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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.

The purpose of this study is to present a parametric fuel tank filling model from first principles. The aim is to build a tool that can help with the initial tank layout, to make sure the design does not promote premature shut off. The governing equations of the model are detailed and results for a test case are presented. The model is based on a common set of parameters enabling it to be adapted to a set of design constrains. Additionally, the model is validated by experimental data where available and a sensitivity analysis on critical design parameters that promote premature shut off is performed.

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.

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.

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.

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 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.

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

The theory of liquid fuel jet instabilities has been developed under several assumptions, which include the assumption that the jets breakup processes are isothermal. However, liquid fuels are normally injected into an elevated combustion-chamber temperature to maintain a desirable homogeneous combustible mixture - liquid vapour and air. Therefore, a new linear theory model is developed for the instability and breakup of non-isothermal liquid jets, with consideration of a spatially variation of surface tension along the liquid-gas interface. The spatial variation of surface tension is obtained through temperature-dependent surface tension and transient heat-transfer from the combusting gases to the liquid jet. The classical interface hydrodynamic breakup theory and solution of heat-transfer through semi-infinite medium are coupled through the surface tension gradient. The analytical model accounts for the non-isothermal effects on jet breakup.

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.