An intelligent decision-making method was proposed for airport bird-repelling based on a Support Vector Machine (SVM) and bird-strike risk assessment. The bird-strike risk assessment model is established with two exponential functions to separate the risk levels, while the SVM method includes two steps of training and testing. After the risk assessment, the Bird-Repelling Strategy Classification Model (BRSCM) was trained based on the expert knowledge and large amount of historical bird information collected by the airport linkage system for bird detection, surveillance and repelling. Then, in the testing step, the BRSCM was continuously optimised according to the real-time intelligent bird-repelling strategy results. Through several bird-repelling examples of a certain airport, it is demonstrated that the decision accuracy of BRSCM is relatively high, and it could solve new problems by self-correction. The proposed method achieved the optimised operation of multiple bird-repelling devices against real-time bird information with great improvement of bird-repelling effects, overcoming the tolerance of birds to the bird-repelling devices due to their long-term repeated operation.

Wind-tunnel tests were carried out to evaluate the performance of the Computational Fluid Dynamics (CFD)-based air-intake duct shape optimisation of the European platform tiltrotor ERICA. A 1/2.5 scale model including the nacelle, the external portion of the wing and two interchangeable internal ducts reproducing the baseline and optimised shape were manufactered to be tested in the large wind tunnel of Politecnico di Milano. Moreover, tests were carried out with the model equipped with rotating blade stubs. The comprehensive experimental campaign included tests reproducing different forward flight conditions of the aircraft including cruise and conversion phases. The evaluation of the internal duct performance was carried out by measuring total pressure losses and flow distortion by directional probes at the Aerodynamic Interface Plane (AIP). Additional pressure measurements were carried out on the internal surface of the duct to compare the pressure distributions along the air-intake. The experimental results confirmed that the optimised duct offers significantly improved performance with respect to the baseline configuration not only in cruise, representing the flight condition considered for the CFD optimisation, but also for the conversion condition. In particular, a remarkable reduction of the total pressure drop at the AIP was found with the optimised duct with the only exception for the stubs-on configuration in cruise. Indeed, the present investigation highlighted that the design of the blade stubs, particularly their length, represents a very critical aspect for air-intake performance tests due to significant disturbances that could be induced by the stubs’ wake on the internal duct flow.

The rotorcraft industry needs Virtual Engineering first to ensure decisions made early in the life-cycle, at the requirements capture and preliminary design phases for example, are reliably informed. Later, in design, development and qualification, Virtual Prototypes can become the centre of attention for critical reviews and, ultimately, certification itself. A significant challenge is to ensure that model fidelity is good enough, not only for supporting design decisions but also in establishing requirements based on sufficiently mature technologies. This international conference, Rotorcraft virtual engineering; supporting life-cycle engineering through design and development, test and certification and operations and co-sponsored by the RAeS/AHS/A3F/DGLR/AIDAA addressed these themes and this paper reviews and assesses the value of the various contributions.

The flatness of a six-degree-of-freedom (6DoF) aircraft model with conventional control surfaces – aileron, flap, rudder and elevator, along with thrust vectoring ability is established in this work. Trajectory optimisation of an aircraft can be cast as an inverse problem where the solution for control inputs that yield desired trajectories for certain states is sought. The solution to the inverse problems for certain systems is made tractable when they exhibit differential flatness. Flatness-based trajectory optimisation has a significant advantage over an equivalent collocation-based method in terms of computational efficiency and viability for real-time implementation. An application for the flatness of 6DoF aircraft is shown in the trajectory optimisation for dynamic soaring, and its connection with an equivalent 3DoF flatness-based implementation is also brought out. The results are compared with that from a collocation-based approach.

Aiming at three-dimensional (3D) terminal guidance problem, a novel guidance model is established in this paper, in which line-of-sight (LOS) range is treated as an independent variable, describing the relative motion between the vehicle and the target. The guidance model includes two differential equations that describe LOS’s pitch and yaw motions in which the pitch motion is separately decoupled. This model avoids the inaccuracy of simplified two-dimensional (2D) guidance model and the complexity of 3D coupled guidance model, which not only maintains the accuracy but also simplifies the guidance law design. The application of this guidance model is studied for optimal re-entry guidance law with impact angle constraint, which is presented in the form of normal overload. Compared with optimal guidance laws based on traditional guidance model, the proposed one based on novel guidance model is implemented with the LOS range instead of time-to-go, which avoids the problem of the time-to-go estimation of traditional optimal guidance laws. Finally, the correctness and validity of the guidance model and guidance law are verified by numerical simulation. The guidance model and guidance law proposed in this paper provide a new way for the design of terminal guidance.

