Emergency search and rescue on the sea is an important part of national emergency response for marine perils. Optimal route planning for maritime search and rescue is the key capability to reduce the searching time, improve the rescue efficiency, as well as guarantee the rescue target’s safety of life and property. The main scope of the searching route planning is to optimise the searching time and voyage within the constraints of missing search rate and duplicate search rate. This paper proposes an optimal algorithm for searching routes of large amphibious aircraft corresponding to its flight characteristics and sea rescue capability. This algorithm transforms the search route planning problem into a discrete programming problem and applies the route traceback indexes to satisfy the duplicate search rate and missing search rate.

Flight delays may be decreased in a predictable way if the Weibull wind speed parameters of a runway, which are an important aspect of safety during the take-off and landing phases of aircraft, can be determined. One aim of this work is to determine the wind profile of Hasan Polatkan Airport (HPA) as a case study. Numerical methods for Weibull parameter determination perform better when the average wind speed estimation is the main objective. In this paper, a novel objective function that minimises the root-mean-square error by employing the cumulative distribution function is proposed based on the genetic algorithm and particle swarm optimisation. The results are compared with well-known numerical methods, such as maximum-likelihood estimation, the empirical method, the graphical method and the equivalent energy method, as well as the available objective function. Various statistical tests in the literature are applied, such as R2, Root-Mean-Square Error (RMSE) and $\chi$2. In addition, the Mean Absolute Error (MAE) and total elapsed time calculated using the algorithms are compared. According to the results of the statistical tests, the proposed methods outperform others, achieving scores as high as 0.9789 and 0.9996 for the R2 test, as low as 0.0058 and 0.0057 for the RMSE test, 0.0036 and 0.0045 for the MAE test and 3.53 × 10−5 and 3.50 × 10−5 for the $\chi$2 test. In addition, the determination of the wind speed characteristics at HPA show that low wind speed characteristics and regimes throughout the year offer safer take-off and landing schedules for target aircraft. The principle aim of this paper is to help establish the correct orientation of new runways at HPA and maximise the capacity of the airport by minimising flight delays, which represent a significant impediment to air traffic flow.

To reduce fan noise and weight, according to the structural characteristics of a turbofan engine, a fan rotor with an ultra-low rotating speed is designed in this study by using a new concept of diffusion blade profiles in which the rotating speed of an ultra-highly loaded rotor is only 0.58 times that of a normally loaded rotor. To further examine the applicability of this rotor, its matching stator is also designed. The flow fields in the ultra-highly and normally loaded fan stages are simulated using the same numerical method to conduct an aerodynamic characteristic comparison. Compared with the normally loaded rotor, the sizes of the boundary layers on the blade surfaces, the wakes behind the blades and the flow losses of the ultra-highly loaded rotor are smaller. At the design point, the efficiency of the ultra-highly loaded fan stages is higher than that of the normally loaded stage; moreover, the surge margin of the former is evidently larger than that of the latter. The ultra-highly loaded fan could be a good candidate for use in Ultra-High Bypass Ratio Geared Turbofan (UHBRGT) technology.

The rotating instability in a contra-rotating axial flow compressor is investigated by experiments. Twenty-four pressure sensors were installed on the casing to capture the unsteady flow in the rotor tip region simultaneously. A double-phase-locking technique suitable for the contra-rotating compressor was proposed to characterise the static pressure contours of the rotor tip. The mean and root-mean-square pressure contours indicate that rotating instability occurs before the rotating stall happened, and the rotor tip clearance vortex is located upstream of the rear rotor leading edge plane before stall. Fourier spectrum shows that rotating instability and rotating stall both happened under the stall condition, and the frequency band of rotating instability does not change with the flow rate. In the front rotor, the frequency of rotating instability is half of the blade passing frequency. It is verified that the modal estimation method can be implemented by using the average azimuthal phase velocity, which significantly reduced the number of pressure sensors required. Modal estimation results show that each peak of the rotating instability frequency band corresponds to a unique dominant circumferential mode. By optimising average azimuthal phase velocity, an improved modal estimation method is obtained, which can further improve the reliability of the modal estimation results.

