Problem: Why did the pilots do that? Human error is a reasonably common retrospective assignment of responsibility tied to undesirable aeronautical safety occurrences. Although retributive justice has long been accepted in aviation, its effectiveness in preventing recurrence is minimal. Airmen tend to decide based on their best knowledge with the available resources in intrinsically fallible systems in the ultra-safe high-risk aviation industry.

Method and Results: This paper sheds light on Safety as Capacity under the vanguardist Safety-II perspective and examines procedures as static tools incapable of sustaining safety. It discusses the prejudice in non-critical adherence to procedural compliance beyond creating bureaucratic work environments permissible to sanction workers against regulations. Disputing the safety gain in a retrospective analysis of mishaps, the paper instils the airmen as solution elements to sustain safety at the management of context, a fundamental aspect of Safety-II.

Impact on Industry: A systemic deficiency in civilian pilot training is exposed, and an independent organisational Safety Capacity assessment tool to air operations is provided. The main debate is the synergetic interaction between aircrew’s aeronautical decision-making skills and organisational Safety-II as safety capacity. The pilot’s preparedness to analyse, create and evaluate outside forecasted protocols in modern aviation environments is discussed. These dynamics are revised in their inter-reliability known as Safety as Capacity.

This paper investigates the hydrodynamic near-field of a NACA 16-616 aerofoil over a range of angles-of-attack, encompassing the pre-stall, stall and post-stall flow regimes. In both the static pressure and the pressure fluctuation results, it is shown that each flow regime is easily distinguished, and it is further shown that each regime has different spectral behaviour and boundary layer characteristics. It is found that the NACA 16-616 aerofoil stalls by an abrupt leading-edge mechanism, characterised by a sudden change in the static pressure and unsteady surface pressure spectra between $16^\circ $ and $17^\circ $ angles-of-attack, but of more interest is that there is a secondary yet significant trailing-edge flow separation mechanism occurring upstream of the trailing-edge and moving further upstream as the angle-of-attack increases in the pre-stall regime. A comparison is made between the spectra and coherence of the unsteady surface pressure of the NACA 16-616 aerofoil and those of the classic NACA 0012 aerofoil and shows that such a secondary mechanism has a significant impact for large pre-stall angles-of-attack on the unsteady surface pressure. This will have a significant impact on the radiated far-field sound, distinguishing the NACA 16-616 aerofoil from aerofoils that do not have this secondary mechanism. The existence and extent of this secondary trailing-edge separation mechanism is further shown by the hot-wire anemometry boundary layer velocity results that indicate separation within the pre-stall regime.

The evaluation of the on-ground casualty risk assessments due to a controlled or uncontrolled re-entry is highly sensitive to the accurate prediction of fragmentation events during an atmospheric re-entry. The main objective of this study is an investigation into the use of peridynamics (PD) to improve the analysis of fragmentation during atmospheric re-entry with respect to currently adopted semi-empirical approaches. The high temperatures characterising such scenarios may substantially impact fragmentation, which requires appropriate modelling of the damage process within the PD method. The damage models in PD require experimentally determined fracture mechanical properties that are unavailable as a function of temperature. This work proposes a numerical methodology to estimate the PD damage parameters changes with temperature to enable the study of fragmentation during atmospheric re-entry. Initially, tensile-testing simulation experiments are performed in peridynamics to calibrate material parameters for steel and aluminium alloys as a function of temperature. Then, a parametric study is carried out to evaluate the temperature-dependent damage model parameters for the same materials. The applicability of the proposed methodology is showcased using a re-entry test case scenario.

Prediction of stall before it occurs, or detection of stall is crucial for smooth and lasting operation of fans and compressors. In order to predict the stall, it is necessary to distinguish the operational and stall regions based on certain parameters. Also, it is important to observe the variation of those parameters as the fan transitions towards stall. Experiments were performed on a contra-rotating fan setup under clean inflow conditions, and unsteady pressure data were recorded using seven high-response sensors circumferentially arranged on the casing, near the first rotor leading edge. Windowed Fourier analysis was performed on the pressure data, to identify different regions, as the fan transits from the operational to stall region. Four statistical parameters were identified to characterise the pressure data and reduce the number of data points. K-means clustering was used on these four parameters to algorithmically mark different regions of operation. Results obtained from both the analyses are in agreement with each other, and three distinct regions have been identified. Between the no-activity and stall regions, there is a transition region that spans for a short duration of time characterised by intermittent variation of abstract parameters and excitations of Fourier frequencies. The results were validated with five datasets obtained from similar experiments at different times. All five experiments showed similar trends. Neural Network models were trained on the clustered data to predict the operating region of the machine. These models can be used to develop control systems that can prevent the stalling of the machine.

