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The simulation of natural-like snow conditions in a controlled environment such as an Icing Wind Tunnel (IWT) is a key component for safe, efficient and cost-effective design and certification of future aircraft and rotorcraft. Current capabilities do not sufficiently match the properties of natural snow, especially in terms of size and morphology. Within the Horizon 2020 project ICE GENESIS, a new technology has been developed aiming to better recreate natural snowflakes. The focus of the newly developed system was the generation of falling snow in a temperature range of +1°C to -4°C. Ground measurements and flight test campaigns have been performed to better characterize these conditions and provide requirements for wind tunnel facilities. The calibration results of the new snow generation system as well as snow accretion data on a NACA0012 test article with a chord length of 0.377 m are presented.

Dents on the aircraft skin are frequent and may easily go undetected during airworthiness checks, as their inspection process is tedious and extremely subject to human factors and environmental conditions. Nowadays, 3D scanning technologies are being proposed for more reliable, human-independent measurements, yet the process of inspection and reporting remains laborious and time consuming because data acquisition and validation are still carried out by the engineer. For full automation of dent inspection, the acquired point cloud data must be analysed via a reliable segmentation algorithm, releasing humans from the search and evaluation of damage. This paper reports on two developments towards automated dent inspection. The first is a method to generate a synthetic dataset of dented surfaces to train a fully convolutional neural network. The training of machine learning algorithms needs a substantial volume of dent data, which is not readily available.

This paper presents the design concept behind a novel remote visual inspection robotic system for fighter jet aircraft wing fuel tank inspection. This work is part of a larger research project which focuses on design, simulation, physical prototyping and experimental validation of a robotic system. Whereas this paper specifically focuses on the development concept of locomotion design choice for the robot. Therefore without an effective mobility method the robot will not be able to fulfill its purpose to access the hazardous confined spaces of the fuel tank. Aircraft wing fuel tank inspection is a challenging area of maintenance which requires a considerable amount of preparation and involvement of several tasks in order to conduct effective Visual and Non Destructive Inspection. The environment of an aircraft wing fuel tank poses several challenges due to both physical and atmospheric constraints which can be detrimental to human personal.

Every state-of-art aircraft has a complex distributed systems of avionics Line Replaceable Units/Modules (LRUs/LRMs), networked by several Data buses. These LRUs are becoming more complex because of an increasing number of new functions need to be integrated into avionics architecture. Moreover, the complexity of the overall avionics architecture and its impact on cable length, weight, power consumption, reliability and maintainability of avionics systems encouraged manufacturers to incorporate efficient avionics architectures in their aircraft design process. The evolution of avionics data buses and architectures have moved from distributed analog and federated architecture to digital integrated modular avionics (IMA). IMA architecture allows suppliers to develop their own LRUs/LRMs capable of specific features that can then be offered to Original Equipment Manufacturers (OEMs) as Commercial-Off-The-Shelf (COTS) products.

Bus drivers are a group at risk of often suffering from musculoskeletal problems, such as low-back pain, while bus passengers on the last-row seats experience accelerations of high values. In this paper, the contribution of K-seat in decreasing the above concern is investigated with a detailed simulation study. The K-seat model, a seat with a suspension that functions according to the KDamper concept, which combines a negative stiffness element with a passive one, is benchmarked against the conventional passive seat (PS) in terms of comfort when applied to different bus users’ seats. More specifically, it is tested in the driver’s and two different passengers’ seats, one from the rear overhang and one from the middle part. For the benchmark shake, both are optimized by applying excitations that correspond to real intercity bus floor responses when it drives over a real road profile.

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.

Digital Twin (DT) is a dynamic digital representation of a real-world asset, process or system. Industry 4.0 has recognised DT as the game changer for manufacturing industries in their digital transformation journey. DT will play a significant role in improving consistency, seamless process development and the possibility of reuse in subsequent stages across the complete lifecycle of the product. As the concept of DT is novel, there are several challenges that exist related to its phase of development and implementation, especially in high value manufacturing sector. The paper presents a thematic analysis of current academic literature and industrial knowledge. Based on this, eleven key challenges of DT were identified and further discussed. This work is intended to provide an understanding of the current state of knowledge around DT and formulate the future research directions.