The research focuses on the design space optimisation of National Advisory Committee for Aeronautics (NACA) submerged inlets through the formulation of a hybrid data fusion methodology. Submerged inlets have drawn considerable attention owing to their potential for good on-design performance, for example during cruise flight conditions. However, complexities due to the geometrical topology and interactions among various design variables remain a challenge. This research enhances the current design knowledge of submerged inlets through the utilisation of data mining and Computational Fluid Dynamics (CFD) methodologies, focusing on design space optimisation. A two-pronged approach is employed where the first step encompasses a low-fidelity model through data mining and surrogate modelling to predict and optimise the design parameters, while the second step uses the Design of Experiments (DOE) approach based on the CFD results for the candidate design geometry to construct a surrogate model with high fidelity for design refinement. The feasibility of the proposed methodology is demonstrated for the optimisation of the total pressure recovery of a NACA submerged inlet for the subsonic flight regime. The proposed methodology is found to provide good agreement between the surrogate and CFD-based model and reduce the optimisation processing time by half in comparison with conventional (global-based) CFD optimisation approaches.

New alternative jet fuels have provided many advantages in the aviation industry, especially in terms of economics and environment. However, fuel–seal compatibility is one of the major issues that restricts alternative fuel advancement into the market. Thus, to help understand and solve the problem, this study examines the swelling effect of prepared and non-prepared O-rings in different fuels and aromatic species. Stress relaxation experiments were carried out to evaluate seal compatibility under compression, which mimics engine operation conditions. Seals were compressed and immersed in a variety of fuels and their blends for about 90h while maintaining a constant temperature 30°C and constant compression force of 25% seal thickness. The two types of elastomers investigated were fluorosilicone and nitrile O-rings, which are predominantly used in the aviation industry. Meanwhile, three different fuels and aromatic species were utilised as the variables in the experiments. The fuels used were Jet-A1, SPK and SHJFCS, while the aromatic species added were propyl benzene, tetralin and p-xylene. The swelling effects were determined from the P/Po value. Results indicate that Jet-A1 has the highest swelling effect, followed by SHJFCS and SPK. It was observed that the higher the percentage of aromatics in fuel, the higher the rate of swelling. Furthermore, prepared seals had a lower swelling rate than did non-prepared seals. Meanwhile, the intensity of the swelling effect in the Jet-A1-SHJFCS blends was in the order of 60/40, 85/15 and 50/50 blend. The work done in this study will aid in the selection of suitable aromatic species in future fuels. The novelty of this research lies in the determination of the appropriate amount of aromatic content as well as the selection of type of aromatic and its mixture fuel. Moreover, the various proportions of fuel blends with aromatic are investigated. The primary aim of this study is to understand the behaviour of prepared and non-prepared seals, and their compatibility with alternative fuels.

The capability of aircraft tyres to sustain landing impact loads is essential for flight landing safety. Hence, the development of a reliable experimental database is necessary to validate numerical models. The experimental data on aircraft tyre landing impact in the public literature are somewhat sparse. This paper describes a detailed design rig for aircraft tyre impact testing. A finite element model is then created and simulated using a finite element tool (ABAQUS). Inflation and static load simulations are analysed based on the FE tyre model to confirm its reliability. Comparison of experimental measurements with the results reveals that the model can predict the significant features of aircraft tyre impact in a landing scenario. Very little experimental data are publicly available to verify aircraft tyre models. Therefore, the experimental data in this paper fill this gap in the literature.

Metal-composite airframes will suffer various defects during their lifetime. One category of defects is composite laminate delamination. This study evaluates the criticality of delaminations existing around adjacent fastener holes in the carbon-fibre-reinforced plastic spar web of the F/A-18 aircraft’s trailing-edge flap. The evaluation is based on experiments and analyses. First, an intensive experimental program for determining necessary material values of F/A-18 is described. Multiple delaminations of the flap spar web are then modelled by varying the set of delaminated hole edges and the interface of delamination. The interaction of defects at the start of delamination propagation is studied via the developed interaction parameter. The results suggest that the interaction parameter can show significant differences in the interaction per delamination case and that the interface of delamination is an important variable. Finally, operator-dependent control parameters are studied, and it is found that the criticality of a delamination case is merely dependent on true material parameters.

