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Current modelling capability for engine icing accretion prediction is still limited for App. C. To further validate icing codes in complex engine geometries, it is necessary to perform additional experimental work in relevant geometrical and environmental conditions. Within the frame of ICE GENESIS [1], an experiment has been setup to replicate the condition at the inlet of an engine first stage compressor. This paper describes the choices for the design of the engine compressor model, the setup within the icing wind tunnel and the methodology employed to obtain the results. Additionally, more effort has been focused on obtaining accurate ice shapes using a 3D scanning system. Results of 3D scans are given.

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.

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.

The rise of autonomous technologies may reflect on new vehicle traffic characteristics, likely reducing vehicle-to-vehicle proximity and emerging platooning formations. Energy consumption, stability, and surface contamination are relevant factors that are sensitive to aerodynamic interference while platooning. From the experimental perspective, most wind tunnels were originally designed to host isolated models, and these constraints often limit the investigation of multiple full-body vehicle formations (e.g. test section length, moving ground dimensions, standard testing points). This paper introduces the ‘MultiWake’ model - a parametric bluff-body device based on a morphing concept, which can emulate the aerodynamic wake characteristics of different vehicle classes.

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.

A modern benchmark for passenger cars - DrivAer model - has provided significant contributions to aerodynamics-related topics in automotive engineering, where three categories of passenger cars have been successfully represented. However, a reference model for high-performance car configurations has not been considered appropriately yet. Technical knowledge in motorsport is also restricted due to competitiveness in performance, reputation and commercial gains. The consequence is a shortage of open-access material to be used as technical references for either motorsport community or academic research purposes. In this paper, a parametric assessment of race car aerodynamic devices are presented into four groups of studies. These are: (i) forebody strakes (dive planes), (ii) front bumper splitter, (iii) rear-end spoiler, and (iv) underbody diffuser.

This paper outlines the procedure used to assess the performance of a Lane Keeping Assistance System (LKAS) in a virtual test environment using the newly developed Euro NCAP Lane Support Systems (LSS) Test Protocol, version 1.0, November 2015 [1]. A tool has also been developed to automate the testing and analysis of this test. The Euro NCAP LSS Test defines ten test paths for left lane departures and ten for right lane departures that must be followed by the vehicle before the LKAS activates. Each path must be followed to within a specific tolerance. The vehicle control inputs required to follow the test path are calculated. These tests are then run concurrently in the virtual environment by combining two different software packages. Important vehicle variables are recorded and processed, and a pass/fail status is assigned to each test based on these values automatically.

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.

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.

The simulation of heat exchanger air flow characteristics in a sub-scale wind tunnel test requires an accurate representation of the full-scale pressure drop across the element. In practice this is normally achieved using laminations of various porous materials and honeycombs on the basis of experience and ad hoc data. In view of this, a series of measurements of the pressure drop, in both the near and far field, across screens with porosity (β) in the range 0.41 ≺ β ≺ 0.76 are reported. The aim being to establish a relationship between the porosity and the pressure drop characteristics of a given material at various angles of inclination to the free-stream flow. Furthermore, the effect of screen depth was investigated using honeycombs. This data will facilitate detailed design and accurate representation of the flow characteristics at sub scale.

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.

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.

Significant effort has been applied to the introduction of automation for the structural assembly of aircraft. However, the equipping of the aircraft with internal services such as hydraulics, fuel, bleed-air and electrics and the attachment of movables such as ailerons and flaps remains almost exclusively manual and little research has been directed towards it. The problem is that the process requires lengthy assembly methods and there are many complex tasks which require high levels of dexterity and judgement from human operators. The parts used are prone to tolerance stack-ups, the tolerance for mating parts is extremely tight (sub-millimetre) and access is very poor. All of these make the application of conventional automation almost impossible. A possible solution is flexible metrology assisted collaborative assembly. This aims to optimise the assembly processes by using a robot to position the parts whilst an operator performs the fixing process.

Water is always present in jet fuel, usually in a mixture of forms. At very low temperatures this phenomenon can lead to the formation of ice crystals within the aircraft fuel system, which can then stay in suspension within the entire volume of fuel. Pumps within the fuel system transfer fuel around the system. Pumps such as boost pumps that are typically used in fuel systems are protected by a weave type filter mesh at the inlet. Ice accretion on the surface of this mesh has operational implications as it can cause non optimal fuel flow. In this investigation, two fundamental tools are being used: 1) a high fidelity MATLAB model of a mesh strainer, pick-up line and pump, and 2) a test rig of the modelled system. The model is being used to investigate fuel system performance when exposed to fuel containing water/ice contaminants at cold temperatures.

The objective of this work is to investigate the thin water film characteristics by performing a range of experiments for different icing conditions. Our focus is on the SLD conditions where the droplets are larger and other effects like splashing and re-impingement could occur. Three features for the thin water film have been studied experimentally: the water film velocity, wave celerity and its wavelength. The experiments are performed in the icing facilities at Cranfiled University. The stability of the water film for the different conditions has been studied to find a threshold for transient from continues water film to non-continues form. A new semi-empirical method is introduced to estimate the water film thickness based on the experimental data of water film velocity in combination of theoretical analysis of water film dynamics. The outcome of this work could be implemented in SLD icing simulation but more analysis is needed.

This paper describes the impact of noise on the civil aircraft design process. The challenge to design ‘silent’ aircraft is the development of efficient airframe-engine technologies, for which integration is essential to produce an optimum aircraft, otherwise penalties such as higher fuel consumption, and, or noise are a concern. A description of work completed by Cranfield University will cover design methodologies used for a Broad delta airframe concept, with reference to future studies into alternate concepts. Engine cycle designs for ultra-high bypass ratio, constant volume combustor, and recuperated propulsion cycles are described, with a discussion of integration challenges within the airframe.

As aviation is one of the fastest growing industrial sector world wide, air-traffic emissions are projected to increase their stake in the contribution to global warming. According to recent studies, both CO2 and contrails will be the principal air-traffic pollutants. Since the environmental impact of contrails is potentially larger, their avoidance is becoming discussed in the aeronautical community. Work on this topic has been carried out at Cranfield University in form of a PhD project. A project summary is given in this paper where contrail avoidance strategies and the different aspects of contrail avoidance are highlighted. The first section provides an overview on the formation principles of contrails based on a literature review. Different technologies are given in the second part, and their introduction is discussed in the last section.