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 flow field and body aerodynamic loads on the DrivAer reference model have been extensively investigated since its introduction in 2012. However, there is a relative lack of information relating to the models wake development resulting from the different rear-body configurations, particularly in the far-field. Given current interest in the aerodynamic interaction between two or more vehicles, the results from a preliminary CFD study are presented to address the development of the wake from the Fastback, Notchback, and Estateback DrivAer configurations. The primary focus is on the differences in the far-field wake and simulations are assessed in the range up to three vehicle lengths downstream, at Reynolds and Mach numbers of 5.2×106 and 0.13, respectively. Wake development is modelled using the results from a Reynolds-Averaged Navier-Stokes (RANS) simulation within a computational mesh having nominally 1.0×107 cells.

Cooling drag, typically known as the difference in drag coefficient between open and closed cooling configurations, has traditionally proven to be a difficult flow phenomenon to predict using computational fluid dynamics. It was seen as an academic yardstick before the advent of grille shutter systems. However, their introduction has increased the need to accurately predict the drag of a vehicle in a variety of different cooling configurations during vehicle development. This currently represents one of the greatest predictive challenges to the automotive industry due to being the net effect of many flow field changes around the vehicle. A comprehensive study is presented in the paper to discuss the notion of defining cooling drag as a number and to explore its effect on three automotive models with different cooling drag deltas using the commercial CFD solvers; STARCCM+ and Exa PowerFLOW.

In the civil aircraft industry there is a continuous drive to increase the aircraft production rate, particularly for single aisle aircraft where there is a large backlog of orders. One of the bottlenecks is the wing assembly process which is largely manual due to the complexity of the task and the limited accessibility. The presented work describes a general wing build approach for both structure and systems equipping operations. A modified build philosophy is then proposed, concerned with large component pre-equipping, such as skins, spars or ribs. The approach benefits from an offloading of the systems equipping phase and allowing for higher flexibility to organize the pre-equipping stations as separate entities from the overall production line. Its application is presented in the context of an industrial project focused on selecting feasible system candidates for a fixed wing design, based on assembly consideration risks for tooling, interference and access.

Simulations are presented which fully couple both the aerodynamics and cooling flow for a model of a fully engineered production saloon car (Jaguar XJ) with a two-tier cooling pack. This allows for the investigation of the overall aerodynamic impact of the under-hood cooling flow, which is difficult to predict experimentally. The simulations use a 100 million-element mesh, surface wrapped and solved to convergence using a commercially available RANS solver (STARCCM+). The methodology employs representative boundary conditions, such as rotating wheels and a moving ground plane. A review is provided of the effect of cooling flows on the vehicle aerodynamics, compared to published data, which suggest cooling flow accounts for 26 drag counts (0.026 Cd). Further, a sensitivity analysis of the pressure drop curves used in the porous media model of the heat exchangers is made, allowing for an initial understanding of the effect on the overall aerodynamics.

In jet atomization, breakup length is the length of the continuous jet segment, before its breakup to discontinuous droplets. Hydrodynamic instability theory, implemented in CFD codes, is often complemented by semi-empirical correlations for breakup length, which may limit parametric investigations. A basic mechanistic approach to the breakup length prediction, based on a simple momentum balance between the injected jet and the aerodynamic drag force due to the surrounding gas, which complements the classic hydrodynamic instability breakup mechanism, is suggested. This model offers a simple complementing mechanistic model. It is shown that obtained results compare well with published experiments, and with the established empirical correlation of Wu and Faeth (1995). A simplified version of the model, taking into account an inviscid hydrodynamic model is shown to maintain plausibility of breakup length predictions in fuel-injection relevant conditions.

