joint clearance results in more pronounced fluctuations of the dynamic response of the mechanism, which is due to the greater relative velocity and contact force between the bushing and the pin. Since axisymmetric vector nozzles are highly complex nonlinear systems, traditional numerical methods of dynamics are extremely time-consuming. Our work indicates that the data-driven approach greatly reduces the computational cost while maintaining accuracy, and can be used for rapid evaluation and iterative computation of complex multibody dynamics of engine nozzle mechanism.

To investigate the flame acceleration to detonation in 2.0 and 0.5 mm planar glass combustion chambers, the experiments have been conducted utilising ethylene/oxygen mixtures at atmospheric pressure and temperature. The high-speed camera has been used to record the revolution of flame front and pressure inside the combustion chamber. Different equivalence ratios and ignition locations have been considered in the experiments. The results show that the detonation pressure in the 2 mm thick chamber is nearly three times of Chapman-Jouguet pressure, while detonation pressure in the 0.5 mm thick chamber is only 45.7% of the Chapman-Jouguet value at the stoichiometric mixture. This phenomenon is attributed to the larger pressure loss in the thinner chamber during the detonation propagation. As the value of equivalence ratio is 2.2, the detonation cannot be produced in the 2 mm thick chamber, while the detonation can be generated successfully in the 0.5 mm thick chamber. This phenomenon indicates that the deflagration is easily to be accelerated and transformed into the detonation, due to a larger wall friction and reflection. Besides, the micro-obstacle has been added into the combustor can shorten the detonation transition time and reduces the distance of the detonation transition.

Effusion cooling is the state-of-the-art cooling technology for gas turbine hot-gas path components. Typically, effusion cooling holes across the entire combustor liner are aligned with the combustor axis, rendering a nominal zero compound angle between highly directional miniature effusion cooling jets and the main flow direction. The pitch of effusion cooling holes is optimised accordingly. However, the swirling main flow results in a non-zero compound angle and an effectively different pitch from the design. The directional effect of effusion cooling as a result of swirling main flow on the adiabatic film cooling effectiveness (AFE) is a combined effect of a non-zero compound angle and a varied pitch. The current experimental study aims to investigate the isolated effects of compound angle on AFE by excluding the influences of varying pitch. With an improved understanding of the sole effects of non-zero compound angles on AFE, the roles that a varied pitch plays in modifying AFE are further discussed to guide future effusion cooling designs under swirling main flow conditions. Binary pressure sensitive paint (PSP) was used to determine AFE experimentally.