The ground delay program (GDP) is a commonly used tool in air traffic management. Developing a departure flight delay prediction model based on GDP can aid airlines and control authorities in better flight planning and adjusting air traffic control strategies. A model that combines the improved sparrow search algorithm (ISSA) and Multilayer Perceptron (MLP) has been proposed to minimise prediction errors. The ISSA uses tent chaotic mapping, dynamic adaptive weights, and Levy flight strategy to enhance the algorithm’s accuracy for the sparrow search algorithm (SSA). The MLP model’s hyperparameters are optimised using the ISSA to improve the model’s prediction accuracy and generalisation performance. Experiments were performed using actual GDP-generated departure flight delay data and compared with other machine learning techniques and optimisation algorithms. The results of the experiments show that the mean absolute error (MAE) and root mean square error (RMSE) of the ISSA-MLP model are 16.8 and 24.2, respectively. These values are 5.61%, 6.3% and 1.8% higher in MAE and 4.4%, 5.1% and 2.5% higher in RMSE compared to SSA, particle swarm optimisation (PSO) and grey wolf optimisation (GWO). The ISSA-MLP model has been verified to have good predictive and practical value.

This paper proposes a methodology to define and quantify the precision uncertainties in aerothermodynamic cycle model comparisons. The total uncertainty depends on biases and random errors commonly found in such comparisons. These biases and random errors are classified and discussed based on observations found in the literature. The biases account for effects such as differences in model inputs, the configurations being simulated, and thermodynamic packages. Random errors consider the effects on the physics modeling and numerical methods used in cycle models. The methodology is applied to a comparison of two cycle models, designated as the model subject to comparison and reference model, respectively. The former is the so-called Aerothermodynamic Generic Cycle Model developed in-house at the Laboratory of Applied Research in Active Control, Avionics and AeroServoElasticity (LARCASE); the latter is an equivalent model programmed in the Numerical Propulsion System Simulation (NPSS). The proposed methodology is intended to quantify the bias and random errors effects on different cycle parameters of interest, such as thrust, specific fuel consumption, among others. Each bias and random errors are determined by deliberately preventing the effects from other biases and random errors. The methodology presented in this paper can be extended to other cycle model comparisons. Moreover, the uncertainty figures derived in this work are recommended to be used in other model comparisons when no better reference is available.

Most simple ailerons produce adverse yaw. However, with proper aileron placement and wing twist, an aileron can produce proverse or neutral yaw, eliminating the need for aileron-rudder mixing, differential aileron deflection or Frise ailerons. The relationship between wing planform, aileron placement and lift distribution is studied here for a special class of optimal lift distributions that minimise induced drag for a variety of design constraints. It is shown that a wing employing the elliptic lift distribution will always produce adverse yaw, independent of aileron design or operating condition. However, for wings employing other optimal lift distributions, the ailerons can be placed to produce proverse or neutral yaw. A numerical lifting-line algorithm is used to explore the impact of aileron design on a wide range of wing planforms and lift distributions. Results can be used in the early stages of design to correctly place ailerons with respect to desired roll-yaw coupling.

The BLI (boundary layer ingestion) concept for propulsion seeks to improve the energy efficiency of aircraft propulsion. This is achieved by accelerating low momentum flow ingested from boundary layers and wakes developed over the fuselage through the fan. A major challenge that needs to be overcome to realise the benefits is that the fan needs to work efficiently in distorted flow. Understanding the effects of distortion on the aerodynamic performance and the distortion transfer through the fan is therefore essential to future designs. A BLI fan, designed at reduced scale, is used for analytic modelling and experiments in a rig designed for this purpose. The test rig replicates BLI conditions for a fan installed at the aircraft tail cone. An unsteady model that includes all blades and vanes of the fan, as well as the nacelle and the by-pass duct of the test rig is used for CFD (computational fluid dynamics) simulations. Test results are used to confirm that the CFD model is representative of the aerodynamics of the fan. The tests are conducted using varying fan operating conditions but also tests with an added distortion screen. Analysis results are then used to investigate the effects of distortion on the fan efficiency, as well as on the overall efficiency. The fan efficiency is found to be moderately decreased depending on the level of and extent of inlet circumferential distortion. In terms of overall energy efficiency, a net improvement over a similar fan in clean inlet flow is found.

