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Improving the verification and certification process of the high lift system by introduction of virtual testing is one of the approaches to counter the challenges related to testing of future aircraft, in terms of performing more tests of more complex systems in less time. The quality of the applied modelling methods itself and the guarantee of a completely traceable simulation lifecycle management along the aircraft development are essential. The presentation shows how existing processes for the management of all test related data have to be extended to cover the specifics of using multi body simulation models for virtual tests related to high lift failure cases. Based on a demonstrator, MSC Software GmbH and Airbus developed and are still refining the SimManager based “High Lift System Virtual Test Portal”. This portal has to fulfil on the one side global requirements like data management, data traceability and workflow management.

This study aims to provide an understanding of self-similarity in the turbulent wake generated by a Fastback DrivAer automotive model and assess the impact of upstream disturbances on the wake. The disturbances are generated using a circular cylinder placed five cylinder diameters upstream. Multiple ‘cylinder-model’ positions were tested by offsetting the lateral positioning of the cylinder with respect to the centreline of the model. Data was obtained at cross-planes in the wake going from 25% to 100% car length. Wind tunnel data has been obtained using a total pressure probe rake and a four-hole cobra probe. Data has also been obtained using RANS based simulations with k – ε realisable turbulence model. Mean axial-component velocity profiles were analysed with momentum thickness (θ) and vorticity thickness (δω) used as the scaling parameters. It was seen that self-similarity marginally exists in the wake depending on the upstream conditions and the scaling parameter.

This SAE EDGE™ Research Report builds a comprehensive picture of the current state-of-the-art of human-robot applications, identifying key issues to unlock the technology’s potential. It brings together views of recognized thought leaders to understand and deconstruct the myths and realities of human- robot collaboration, and how it could eventually have the impact envisaged by many. Current thinking suggests that the emerging technology of human-robot collaboration provides an ideal solution, combining the flexibility and skill of human operators with the precision, repeatability, and reliability of robots. Yet, the topic tends to generate intense reactions ranging from a “brave new future” for aircraft manufacturing and assembly, to workers living in fear of a robot invasion and lost jobs. It is widely acknowledged that the application of robotics and automation in aerospace manufacturing is significantly lower than might be expected.

Transient force and surface pressure data has been measured on a range of simple geometric shapes in order to gain an understanding of the complex time dependent and separated flow around a vehicle when subjected to a crosswind. The experiments were carried out using the Cranfield University model crosswind facility. It is found that the leeward face is the dominant area of transient activity. Maximum and minimum peak yawing moments at gust entry and exit are compared

With the rapid growth in passenger transportation through aviation projected to continue into the future, it is incumbent on aerospace engineers to seek ways to reduce the negative impact of airliner operation on the environment. Key metrics to address include noise, fuel consumption, Carbon Dioxide and Nitrous Oxide emissions, and contrail formation. The research presented in this paper generates new aircraft trajectories to reduce these metrics, and compares them with typical scheduled airline operated flights. Results and analysis of test cases on trajectory optimization are presented using an in-house aircraft trajectory optimization framework created under the European Clean Sky Joint Technology Initiative, Systems for Green Operation Integrated Technology Demonstrator. The software tool comprises an optimizer core and relatively high fidelity models of the aircraft's flight path performance, air traffic control constraints, propulsion and other systems.

Glaciated icing conditions potentially leading to in-service event are often encountered in the vicinity of deep convective clouds. Nowcasting of these conditions with space-borne observations would be of a great help for improving flight safety and air-traffic management but still remains challenging. In the framework of the HAIC (High Altitude Ice Crystals) project, methods to detect and track regions of high ice water content from space-based geostationary and low orbit mission are investigated. A first HAIC/HIWC field campaign has been carried out in Australia in January-March 2014 to sample meteorological conditions potentially leading to glaciated icing conditions. During the campaign, several nowcasting tools were successfully operated such as the Rapid Development Thunderstorm (RDT) product that detects the convective areas from infrared geostationary imagery.