Civil aircraft that fly long ranges consume a large fraction of civil aviation fuel, injecting an important amount of aviation carbon into the atmosphere. Decarbonising solutions must consider this sector. A philosophical-analytical feasibility of an airliner family to assist in the elimination of carbon dioxide emissions from civil aviation is proposed. It comprises four models based on the integration of the body of a large two-deck airliner with the engines, wings and flight surfaces of a long-range twin widebody jet. The objective of the investigation presented here is to evaluate the impact of liquid hydrogen tank technology in terms of gravimetric efficiency. A range of hydrogen storage gravimetric efficiencies was evaluated; from a pessimistic value of 0.30 to a futuristic value of 0.85. This parameter has a profound influence on the overall fuel system weight and an impact on the integrated performance. The resulting impact is relatively small for the short-range aircraft; it increases with range and is important for the longer-range aircraft. For shorter-range aircraft variants, the tanks needed to store the hydrogen are relatively small, so the impact of tank weight is not significant. Longer range aircraft are weight constrained and the influence of tank weight is important. In the case of the longest range, the deliverable distance increases from slightly over 4,000 nautical miles, with a gravimetric efficiency of 0.3, to nearly 7,000 with a gravimetric efficiency of 0.85.

This paper presents a relative fuel burn evaluation of the transonic strut-braced-wing configuration for the regional aircraft class in comparison to an equivalent conventional tube-and-wing aircraft. This is accomplished through multipoint aerodynamic shape optimisation based on the Reynolds-averaged Navier-Stokes equations. Aircraft concepts are first developed through low-order multidisciplinary design optimisation based on the design missions and top-level aircraft requirements of the Embraer E190-E2. High-fidelity aerodynamic shape shape optimisation is then applied to wing–body–tail models of each aircraft, with the objective of minimising the weighted-average cruise drag over a five-point operating envelope that includes the nominal design point, design points at $\pm 10\%$ nominal $C_L$ at Mach 0.78, and two high-speed cruise points at Mach 0.81. Design variables include angle-of-attack, wing (and strut) twist and section shape degrees of freedom, and horizontal tail incidence, while nonlinear constraints include constant lift, zero pitching moment, minimum wing and strut volume, and minimum maximum thickness-to-chord ratios. Results show that the multipoint optimised strut-braced wing maintains similar features to those of the single-point optimum, and compromises on-design performance by only two drag counts to achieve up to 11.6% reductions in drag at the off-design conditions. Introducing low-order estimates for approximating full aircraft performance, results indicate that the multipoint optimised strut-braced-wing regional jet offers a 13.1% improvement in cruise lift-to-drag ratio and a 7.8% reduction in block fuel over a 500nmi nominal mission when compared to the similarly optimised Embraer E190-E2-like conventional tube-and-wing aircraft.

This paper describes a new efficient method for the construction of an approximately balanced aerodynamic Reduced Order Model (ROM) via the frequency domain using Computational Fluid Dynamics data. Time domain ROM construction requires CFD data, which is obtained from the DLR TAU RANS or Euler Linearised Frequency Domain (LFD) solver. The ROMs produced with this approach, using a small number of frequency simulations, are shown to exhibit a strong ability to reconstruct the system response for inviscid flow about the NLR7301 aerofoil and the FFAST wing; and viscous flow about the NASA Common Research Model. The latter demonstrates that the reduced order model approach can reconstruct the full order frequency response of a viscous aircraft configuration with excellent accuracy using a strip wise approach. The time domain models are built using the frequency domain, but also give promising results when applied to reconstruct non-periodic motions. Results are compared to time domain simulations, showing good agreement even with small ROM sizes, but with a substantial reduction in calculation time. The main advantage of the current model order reduction approach is that the method does not require the formation and storage of large matrices, such as in POD approaches.

