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Automated countersink measurement methods which require contact with the workpiece are susceptible to a loss of accuracy due to cutting debris and lube build-up. This paper demonstrates a non-contact method for countersink diameter measurement on CFRP which eliminates the need for periodic cleaning. Holes are scanned in process using a laser profilometer. Coordinates for points along the countersink edge are processed with a unique filtering algorithm providing a highly repeatable estimate for major and minor diameter.

The aviation sector has played a significant role in shaping the world into what it is today. The rapid growth of global economies and the corresponding sharp rise in the number of people now wanting to travel on business and for pleasure, has largely been responsible for the development of this industry. With a predicted rise in Revenue Passenger Kilometers (RPK) by over 150% in the next 20 years, the industry will correspondingly be a significant contributor to environmental emissions. Under such circumstances optimizing aircraft trajectories for lowered emissions will play a critical role amongst various other measures, in mitigating the probable environmental effects of increased air traffic. Aircraft trajectory optimization using evolutionary algorithms is a novel field and preliminary studies have indicated that a reduction in emissions is possible when set as objectives.

The paper is devoted to the simulation of A320 wing assembly on the base of numerical experiments carried out with the help of ASRP software. The main goal is to find fasteners’ configuration with minimal number of fastening elements that provides closing of admissible initial gaps. However, for considered junction type initial gap field is not known a priori though it should be provided as input data for computations. In order to resolve this problem the methodology of random initial gap generation based on available results of gap measurements is developed along with algorithms for optimization of fasteners' configuration on generated initial gaps. Presented paper illustrates how this methodology allows optimizing assembly process for A320 wing.

Water is a contaminant that can lead to fuel system icing, microbial contamination, corrosion and fuel quantity gauging problems and therefore an efficient water management system is required in order to maximise the performance of an aircraft's fuel system. This paper describes a time-transient aircraft fuel tank model with water contamination, due to the principal mechanisms of dissolution, suspension, condensation and transportation. The tank model presented is a component of the NEPTUNE fuel system model which was developed for Airbus using the A380 as an example aircraft. A description of the physics of water contaminated fuel is given and of how this has been incorporated into a mathematical model of an aircraft fuel tank. A modular approach is demonstrated which enables interconnecting fuel tanks to be configured in larger systems in a flexible and easily understood manner.

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.

This study presents the results of the ICE GENESIS 2021 Swiss Jura Flight Campaign in a way that is readily usable for ice accretion modelling and aims at improving the description of snow particles for model inputs. 2D images from two OAP probes, namely 2D-S and PIP, have been used to extract 3D shape parameters in the oblate spheroid assumption, as there are the diameter of the sphere of equivalent volume as ellipsoid, sphericity, orthogonal sphericity, and an estimation of bulk density of individual ice crystals through a mass-geometry parametrization. Innovative shape recognition algorithm, based on Convolutional Neural Network, has been used to identify ice crystal shapes based on these images and produce shape-specific mass particle size distributions to describe cloud ice content quantitatively in details. 3D shape descriptors and bulk density have been extracted for all the data collected in cloud environments described in the regulation as icing conditions.

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.

Accurate calculation of the catch efficiency β is of paramount importance for any ice accretion calculation since β is the most important factor in determining the mass of ice accretion. A new scheme has been proposed recently in [1] for accurately calculating β on a discretized two-dimensional geometry based on the results of a Lagrangian droplet trajectory integrator (start and impact conditions). This paper proposes an extension to the algorithm in Ref. [1], which is applicable to three-dimensional surfaces with arbitrary surface discretization. The 3D algorithm maintains the positive attributes of the original 2D algorithm, namely mass conservation of the impinging water, capability to deal with overlapping impingement regions and with crossing trajectories, computational efficiency of the algorithm, and low number of trajectories required to reach good accuracy in catch efficiency.