Accurate navigation is required in many Unmanned Aerial Vehicle (UAV) applications. In recent years, GNSS Precise Point Positioning (PPP) has been recognised as an efficient approach for providing precise positioning services. In contrast to the widely used Real-Time Kinematic (RTK), PPP is independent of reference stations, which greatly broadens its scope of application. However, the accuracy and reliability of PPP can be significantly decreased by poor GNSS satellite geometry and outage. In response, a real-time four-constellation GNSS PPP is applied to improve the geometry in this work, and PPP is tightly coupled with an Inertial Measurement Unit (IMU) to smooth the position and velocity output, thus improving the robustness of the navigation solution. Experimental flight tests are carried out using a UAV in an open-sky area, and GNSS-challenged environments are simulated. The results show that the four-constellation GNSS PPP/IMU integration reduces the Root-Mean-Square (RMS) Three-Dimensional (3D) positioning and velocity error by 76.4% and 67.1%, respectively, in open sky with respect to the one-GNSS PPP. Under scenarios where GNSS measurements are insufficient, the coupled system can still provide continuous solutions. Moreover, the coupled PPP/IMU system can also maintain the convergence of PPP during GNSS-challenged periods and can greatly shorten the re-convergence period of PPP when the UAV returns to the open sky.

On the basis of air heater characteristics, a new computational model was developed in this paper, which was aimed at investigating acoustics and instabilities in air heaters. This model included the effects of mean flow, viscosity, entropy waves, non-linear acoustics and realistic boundary conditions. In addition, it was practical for air heaters with hundreds of injectors, complex configurations and geometries. Analytical solutions of acoustics in a closed rectangular cavity were used to verify and validate the computational model. It was shown that the predicted critical parameters of air heater agreed well with the experimental data or design values. This model predicted the self-excited spinning tangential modes without any preliminary assumptions about them. Traditional combustion response function assumes that combustion mainly takes place in a so-called rapid combustion zone, and this zone is usually modelled as a disc in the combustor near the injection head. However, in practice, the flame has a spatial distribution. This paper described the effect of flame spatial distribution on predictions of oscillation frequency and mode. It was found that frequency and mode shape of oscillations closely depended on the length of the heat release zone. Comparison of different heat release zones indicated that the increment of heat release length exhibited an increased tendency toward lower-order longitudinal modes, when the heat release zone was located near the faceplate where it was the pressure antinode of the longitudinal mode. Modulation of heat release length might cause bifurcations between standing and turning modes. A noticeable tendency was toward higher-order standing tangential mode with increasing heat release length. Finally, theoretical analysis of the modal behaviour, i.e. standing or spinning waves, was performed.

We present a hybrid, semi-analytical approach to perform an eigenvalue-based flutter analysis of an Unmanned Aerial Vehicle (UAV) wing. The wing has a modern design that integrates metal and composite structures. The stiffness and natural frequency of the wing are calculated using a Finite Element (FE) model. The modal parameters are extracted by applying a recursive technique to the Lanczos method in the FE model. Subsequently, the modal parameters are used to evaluate the flutter boundaries in an analytical model based on the p-method. Two-degree-of-freedom bending and torsional flutter equations derived using Lagrange’s principle are transformed into an eigenvalue problem. The eigenvalue framework is used to evaluate the stability characteristics of the wing under various flight conditions. An extension of this eigenvalue framework is applied to determine the stability boundaries and corresponding critical flutter parameters at a range of altitudes. The stability characteristics and critical flutter speeds are also evaluated through computational analysis of a reduced-order model of the wing in NX Nastran using the k- and pk-methods. The results of the analytical and computational methods are found to show good agreement with each other. A parametric study is also carried out to analyse the effects of the structural member thickness on the wing flutter speeds. The results suggest that changing the spar thickness contributes most significantly to the flutter speeds, whereas increasing the rib thickness decreases the flutter speed at high thickness values.