There are instances when an aircraft encounters a bird’s flock or faces a heavy hailstorm, causing the windshield to sustain consecutive impacts. Therefore, the investigation of windshield resistance against repeated impacts is crucial. In this research, various tests such as tensile, split Hopkinson pressure bar (SHPB), and three-point bending are conducted to extract the mechanical properties of the materials used in a five-layers windshield under high strain rates. Using this information, the bird impact on the windshield is simulated using the smooth particle hydrodynamics (SPH) method, and the results are compared with real bird impact test outcomes, and the validation of this simulation is confirmed. The simulation of two consecutive bird strikes indicates the current windshield lacks sufficient resistance against successive dual impacts; in such scenarios, the second bird penetrates the windshield after breaking it and tearing the interlayer. Considering new materials and thicknesses for each windshield layer, a Taguchi experimental design method is employed to examine various layer arrangements with different materials and thicknesses. The configurations in which the windshield can withstand a maximum of three bird impacts in succession are identified. Subsequently, using the “the smaller, the better” criterion in the Taguchi optimisation approach, the configuration that not only prevents bird penetration but also minimises the maximum strain in the inner layer is selected as the desired outcome. Thus, a new five-layer windshield with new materials and thicknesses is presented, which is resistant to the repeated collision of up to three birds, tearing in the interlayer and bird penetration does not happen.

To enhance the impact resistance capacity and ensure the floatability of aircraft after ditching, the slamming response of three types of aircraft sub-floor structures are investigated including the flat, cylindrical and ellipsoidal under floor. A coupled Finite Element-Smooth Particle Hydrodynamic (FE-SPH) method is employed with focus on non-linear structural collapse in fluid-structure interaction. The material is defined by bilinear elastic plastic law, and the strain rate effect is taken into account. Further, comparison and analyses are performed in terms of acceleration, local pressure and strains at different speeds. Results show that conventional flat sub floor structures perform poorly during ditching due to excessive peak acceleration and pressure. By contrast, the peak acceleration of ellipsoidal under floor is lower at all measured speeds and the pressure on the sides is reduced. Moreover, the ellipsoidal sub-floor with bi-directional curvature generates smaller plastic strain and deflection of skin, demonstrating better mechanical properties in water impact scenarios.

Every manufacturing procedure is subject to tolerance variations. Over the years, a set of key characteristic features (KCF) that can explain the effect of manufacturing variations on the aero-mechanical performance of a fan blade has been devised and monitored to ensure conformality and good performance. The KCFs are derived from a cloud of coordinate measurement machine (CMM) points and are defined on approved engineering drawings for the manufactured part. In this paper, it is demonstrated that some of the traditional, common wisdom KCFs are not adequate to explain the engine performance deviation behaviour on a test bed at the sea-level condition. On the other hand, good correlation is found by analysing a set of engineering parameters drawn from a new inverse-mapping procedure of the CMM data. It is further demonstrated that a deviation measured via CMM or 3D structured light (GOM) data in cold conditions can be translated to a variation in the hot running shape of the blade. Having identified the key blade features, a cheap alternative to modifying the manufacturing procedure is devised to recover the fan performance by optimising its leading-edge shape.

Free route airspace (FRA) are increasingly widespread in European countries. A step further, cross-border FRA aims to implement FRA in a seamless,defragmented airspace in Europe. This study aims to bring a different perspective by extending the scope of cross-border FRA applications beyond socioeconomic status (SES) countries. In the study, analyses were made using fast-time simulation outputs for one of the busiest days of Turkish airspace in 2022. The simulation models of four cases were created and compared in such a way that airspaces of Türkiye, South East Europe free route airspace (SEEFRA) countries and Ukraine combined under different border operations above FL285. Flight trajectories were assessed in terms of flight distance, fuel economy and environmental impact within the aforementioned airspaces. The participation of Turkish airspace in the cross-border region and opening of Ukrainian airspace are examined. Concluded, among all, cross-border FRA implemented through all aforementioned regions (Case 4) may constitute the best benefit for flight trajectories and related variables.

Axial fans are vital accessories in aircraft ventilation systems, but, they may experience erosion from particulate flows, causing a decline in effectiveness over time. This study investigated the trajectories of two types of sand particles and erosion in an axial fan stage, considering the relative position of the blades facing the inlet guide vanes.

