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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 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.

In response to the ice crystal icing hazard identified twenty years ago, aviation industry, regulation authorities, and research centers joined forces into the HAIC-HIWC international collaboration launched in 2012. Two flight campaigns were conducted in the high ice water content areas of tropical mesoscale convective systems in order to characterize this environment conducive to ice crystal icing. Statistics on cloud microphysical properties, such as Ice Water Content (IWC) or Mass Median Diameter (MMD), derived from the dataset of in situ measurements are now being used to support icing certification rulemaking and anti-icing systems design (engine and air data probe) activities. This technical paper focuses on methodological aspects of the derivation of MMD. MMD are estimated from PSD and IWC using a multistep process in which the mass retrieval method is a critical step.

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.

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.

Industrial requirements imply optimizing the development cycle, reducing manufacturing costs and reaching marketable product maturity as fast as possible. The design stage often involves multiple sites and various partners. In this context, the use of computer simulation becomes absolutely necessary to meet industrial needs. Nevertheless, this activity can be effective only if it is integrated correctly in the industrial organization. In the aeronautical and space systems industry, mechanical specifications often require the use of composites reinforced by continuous carbon fibers. The goal of this article is to describe how, on a time frame of nearly twenty years, a series of scientific and technical tasks were carried out in partnership in order to develop, validate and implement Resin Transfer Molding (RTM) flow simulation and cure analysis for high performance composites. The research stage started at the university in 1991.

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.

Testing real-time vehicular systems challenges the tester to design test cases for concurrent and sequential input events, emulating unexpected user and usage profiles. The vehicle response should be robust to unexpected user actions. Sequence Covering Arrays (SCA) offer an approach which can emulate such unexpected user actions by generating an optimized set of test vectors which cover all possible t-way sequences of events. The objective of this research was to find an efficient nonfunctional sequence testing (NFST) strategy for testing the robustness of real-time automotive embedded systems measured by their ability to recover (prove-out test) after applying sequences of user and usage patterns generated by combinatorial test algorithms, considered as “noisy” inputs. The method was validated with a case study of an automotive embedded system tested at Hardware-In-the-Loop (HIL) level. The random sequences were able to alter the system functionality observed at the prove-out test.

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.

This paper gives an overview of the development of a number of loss models for the pushing metal V-belt CVT. These were validated using a range of experimental data collected from two test rigs. There are several contributions to the torque losses and new models have been developed that are based upon relative motion between belt components and pulley deflections. Belt slip models will be proposed based upon published theory, expanded to take account of new findings from this work. The paper introduces a number of proposals to improve the efficiency of the transmission based on redesign of the belt geometry and other techniques to reduce frictional losses between components. These proposed efficiency improvements have been modelled and substituted into a complete vehicle simulation to show improvements in vehicle fuel economy over a standard European drive cycle.

In Aeronautic industry, when we launch a new industrialization for an aircraft sub assembly we always have the same questions in mind for drilling operations, especially when focusing on lean manufacturing. How can we avoid dismantling and deburring parts after drilling operation? Can a drilling centre perform all the tasks needed to deliver a hole ready to install final fastener? How can we decrease down-time of the drilling centre? Can a drilling centre be integrated in a pulse assembly line? How can we improve environmental efficiency of a drilling centre? It is based on these main drivers that AIRBUS has developed, with SPIE and SOS, a new generation of drilling centre dedicated for hard materials such as titanium, and high thicknesses. The first application was for the assembly of the primary structure of A350 engine pylons. The main solution that was implemented meeting several objectives was the development of orbital drilling technology in hard metal stacks.

In Aeronautic industry, when we launch a new industrialization for an aircraft sub assembly we always have the same questions in mind for drilling operations, especially when focusing on lean manufacturing. How can we avoid dismantling and deburring parts after drilling operation? Can a drilling centre perform all the tasks needed to deliver a hole ready to install final fastener? How can we simplify specific jigs used to maintain parts during drilling operations? How can we decrease down-time of the drilling centre? Can a drilling centre be integrated in a pulse assembly line? How can we improve environmental efficiency of a drilling centre? It is based on these main drivers that AIRBUS has developed, with SPIE and SOS, a new generation of drilling centre dedicated for hard materials such as titanium, and high thicknesses. The first application was for the assembly of the primary structure of A350 engine pylons.

The Environmental Control System is a relevant element of any conventional or More Electric Aircraft (MEA). It is either the key consumer of pneumatic power or draws a substantial load from the electric power system. The objective of this paper is to present a tool for the design of Environmental Control Systems and to apply it to an unconventional system. The approach is based on a recently proposed methodology, which is improved with respect to flexibility and ease-of-use. Furthermore, modeling and simulation of vapor compression cycles is discussed, which are candidate technological solutions for More Electric Aircraft concepts. A steady-state moving boundary method is presented to model heat exchangers for such applications. Finally, the resulting design environment is applied to optimization of an unconventional ECS architecture and exemplary results are presented.

The main study illustrated in this paper deals with the computation of commands which allow an aircraft to recover a nominal energy trajectory from a low/high energy state during the approach phase. The commands taken into account in this paper are the slat/flap aerodynamic control surfaces which allow the aircraft to maintain the best lift performance for low velocities during the approach phase. In this study, it is supposed that the aircraft maintains a known vertical trajectory, simplified by a constant ground slope, while no engines and airbrakes are used. A non-linear optimization approach is studied in this paper and two methods are tested: a) Hermite-Simpson, trapezoidal collocation methods, b) Sequential numerical integration method. These different methods are tested and simulation results are given for comparison, with different initial velocities permitting to change the initial energy state.