In this study, prediction of aircraft Estimated Time of Arrival (ETA) is proposed using machine learning algorithms. Accurate prediction of ETA is important for management of delay and air traffic flow, runway assignment, gate assignment, collaborative decision making (CDM), coordination of ground personnel and equipment, and optimisation of arrival sequence etc. Machine learning is able to learn from experience and make predictions with weak assumptions or no assumptions at all. In the proposed approach, general flight information, trajectory data and weather data were obtained from different sources in various formats. Raw data were converted to tidy data and inserted into a relational database. To obtain the features for training the machine learning models, the data were explored, cleaned and transformed into convenient features. New features were also derived from the available data. Random forests and deep neural networks were used to train the machine learning models. Both models can predict the ETA with a mean absolute error (MAE) less than 6min after departure, and less than 3min after terminal manoeuvring area (TMA) entrance. Additionally, a web application was developed to dynamically predict the ETA using proposed models.

This paper aims to accurately estimate the lateral directional aerodynamic parameters in real time irrespective of the variations in the process and measurement covariance matrices. The proposed algorithm for parameter estimation is based on the integration of adaptive techniques into a stochastic nonlinear filter. The proposed adaptive estimation algorithm is applied to flight test data, and the lateral directional derivatives are estimated in real time. The estimates are compared with those obtained from the Filter Error Method (FEM), an offline parameter estimation method accounting for process noise. The estimation results are observed to be very comparable, and the supremacy of the adaptive filter is illustrated by varying the covariance matrices of both process and measurement noises. The parameters estimated by the adaptive filter are found to converge to their actual values, whereas the estimates of the regular filter are observed to diverge from the actual values when changing the noise covariance matrices. The proposed adaptive algorithm can estimate the lateral directional aerodynamic derivatives more accurately without prior knowledge of either process or measurement noise covariance matrices. Hence, it is of great value in online implementations.

The use of a submerged inlet is advantageous in modern aircrafts because of its low drag resistance, small radar cross section and ease of maintenance. Although it is well known that the forebody boundary layer deteriorates the aerodynamic performance of a submerged inlet, the level of impact has not yet been fully quantified. To quantify the forebody boundary-layer effect, a submerged diverter was designed to remove a portion of the low-energy boundary flow. The flow pattern and aerodynamic performance of a submerged inlet, with and without the diverter, were investigated by wind-tunnel experimentation and numerical simulations. The effects of mass flow, free stream speed, angle-of-attack and sideslip angle on the aerodynamic characteristics of the inlet with and without the submerged diverter were studied, over an operating envelope of M0 = 0.3 ∼ 0.6, $\alpha$ = –6$^{\circ}$ ∼ 8$^{\circ}$ and $\beta$ = 0$^{\circ}$ ∼ 4$^{\circ}$. The results indicate that both the total pressure loss and the circumferential distortion can be significantly reduced with the removal of the forebody boundary-layer low-energy flow. Meanwhile, the main mechanisms for losses in the submerged inlet were also analysed.

The design and development of Stratospheric Airships for High-Altitude Long-Endurance missions (HALESAs) has generated interest worldwide. Conventional airships usually have a single-lobed axisymmetrical envelope shape. In contrast, several non-axisymmetric envelope configurations have been proposed for the HALESAs, such as flattened single lobed and multi lobed. This paper describes a methodology for carrying out a comparative analysis of a conventional HALESA and the multi-lobed HALESA designed for the same design mission. A sizing methodology which enables the estimation of its design parameters to meet some user-specified requirements has been developed for airships with envelopes of both these shapes. A Multidisciplinary Design Optimisation (MDO) approach has been followed in this methodology, which includes considerations from the disciplines of aerodynamics, energy, environment and structures. The study indicates that the envelope volume, solar array area and total mass of the single-lobed conventional airship are better than those of the tri-lobed HALESA. While the multi-lobed HALESA has the advantage of a flatter upper surface resulting in higher efficiency of the solar panels, the conventional airship has lower drag, which results in superior mission performance.