In the current literature, the research studies on the trajectory tracking control and stability control strategy for autonomous vehicles in limited condition mostly focus on the yaw plane control, but few of the studies have considered the combined control performance of trajectory tracking, yaw and roll stability, and the roll stability is critical under the extreme cornering condition for autonomous vehicles. Aiming at the above shortages, this study designs the model predictive control (MPC) strategy for the autonomous vehicles under the limited handling condition, which integrates the front and rear wheel active steering control, four-wheel independent drive and braking control and active suspension control to comprehensively improve the trajectory tracking accuracy, yaw plane stability and roll plane stability of the vehicle under the extreme condition.

A 3D Navier-Stokes CFD model of a wheel located within a wheelhouse cavity has been produced. Both a stationary wheel on a fixed ground and a rotating wheel on a moving ground were considered. Extensive comparisons with the results of a wind tunnel investigation based on the same geometry are presented. These consist of three force coefficients and pressures on the internal faces of the cavity. Comparison with the experimental results gave encouraging agreement. It was found that the rotating wheel produced more drag than the stationary wheel whilst shroud drag decreased when the groundplane was moving compared to when it was stationary.

Electroimpact has developed a new Fastener Feed System which provides an automated solution for fasteners previously hand fed via drop tubes. The hardware is simple, compact, and is supplied a fraction of the cost of hoppers or cartridges. It can be used as a primary feed system or it can be used as an auxiliary feed system when combined with feed systems designed for high quantities of fasteners. We have installed this system on the A380 Stage 0 LVER lower panel wing machines and feed 5 diameters, 10 grips each, for a total of 50 different fastener types. This system moves 547 total fasteners per ship set from manual feed to automatic feed, saving considerable build time.

The presented paper describes the software complex developed in St. Petersburg Polytechnical University for AIRBUS aimed at simulation of aircraft assembly process. Previous version of this complex was described in [1].

Measurements in snow conditions performed in the past were rarely initiated and best suited for pure and extremely detailed quantification of microphysical properties of a series of microphysical parameters, needed for accretion modelling. Within the European ICE GENESIS project, a considerable effort of natural snow measurements has been made during winter 2020/21. Instrumental means, both in-situ and remote sensing were deployed on the ATR-42 aircraft, as well as on the ground (ground station at ‘Les Eplatures’ airport in the Swiss Jura Mountains with ATR-42 overflights). Snow clouds and precipitation in the atmospheric column were sampled with the aircraft, whereas ground based and airborne radar systems allowed extending the observations of snow properties beyond the flight level chosen for the in situ measurements.

A methodology to evaluate the sensitivity of total pressure intake distortion descriptors defined by SAE ARP 1420 to individual pressure fluctuations in the Aerodynamic Interface Plane -AIP- has been developed. Individual pressure fluctuations were simulated as a white noise using a random number generator with a Gaussian distribution of known standard deviation. Monte Carlo experiments were performed perturbing different steady total pressure patterns on the AIP with random signals of different RMS values. Instantaneous distortion descriptors were calculated and statistically characterized. General correlations were obtained applying maximum value statistics to relate the maximum expected distortion increment to the RMS of the individual pressure fluctuations, the mean total pressure on the AIP and the number of samples.

The work describes a concept application that aids a safety engineer to create a layup of equipment models by using an image scan of a schematic and a library of predefined standard component and their symbols. The approach uses image recognition techniques to identify the symbols within the scanned image of the schematic from a given library of symbols. Two recognition approaches are studied, one uses General Hough Transform; the other is based on pixel-level feature computation combining both structure and statistical features. The application allows the user to accept or edit the results of the recognition step and allows the user to define new components during the layup step. The tool then generates an output file that is compatible with a formal safety modeling tool. The identified symbols are associated to behavioral nodes from a model based safety tool.

Hybrid electric vehicles (HEV) are considered as the most cost effective solution, in the short term perspective, for the achievement of improved fuel economy (FE) and reduced emissions. This paper focuses on regenerative braking in a mild hybrid powertrain with infinitely variable transmission (IVT) and specifically on how its control strategy can be formulated and optimized. The study is conducted using a previously validated fully dynamic powertrain model. An initial investigation of the dynamic vehicle behaviour under braking conditions serves as the basis for the development of a control strategy for best braking performance and maximum energy recovery, the implementation of which requires a fully active and integrated brake control system. Limitations and constraints due to driveline configuration and driveability issues are considered and their effect evaluated. Simulation results show that fuel consumption reductions of 12% are achievable along a standard drive cycle.