The movement of particles was simulated using an in-house code that implements a Lagrangian approach along with a stochastic particle-eddy interaction model. The flow field was solved separately and the flow data was transferred to the particle trajectory code. The finite element method allowed for the tracking of particles through the computational cells and accurate determination of their impact positions. A semi-empirical erosion correlation was used to evaluate the local erosion rates, mass removal, and geometry deterioration.

As a result, the rotor exhibits a high frequency of impacts and significant erosion on the leading edge of the blade, extending to the upper corner of the pressure side and blade tip, as well as the front of the suction side. In the inlet guide vane, the erosion is spread out along the entire pressure side but at lower erosion rates compared to the rotor blade. The erosion patterns obtained at different pitch-wise positions were cumulated to get better representation of erosion patterns. After being exposed to MIL-E5007E sand (0–1000 $\unicode{x03BC}$m) at the highest concentration for 10 hours, the blade experienced a reduction of a 0.29% in mass, a 0.45% decrease in tip chord, and a 0.23% increase in tip clearance. On the other hand, AC-coarse sand (0–200 μm) resulted in a 0.23% decrease in blade mass, a 0.4% reduction in tip chord, and a 0.16% increase in tip clearance.

The data that is available can be used to monitor the lifespan of axial fans of similar design and select appropriate coatings to protect against erosion.

This paper proposes a robust generalised dynamic inversion (GDI) control system design with adaptive neural network (NN) estimation for spacecraft attitude tracking under the absence of knowledge of the spacecraft inertia parameters. The robust GDI control system works to enforce attitude tracking, and the adaptive NN augmentation compensates for the lack of knowledge of the spacecraft inertia parameters. The baseline GDI control law consists of a particular part and an auxiliary part. The particular part of the GDI control law works to realise a desired attitude dynamics of the spacecraft, and the auxiliary part works for finite-time stabilisation of the spacecraft angular velocity. Robustness against modeling uncertainties and external disturbances is provided by augmenting a siding mode control element within the particular part of the GDI control law. The singularity that accompanies GDI control is avoided by modifying the Moore-Penrose generalised inverse by means of a dynamic scaling factor. The NN weighting matrices are updated adaptively through a control Lyapunov function. A detailed stability analysis shows that the closed loop system is semi-global practically stable. For performance assessment, a spacecraft model is developed, and GDI-NN control is investigated for its attitude control problem through numerical simulations. Simulation results reveal the efficacy, robustness and adaptive attributes of proposed GDI-NN control for its application to spacecraft attitude control.

Bird strike accidents are critical threats for aviation safety especially in airport airspaces. Environment friendly solutions are preferred for wildlife managements to achieve harmonic coexistence between airports and surrounding environments. Avian radar systems are the most effective remote sensing approach for long-range and all-weather birds monitoring. Massive historical avian radar datasets and other data sources provide an opportunity to explore relevance between bird behaviour and environments. This paper proposes a bird behaviour characterisation and prediction method to reveal bird behaviour dependency with weather parameters. Bird behaviours are modelled as indices and grades from selected avian radar datasets. Weather dependence are studied from single parameter to multivariable parameters. The random forest model is selected as a behaviour grade prediction model taking four weather parameters as system inputs. Radar datasets for diurnal and nocturnal birds are constructed to validate their behaviour characters and prediction performance, respectively. Experiment results verify the feasibility of bird behaviour prediction using weather parameters, but also reflect some insufficiencies within the proposed method. Data sufficiency and severe weather considerations are also discussed to analyse their impact on prediction accuracy. A more comprehensive prediction model with standardised avian radar data quality and enhanced weather information accuracy is promising to further elevate the application significance of the proposed method.

In this paper, a super-twisting disturbance observer (STDO)-based adaptive reinforcement learning control scheme is proposed for the straight air compound missile system with aerodynamic uncertainties and unmodeled dynamics. Firstly, neural network (NN)-based adaptive reinforcement learning control scheme with actor-critic design is investigated to deal with the tracking problems for the straight gas compound system. The actor NN and the critic NN are utilised to cope with the unmodeled dynamics and approximate the cost function that are related to control input and tracking error, respectively. In other words, the actor NN is used to perform the tracking control behaviours, and the critic NN aims to evaluate the tracking performance and give feedback to actor NN. Moreover, with the aid of the STDO disturbance observer, the problem of the control signal fluctuation caused by the mismatched disturbance can be solved well. Based on the proposed adaptive law and the Lyapunov direct method, the eventually consistent boundedness of the straight gas compound system is proved. Finally, numerical simulations are carried out to demonstrate the feasibility and superiority of the proposed reinforcement learning-based STDO control algorithm.