Compression systems of modern, civil aircraft engines consist of three components: Fan, low-pressure compressor (LPC) and high-pressure compressor (HPC). The efficiency of each component has improved over the last decades by means of rising computational power which made high level aerodynamic optimisations possible. Each component has been addressed individually and separated from the effects of upstream and downstream components. But as much time and effort has been spend to improve performance of rotating components, the stationary inter-compressor duct (ICD) has only received minor attention. With the rotating compression components being highly optimised and sophisticated their performance potential is limited. That is why more aggressive, respectively shorter, ICDs get more and more into the focus of research and engine manufacturers. The length reduction offers high weight saving and thus fuel saving potential as a shorter ICD means a reduction in aircraft engine length. This paper aims at evaluating the impact of more aggressive duct geometries on LPC and HPC performance. A multi objective 3D computational fluid dynamics (CFD) aerodynamic optimisation is performed on a preliminary design of a novel two spool compressor rig incorporating four different operating line and two near-stall (NST) conditions which ensure operability throughout the whole compressor operating range. While the ICD is free to change in length, shape and cross-section area, the blades of LPC and HPC are adjusted for changing duct aerodynamics via profile re-staggering to keep number of free parameters low. With this parametrisation length, reductions for the ICD of up to 40% are feasible while keeping the reduction in isentropic efficiency at aerodynamic design point for the compressor below 1%pt. Three geometries of the Pareto front are analysed in detail focusing on ICD secondary flow behaviour and changes of aerodynamics in LPC and HPC. In order to asses changes in stall margin, speedlines for the three geometries are analysed.

A spacetime formulation is presented to solve unsteady aerodynamic problems involving large deformation or topological change such as store separation, slat and flap deployment or spoiler deflection. This technique avoids complex CFD meshing methods, such as Chimera, by the use of a finite-volume approach both in space and time, and permits a locally varying real timestep. The use of a central-difference scheme in the time direction can yield non-physical transient solutions as a consequence of information travelling backwards in time. Therefore, an upwind formulation is provided and validated against one-dimensional and two-dimensional test cases. A hybrid formulation (central in space, upwind in time) is also given and unsteady cases are computed for a spoiler and spoiler/flap deployment, with all three formulations compared, demonstrating that the use of an upwind time stencil yields more representative physical solutions and improves the rate of convergence.

The reduction of computational costs in the context of the Multidisciplinary Design Optimisation of a typical medium-range aircraft was investigated through an assessment of active constraints and the use of multi-fidelity models-based estimation of drag and structural stress. The results show that for this problem, from the set of considered constraints that includes flutter boundary, the active constraint is a 2.5g pull up Maximum Take Off Weight. Results show that the multi-fidelity approach reduced the required high-fidelity aerodynamic number of evaluations, for both drag assessment and stress assessment with sufficient level of accuracy for the former and conservatively for the latter. Further computational cost reduction can be achieved using a surrogate model based Multidisciplinary Design Optimisation. The best configuration attained shows an Aspect Ratio increase of 16%, a reduction of 4.5% in fuel consumption and wing structural weight increase of 2.7% relative to a predefined baseline configuration.

A control system verification framework is presented for unmanned aerial vehicles using theorem proving. The framework’s aim is to set out a procedure for proving that the mathematically designed control system of the aircraft satisfies robustness requirements to ensure safe performance under varying environmental conditions. Extensive mathematical derivations, which have formerly been carried out manually, are checked for their correctness on a computer. To illustrate the procedures, a higher-order logic interactive theorem-prover and an automated theorem-prover are utilised to formally verify a nonlinear attitude control system of a generic multi-rotor UAV over a stability domain within the dynamical state space of the drone. Further benefits of the procedures are that some of the resulting methods can be implemented onboard the aircraft to detect when its controller breaches its flight envelope limits due to severe weather conditions or actuator/sensor malfunction. Such a detection procedure can be used to advise the remote pilot, or an onboard intelligent agent, to decide on some alterations of the planned flight path or to perform emergency landing.