As the essential of future driver assistance system, brake-by-wire system is capable of performing autonomous intervention to enhance vehicle safety significantly. Regenerative braking is the most effective technology of improving energy consumption of electrified vehicle. A novel brake-by-wire system scheme with integrated functions of active braking and regenerative braking, is proposed in this paper. Four pressure-difference-limit valves are added to conventional four-channel brake structure to fulfill more precise pressure modulation. Four independent isolating valves are adopted to cut off connections between brake pedal and wheel cylinders. Two stroke simulators are equipped to imitate conventional brake pedal feel. The operation principles of newly developed system are analyzed minutely according to different working modes. High fidelity models of subsystems are built in commercial software MATLAB and AMESim respectively.

Rising energy costs and increased regulation in recent years have caused industrialists to investigate how to apply ‘energy efficiency’ to their manufacturing operations. As well as reducing operating costs, the benefits of a ‘green’ image as a market differentiator are beginning to be realised. The literature describes the successful implementation of a variety of approaches to energy reduction, with particular focus on energy intensive industries (such as foundries) and on improvements to building services (such as lighting). However, a systematic approach to applying sustainable practices to the manufacturing processes involved in the production of high value products, such as aircraft, is noticeably absent. This paper describes how a number of sustainable manufacturing approaches have been combined, enhanced and applied to the shop floor of a manufacturing facility in the UK responsible for the production of large component assemblies for the aerospace industry.

Recently, the development of braking assistance system has largely benefit the safety of both driver and pedestrians. A robust prediction and detection of driver braking intention will enable driving assistance system response to traffic situation correctly and improve the driving experience of intelligent vehicles. In this paper, two types unsupervised clustering methods are used to build a driver braking intention predictor. Unsupervised machine learning algorithms has been widely used in clustering and pattern mining in previous researches. The proposed unsupervised learning algorithms can accurately recognize the braking maneuver based on vehicle data captured with CAN bus. The braking maneuver along with other driving maneuvers such as normal driving will be clustered and the results from different algorithms which are K-means and Gaussian mixture model (GMM) will be compared.

The objective of this paper is to present a numerical method to rank thick ice shapes for aircraft by comparing the ice accretion effects for different icing scenarios in order to determine the more critical ice shape. This ranking allows limiting the demonstration of the aerodynamic characteristics of the aircraft in iced condition during certification to a reduced number of ice shapes. The usage of this numerical method gives more flexibility to the determination of the critical ice shapes, as it is not dependent of the availability of physical test vehicles and/or facilities. The simulation strategy is built on the Lattice Boltzmann Method (LBM) and is validated based on a representative test case, both in terms of aircraft geometry and ice shapes. Validation against existing experimental results shows the method exhibits an adequate level of reliability for the ranking of thick ice shapes.

AmSafe®, Airbus and IABG were the first in decades to undertake an ultimate forward load Full-Scale Test (FST) of a 9 g₁ Barrier Net. Barrier Nets are safety-critical products used during an emergency landing (FAR25.561/CS25.561) to protect passengers and crew. When Airbus Military required an A400M Barrier Net they identified requirements well beyond the "normal" and demanded that payloads from a rigid structure to a frangible be restrained. AmSafe uses non-liner Finite Element Analysis (FEA) technology to analyze their nets and proposed an innovative solution for a new Barrier Net to satisfy these very demanding requirements. Given these new requirements, it was decided to also carry out a Full-Scale Test (FST). This test required the expertise of IABG, a testing facility based in Germany.

The motion of a vehicle along a desired path is possible due to steering action of the driver. Hence, vehicle dynamics and control simulations should take into consideration the action of the driver. This work presents a preview based vehicle steering controller using Neural Networks which can be used in the vehicle lateral dynamics simulations. The training data for the Neural Network is being obtained using a steering controller from the existing literature and its gains are determined using Optimization. Three different architectures are being designed and conclusions are presented. These Neural Network models are validated by testing against real track data.