Particulate deposits in aero-engine turbines change the profile of blades, increase the blade surface roughness and block internal cooling channels and film cooling holes, which generally leads to the degradation of aerodynamic and cooling performance. To reveal particle deposition effects in the turbine, unsteady simulations were performed by investigating the migration patterns and deposition characteristics of the particle contaminant in a one-stage, high-pressure turbine of an aero-engine. Two typical operating conditions of the aero-engine, i.e. high-temperature take-off and economic cruise, were discussed, and the effects of particle size on the migration and deposition of fly-ash particles were demonstrated. A critical velocity model was applied to predict particle deposition. Comparisons between the stator and rotor were made by presenting the concentration and trajectory of the particles and the resulting deposition patterns on the aerofoil surfaces. Results show that the migration and deposition of the particles in the stator passage is dominated by the flow characteristics of fluid and the property of particles. In the subsequential rotor passage, in addition to these factors, particles are also affected by the stator–rotor interaction and the interference between rotors. With higher inlet temperature and larger diameter of the particle, the quantity of deposits increases and the deposition is distributed mainly on the Pressure Side (PS) and the Leading Edge (LE) of the aerofoil.

Aileron to Rudder Interconnect (ARI) gain is implemented on most fighter aircraft, primarily to reduce the side slip produced due to adverse yaw from pilot lateral control stick input and to improve the turn rate response. A systematic and non-iterative design procedure for ARI gain is proposed herein based on the evaluation of a transfer function magnitude at the aircraft roll mode frequency. The simplicity of the proposed method makes it useful for real-time flight control law reconfiguration in situations where the aileron control authority is diminished due to damage. This is demonstrated by a simulation example considering an aileron surface damage scenario.

Research on flight emissions at airports is very important for environmental policymaking. This study analysed the trend of aircraft air pollutant emissions at mainland China airports from 1990 to 2017, mainly focusing on standard landing and take-off (LTO) cycles. Total flight movements increased 29-fold from 1990 to 2017 at Chinese airports. Over the same period, the emissions of NOx, SOx, CO, hydrocarbons (HC), and particulate matter (PM) increased 46, 27, 12, 5, and 4 times, respectively. Emissions at the 216 public airports showed a growth trend. It was estimated that in 2017, Chinese airports emitted 12,875 kilotons of CO2, 59 kilotons of NOx, 3 kilotons of SOx, 38 kilotons of CO, 5 kilotons of HC, and 0.4 kilotons of PM. The largest 30 airports produced 68.2% of the total emissions. Emissions from B737-800, A320, A321, B737-700, A330-300, and A319 aircraft accounted for more than 75% of aircraft LTO emissions at Chinese airports in 2017. Results show that average emissions per passenger have decreased for CO2, CO, HC, SOx, PM, and NOx from 1990 to 2017.

Air traffic controller training is highly regulated but lacks prescribed common assessment criteria and methods to evaluate trainees at the level of basic training and consideration of how trainees in fluence flight efficiency. We investigated whether there is a correlation between two parameters, viz. the trainees’ assessment score and fuel consumption, obtained and calculated after real-time human-in-the-loop radar simulations within the ATCOSIMA project. Although basic training assessment standards emphasise safety indicators, it was expected that trainees with higher assessment scores would achieve better flight efficiency, i.e. less fuel consumption. However, the results showed that trainees’ assessment scores and fuel consumption did not correlate in the expected way, leading to several conclusions.

Carrier-based unmanned aerial aircraft (UAV) structure is subjected to severe tensile load during takeoff, especially the drawbar, which affects its fatigue performance and structural safety. However, the complex structural features pose great challenges for the engineering design. Considering this situation, a structural design, fatigue analysis, and parameters optimisation joint working platform are urgently needed to solve this problem. In this study, numerical analysis of strain fatigue is carried out based on the laboratory fatigue failure of the carrier-based aircraft drawbar. Taking the sensitivity of drawbar parameters to stress and life into account and optimum design of drawbar with fatigue life as a target using the parametric method, this study also includes cutting-edge parameters of milling cutters, structural details of the drawbar and so on. Then an experimental design is applied using the Latin hypercube sampling method, and a surrogate model based on RBF neural network is established. Lastly, a multi-island genetic algorithm is introduced for optimisation. The results show that the error between the obtained optimal solution and simulation is 0.26%, while the optimised stress level is reduced by 15.7%, and the life of the drawbar is increased by 122%.