In the era of Unmanned Aerial Systems (UAS), an onboard autopilot occupies a prominent place and is inevitable for many of their modern applications. The efficacy of autopilot heavily relies upon the accuracy of the sensors employed and the capability of the onboard flight controller. In general, aerodynamic behaviour and flight dynamic capabilities of Unmanned Aerial Vehicles (UAVs) govern the selection and the design of flight controllers. Precise modeling of linear aerodynamic characteristics from flight data can be achieved using many of the existing classical parameter estimation techniques such as Output Error Method (OEM), Equation Error Method (EEM), and Filter Error Method (FEM). However, all the classical methods may not be readily applicable for aerodynamic modeling in nonlinear flight envelopes. The current manuscript is an attempt to exploit the capabilities of the Artificial Intelligence (AI) technique, named Particle Swarm Optimisation (PSO), in combination with Least Squares (LS) cost function to perform linear as well as nonlinear aerodynamic parameter estimation. The aforementioned task is accomplished by considering flight data from manoeuvers pertaining to linear angles of attack, moderate and near stall flight envelopes of two different UAVs with cropped delta planform geometry. Parameters estimated using the proposed LS-PSO method are consistent with minimum standard deviation and are on a par with OEM estimates. The proposed LS-PSO method enhances the capabilities of LS-based EEM while estimating stall characteristic parameters, which was not possible with LS alone. The longitudinal and lateral-directional static parameters estimated from the full-scale wind tunnel testing of the two UAVs were also used to corroborate the results obtained from the flight data using the LS-PSO method.

Although the problem of locked-in deep stall is well documented over many years, there currently exists no consistent procedure that can guarantee recovery. Past studies have suggested that it might be possible to rock the aircraft in pitch to destabilise the statically stable deep stall trim point, thereby gaining enough momentum to push the nose down. However, the methods used in these studies are either of preliminary or empirical nature and cannot guarantee recovery. In this paper, we use bifurcation analysis to derive a recovery manoeuvre, specifically by assessing the aircraft’s nonlinear frequency response under an elevator forcing. The ensuing nonlinear Bode plot detects unstable (divergent) solutions near resonance that contribute to a successful deep stall recovery. Moreover, the nonlinear resonant frequency is slightly lower than the result obtained using linear analysis, and time simulation shows that relying on the linear result does not lead to a successful recovery. It is also found that at the high angles of attack associated with deep stall, the frequency separation between the short period and phugoid mode is significantly reduced, leading to only one visible peak in the frequency response. This feature is also reflected in the time-domain step response.

Reinforcement learning has previously been applied to the problem of controlling a perched landing manoeuvre for a custom sweep-wing aircraft. Previous work showed that the use of domain randomisation to train with atmospheric disturbances improved the real-world performance of the controllers, leading to increased reward. This paper builds on the previous project, investigating enhancements and modifications to the learning process to further improve performance, and reduce final state error. These changes include modifying the observation by adding information about the airspeed to the standard aircraft state vector, employing further domain randomisation of the simulator, optimising the underlying RL algorithm and network structure, and changing to a continuous action space. Simulated investigations identified hyperparameter optimisation as achieving the most significant increase in reward performance. Several test cases were explored to identify the best combination of enhancements. Flight testing was performed, comparing a baseline model against some of the best performing test cases from simulation. Generally, test cases that performed better than the baseline in simulation also performed better in the real world. However, flight tests also identified limitations with the current numerical model. For some models, the chosen policy performs well in simulation yet stalls prematurely in reality, a problem known as the reality gap.

The impact of alternative aviation jet fuels and their properties on lean blowout (LBO) limits has recently raised several questions in the jet fuel area. There is a need for a detailed investigation of the impact of fuel properties on the LBO limit involving actual engine hardware. This study investigates the impact of a range of alternative aviation jet fuels with notable differences in physical and chemical properties and derived cetane number (DCN) on the LBO limit and their effects on key performance indicators. LBO performance results for ten different alternative fuels using a Rolls-Royce single-can Tay combustor are presented in this study. The study also assesses impact of different equivalence ratios and flow rates on LBO, with the aim of determining the impact of a certain range of operating conditions. The results are further analysed to determine the influence of fuel chemical and physical properties on the LBO limit. Finally, based on results in the above experiments, individual fuel properties are adjusted for subsequent experimental analysis of blended fuels. With this approach, 25 additional fuel blends are evaluated and presented, with an emphasis on varying the DCN. This study provides effective data and results to facilitate future fuel optimisation and reduce the risk of a negative performance of new fuels in gas turbines.

The objective of the present work is to estimate the performance of a turbojet engine during Fluidic Thrust Vectoring (FTV) employed by injecting the secondary-jet at the throat of a convergent nozzle. The nozzle performance maps and effective nozzle throat area obtained from experiments are coupled with the performance of a conventional engine (without FTV) using an iterative algorithm developed as a part of this work. The performance is estimated for different flow rates of secondary-jet sourced either from a separate compressor or the engine’s compressor. During FTV, the operating point shifted towards the surge line with increased turbine entry temperature. The desired and obtained vector angles and thrust magnitudes are different. At high secondary-jet flow rates, the turbine operation moved out of its performance map. These aspects should be incorporated while integrating the FTV at the system level, thus, asserting the importance of FTV studies coupled with engine performance.