The laminar flow over a slender delta wing at incidence has been extensively studied both experimentally and theoretically using vortex sheet methods. These vortex sheet methods have generally been successful apart from the prediction of the secondary boundary-layer separation induced by the primary vortex. This paper revisits the problem using computational fluid dynamics (CFD) and focusses on the effects of the secondary flow separation. The modelling approach is briefly summarised, and the results are compared with flow measurements and results from vortex sheet methods. The computations show very good agreement with measurements for the surface pressures and total head contours. The results help to understand the complex structure of the leading edge vortex flow, and the associated secondary separation of the boundary layer. They indicate that inviscid mechanisms dominate the larger scale features, and highlight a possible mechanism for the development of an instability in the leading edge vortex sheet.

High-precision response of the surrogate model is desired in the process of optimisation. An excessive number of sampling points will increase the cost of the calculation. The appropriate number of sampling points cannot only guarantee the accuracy of the surrogate model but also save the calculation cost. The purpose of this research is to demonstrate the eventuality of using an adaptive surrogate model for optimisation problems. The adaptive surrogate model is built on an adaptive sampling approach and an extended radial basis function (ERBF). The adaptive sampling is an approach that new sampling points are placed in the blank area and all the sampling points are uniformly distributed in the design region using Multi-Island GA. The precision of the ERBF surrogate model is checked using standard error measure to determine whether the surrogate model should be updated or not. This adaptive surrogate model is used to optimise a cruise missile head shape. Aerodynamic and stealthy performance of the cruise missile head shape are considered in this research. Different global objective function and different weight factor are used to research the aerodynamic and stealthy performance in this optimisation process. The results show that the drag is reduced with a slender head shape and the radar-cross section (RCS) value is reduced with a short head shape.

The aim of this work is to investigate and quantify the latency on a Stewart Platform caused exclusively by a Classic washout filter. This washout filter is intended to recreate the sensations of motion caused by changes of translational and rotational acceleration that an aircraft can provide, due to changes in attitudes caused by external factors, and those caused by the pilot’s command. The input signal was generated by a FlightGear Simulator in order to obtain the specific forces and angular velocities of a Boeing 747 during a take-off procedure. These signals are then filtered by a washout filter and sent to the inverse kinematics of the movable platform, which will transform the aircraft motion sensations in platforms actuator position, thereby causing a certain signal delay. Experiments were performed in a Stewart Platform to obtain the latency caused by the mathematical modelling of the entire washout filter system. This latency are then compared to the latency caused by the control and dynamics of the platform’s actuators. Results indicate that the washout filter is the most responsible for the latency of the specific force signals to be reproduced by the platform in this experiment, and that the natural frequency and damping coefficient values must be properly estimated in order to optimise the total latency.

The Federal Aviation Administration often blocks strategically located airspace volumes to ensure safety during a variety of operations that are potentially hazardous to aircraft, such as space launches. As the frequency of these operations increases, there is a growing need to deepen collaboration and transparency between stakeholders regarding the use of airspace. This collaboration can be supported by models and capabilities to quickly assess the impact of airspace closures, up to 12 months into the future. This paper presents a technique to enable a ‘what-if’ analysis capability coupled with a prediction model, whereby changes in airspace dimension, location, and activation time are reflected instantaneously as measures of projected impact. The technique can also be used for quick post-operations analysis using historical traffic data and to develop air traffic impact assessment capabilities accessible to a broad range of users outside of the air traffic domain. This research has three key components: developing a model to predict air traffic demand up to 12 months into the future, modelling air traffic impact to the affected traffic, and reducing this information into a data structure that can support on-demand analysis. The focus of this paper is on new techniques to predict demand using a large set of historical track data and further encode these projections to support the quick assessment of the impact of blocking various airspace volumes. Initial results show that the proposed data reduction scheme accurately represented the traffic crossing an airspace and resulted in data size reduction by over 50%. The projection model performed well, the actual number of impacted flights were within the estimated range of approximately 80% of the time. Finally, the responsiveness of the web-based prototype developed to illustrate the concept demonstrated the model’s ability to support an on-demand assessment of the air traffic impact of blocking airspace. A significant limitation of the projection model is that it is based on the historical traffic pattern within the U.S. airspace; separate analysis is needed to adapt it to other geographical location.