In this study a representative sandwich panel is investigated statically in two different configurations under similar bending loads. In one configuration serrations are introduced in the honeycomb core while the other one has un-modified core. Three-point bend test (TPBT) has been performed on both configurations through Finite Element Analysis (FEA) technique using ANSYS Workbench considering American Society for Testing and Materials (ASTM) standards. In both configurations the same aluminium honeycomb core is modelled having an adhesive layer in between adjacent foils to simulate actual scenario instead of relying on the block properties. Honeycomb core offers highest strength in its thickness (T) direction or the z-direction by virtue of its shape. Any distortion in the shape of the honeycomb adversely affects its strength. During bending the honeycomb core witnesses multidirectional forces consequently leading to distortion or crumpling. The serrations in the structure allow bending of the honeycomb core with minimal loss of strength by limiting the deformation to a specific region consequently preserving the shape as well as the strength of the honeycomb core. The results of both samples are compared with respect to deflection, strain and reaction force. It proves that serrated core is more favourable to be used in bent or curved sandwich panels.

The objective of this research is to predict the delays in the departure of scheduled commercial flights through a methodology that uses predictive tools based on machine learning/deep learning (ML/DL), with supervised training in regression, based on the available flight datasets. Since the novel contribution of this work is, first, to make the comparison of the predictions in terms of means and statistical variance of the different ML/DL models implemented and, second, to determine the coefficients of the importance of the features or flight attributes, using ML methods known as permutation importance, it is possible to rank the importance of flight attributes by their influence in determining the delay time and reduce the problem of selecting the most important flight attributes. From the results obtained, it is worth mentioning that the model that presents the best performance is the ensemble or combinatorial method of random forest regressor models, with an acceptable prediction range (measured with the root-mean-square-error).

Gas turbine engine starting models require a lot of calibration to represent reality with acceptable accuracy due to the lack of high-quality component rig data in the sub-idle region. A detailed sensitivity study is presented in this paper to guide such calibration efforts. A thermodynamic component-matching type transient model of a single-spool turbojet engine with shaft and heat-soakage dynamics is employed for this purpose. Turbomachinery component maps are extended to sub-idle using an in-house map smoothing tool and the strategies presented by Kurzke recently. These extension strategies make use of the correlations hidden in the already available regions of the maps and ensure physical consistency. However, they contain some uncertainty, even when an experimentally obtained zero-speed line is available. Combustor sub-idle efficiency, stability limits, and delay are taken from the literature. Due to the chaotic nature of a combustor in the sub-idle region, a precise prediction of the combustor efficiency seems impossible. Effects of uncertainties related to sub-idle turbomachinery map extensions, burner efficiency, and heat soakage are investigated in this paper. Two popular fuel control strategies are employed and compared to see how controls deal with these uncertainties. It is concluded that turbomachinery torque characteristics and turbine capacities are the most important parameters when calibrating a starting model with a control based on rotational acceleration while burner efficiency and heat soakage are added on top of these with a control based on fuel flow rate.

The distinct operational characteristics of military aircraft, relative to civil aircraft, have impeded the standardisation of airworthiness management practice across Europe. Standardisation has been further deterred by the intertwined certification and qualification activities specific to military aircraft. The management of airworthiness in European military aviation has undergone significant changes over the past 15 years, with the progress made attributed to the harmonisation efforts driven by the European Defence Agency (EDA). The creation of a Military Airworthiness Authorities Forum and the development of the European Military Airworthiness Requirements (EMAR) have been instrumental in creating a more homogenous regulatory landscape. The examples of five main players of the European aerospace sector, namely France, Italy, Germany, Spain and the United Kingdom, are examined from the point of view of adoption and implementation of an EMARs-based system. Their regulatory structures have revealed similarities and primary differences. The EMAR’s framework has enabled a gradual build-up of technical knowhow within the European countries who embraced this, civil-based, framework. All five countries have adopted EMARs, though through a variety of regulatory constructs. Their regulatory structures exhibit diverse practices, especially in how initial and continuing airworthiness is managed. Some countries have also elected to have more than one authority overseeing/been responsible for airworthiness. Closer collaboration between national Military Aviation Authorities (MAAs) can be achieved through standardisation at regulatory structure level. The establishment of a joint MAAs may be the next logical step in the harmonisation process, in line with EDA objective’ for a EU-wide authority with greater powers.