Airports have been frequently affected by different internal and external disruptive events, which generally deteriorated their planned/regular performances. Their resilience is defined as the ability to withstand and maintain a certain level of functionality of performances compared to their reference regular/planned level during the impact of disruptive events and to recover reasonably rapidly afterwards. Robustness is defined as the level of saved functionality of performances compared to their planned/regular level, enabling continuous operations during the impact of disruptive events. The level of deteriorated functionality compared to that of the planned/regular functionality of performances represents their vulnerability. This paper develops a methodology for assessing resilience, robustness and vulnerability of airports affected by a given disruptive event(s). The methodology consists of analytical models of indicators of operational, economic, social and environmental performances of airports and other main actors/stakeholders involved. These indicators are used as figures-of-merit in analytical models for assessing their cumulative and time-dependent resilience, robustness, and vulnerability. The methodology is applied to assess resilience, robustness and vulnerability of two large airports – LHR (London Heathrow, UK) and NYC JFK (John F. Kennedy, US) – affected by a global and lasting external disruptive event – the COVID-19 pandemic disease. Based on the indicators of operational and economic performances, the results indicate very low resilience and robustness and very high vulnerability of both airports and their other main actors/stakeholders involved. Their resilience and robustness based on the indicators of social and environmental performances were not substantively different from the corresponding vulnerability. In absolute terms, LHR airport has been affected stronger than its NYC JFK counterpart. Savings in costs/externalities during the observed period under the given conditions have modestly compensated for total losses of both airports and their main actors/stakeholders involved.

Spinning/Rolling Airframe Missiles (RAM) mostly use an analog (ON-OFF type) control approach that deflects control surfaces (fins) at minimum and maximum positions continuously, and control is achieved by applying phase shift between the minimum and maximum deflections during a complete roll cycle. Therefore, the control signal shape changes continuously during the roll cycle. In this study, a novel single channel digital controller is designed and tested for a high spinning rate (10–20 Hz) RAM. The digital controller adjusts the amplitude of fin deflections instead of applying a phase shift. In this way, control signal shapes are predetermined in design to completely decouple yaw and pitch dynamics. At the beginning of each roll cycle, the algorithm decides on the control signal shape and amplitude to apply throughout the cycle. Delays on the actuator system and sensor measurements which might lead to instability at high spinning rates are handled effectively thanks to the predetermined control signal shapes that are changing with 90-degree intervals. Detailed geometry of a surface-to-air spinning missile is used to obtain aerodynamic coefficients for the entire flight regime (i.e. from launch to terminal phase) via Missile DATCOM. The 6-DOF flight dynamics model and the controller algorithms are built in MATLAB/Simulink environment. The proposed digital controller is tested systematically for various scenarios and the performance is compared with the conventional analog control approach. The digital controller gives better performance compared to the analog approach under the influence of servo delays and sensor noise.

The electrification of the commuter aircraft is instrumental in the development of novel propulsion systems. The scope of this work aims to explore the design space of a parallel hybrid-electric configuration with an entry into service date of 2030 and beyond and determine the impact of other disciplines on conceptual design, such as components positioning, aircraft stability and structural integrity. Three levels of conceptual sizing are applied and linked with a parametric aircraft geometry tool, to generate the aircraft’s geometry and position the components. Subsequently, the structural optimisation of the wing box is performed, providing the centre of gravity of the components placed inside the wing, that minimise the induced stresses. Furthermore, the stability and trim analysis follow, with the former being highly affected by the positioning of components. Results are compared to a similar aircraft with entry into service technology of 2014 and it is indicated that in terms of block fuel reduction the total electrification benefit increases with the increase of degree of hybridisation, if aircraft mass is kept constant. On the other hand, if battery specific energy is kept constant, similar block fuel reduction is possible with lower hybridisation degrees. The potential for improvement in terms of carbon dioxide emissions and block fuel reduction ranges from 15.73% to 21.44% compared to the conventional aircraft, for levels of battery specific energy of 0.92 and 1.14 kWh/kg respectively. Finally, the component positioning evaluation indicates a maximum weight limitation of 240 kg for the addition of an aft boundary layer ingestion fan to a tube and wing aircraft configuration, without compromising the aircraft static stability.