This paper focuses on the investigation of the nature, process and effects of ice accretion on different feed pump strainers upstream of the aircraft feeding system. A suitable test rig was designed to circulate Jet A-1 containing water/ice contaminants at cold temperatures through the strainers. Following an extensive literature review, a number of screening tests were performed. These provided a strong base for an exhaustive study of fuel icing in the dynamic environment offered by the test rig. The effects of the rate of fuel cooling on the nature of ice were examined. As expected, it was observed that the yield of ice generated on the mesh screen increased with the water concentration in the fuel. It was also revealed that at higher cooling rates, a crust of snow formed on top of softer ice on the mesh screen.

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 aim of this paper is to develop a new concept of unconventional airship based on morphing a lenticular shape while preserving the volumetric dimension. Lenticular shape is known to have relatively poor aerodynamic characteristics. It is also well known to have poor static and dynamic stability after the certain critical speed. The new shape presented in this paper is obtained by extending one and reducing the other direction of the original lenticular shape. The volume is kept constant through the morphing process. To improve the airship performance, four steps of morphing, starting from the lenticular shape, were obtained and compared in terms of aerodynamic characteristics, including drag, lift and pitching moment, and stability characteristics for two different operational scenarios. The comparison of the stability was carried out based on necessary deflection angle of the part of tail surface.

The installation of essential systems into aircraft wings involves numerous labour-intensive processes. Many human operators are required to perform complex manual tasks over long periods of time in very challenging physical positions due to the limited access and confined space. This level of human activity in poor ergonomic conditions directly impacts on speed and quality of production but also, in the longer term, can cause costly human resource problems from operators' cumulative development of musculoskeletal injuries. These problems are exacerbated in areas of the wing which house multiple systems components because the volume of manual work and number of operators is higher but the available space is reduced. To improve the efficiency of manual work processes which cannot yet be automated we therefore need to consider how we might redesign systems installations in the enclosed wing environment to better enable operator access and reduce production time.

The first cross-industry guidelines for the implementation of structural health monitoring for aerospace applications have been created as a SAE International Aerospace Recommended Practices document: SAE ARP 6461 ‘Guidelines for Implementation of Structural Health Monitoring on Fixed Wing Aircraft’ [1]. These guidelines have brought together manufacturers, operators / users, systems integrators, regulators, technology providers and researchers to produce information on the integration of SHM into aircraft maintenance procedures, generic requirements and advice on validation, verification and airworthiness. The take-up of SHM in the aerospace industry has been slow, in part due to the lack of accepted industry practices surrounding not just the technology itself (sensors and sensor systems) but also the associated issues arising from the introduction of new methods into aircraft maintenance.

Global aviation is growing exponentially and there is a great emphasis on trajectory optimization to reduce the overall environmental impact caused by aircraft. Many optimization techniques exist and are being studied for this purpose. The CLEAN SKY Joint Technology Initiative for aeronautics and Air transport, a European research activity run under the Seventh Framework program, is a collaborative initiative involving industry, research organizations and academia to introduce novel technologies to improve the environmental impact of aviation. As part of the overall research activities, “green” aircraft trajectories are addressed in the Systems for Green Operations (SGO) Integrated Technology Demonstrator. This paper studies the impact of large commercial aircraft trajectories optimized for different objectives applied to the on board systems.

In today's aircraft the diagnostic and prognostic systems play a crucial part in aircraft safety while reducing the operating and maintenance costs. Aircraft are very complex in their design and require consistent monitoring of systems to establish the overall vehicle health status. Most diagnostic systems utilize advanced algorithms (e.g. Bayesian belief networks or neural networks) which usually operate at system or sub-system level. The sub-system reasoners collect the input from components and sensors to process the data and provide the diagnostic/detection results to the flight advisory unit. Several sources of information must be taken into account when assessing the vehicle health, to accurately identify the health state in real time. These sources of information are independent system-level diagnostics that do not exchange any information/data with the surrounding systems.