Within the context of preliminary aerodynamic design with low order models, the methods have to meet requirements for rapid evaluations, accuracy and sometimes large design space bounds. This can be further compounded by the need to use geometric and aerodynamic degrees of freedom to build generalised models with enough flexibility across the design space. For transonic applications, this can be challenging due to the non-linearity of these flow regimes. This paper presents a nacelle design method with an artificial neural network (ANN) for preliminary aerodynamic design. The ANN uses six intuitive nacelle geometric design variables and the two key aerodynamic properties of Mach number and massflow capture ratio. The method was initially validated with an independent dataset in which the prediction error for the nacelle drag was 2.9% across the bounds of the metamodel. The ANN was also used for multi-point, multi-objective optimisation studies. Relative to computationally expensive CFD-based optimisations, it is demonstrated that the surrogate-based approach with ANN identifies similar nacelle shapes and drag changes across a design space that covers conventional and future civil aero-engine nacelles. The proposed method is an enabling and fast approach for preliminary nacelle design studies.

Stray light from the sun is one of the most significant factors affecting image quality for the optical system of a spacecraft. This paper proposes a method to design a deployable supporting mechanism for the sunshield based on origami. Firstly, a new type of space mechanism with single-closed loop was proposed according to thick-panel origami, and its mobility was analysed by using the screw theory. In order to design a deployable structure with high controllability, the tetrahedral constraint was introduced to reduce the degree of freedom (DOF), and a corresponding deployable unit named tetrahedral deployable unit (TDU) was obtained. Secondly, the process to constructing a large space deployable mechanism with infinite number of units was explained based on the characteristics of motion and planar mosaic array, and kinematics analysis and folding ratio of supporting mechanism were conducted. A physical prototype was constructed to demonstrate the mobility and deployment of the supporting mechanism. Finally, based on the Lagrange method, a dynamic model of supporting mechanism was established, and the influence of the torsion spring parameters on the deployment process was analysed.

Stable separation is a crucial condition that must be met in order for combined aircraft to successfully engage in cooperative flight. In order to achieve the desired fast and controlled separation, this paper proposes a novel design for a torque-driven compliant separation mechanism. By taking into account the compliance characteristics of a sinusoidal acceleration function curve, a mechanical model for the separation mechanism is developed. By utilising the Coulomb friction law, an accurate determination of the aerodynamic load distribution under various conditions is achieved. Subsequently, the relationship between the unlocking moment and the aerodynamic load is derived based on these findings. Through the utilisation of the finite element method, a model of the separation mechanism is generated. To ensure the safety and reliability of the compliant separation mechanism, the mechanical properties of the structural materials are thoroughly analysed under the maximum aerodynamic load. Subsequently, the separation mechanism structure is constructed and subjected to testing in order to showcase the compliance characteristics. In addition, this paper conducts a simulation to analyse the impact of flight speed and angle-of-attack on the separation process. By doing so, the optimal conditions for separation are determined. The methods and findings presented in this study have the potential to contribute valuable insights to the design of combined aircraft.

This paper presents some of the first results of global linear stability analyses performed using a bespoke eigensolver that has recently been implemented in the next generation flow solver framework CODA. The eigensolver benefits from the automatic differentiation capability of CODA that allows computation of the exact product of the Jacobian matrix with an arbitrary complex vector. It implements the Krylov–Schur algorithm for solving the eigenvalue problem. The bespoke tool has been validated for the case of laminar flow past a circular cylinder with numerical results computed using the TAU code and those reported in the literature. It has been applied with both second-order finite volume and high-order discontinuous Galerkin schemes for the case of laminar flow past a square cylinder. It has been demonstrated that using high-order schemes on coarser grids leads to well-converged eigenmodes with a shorter computation time compared to using second-order schemes on finer grids.