Narrow Results

To comprehend the elemental characterization of the particles emitted from an aircraft, we performed element analysis using in-vacuum PIXE for particles emitted from the carbon disc brakes and tires in addition to the exhaust particles produced by the jet engine. As for the elemental characteristics of aircraft source particulate matter, engine reversers mainly consisted of Al, Si, Ca, and Fe, and also included Ti, Cr, Mo, and W. The disc brakes mainly contained Si, Ca, and Fe, and also contained S, K, Ti, Cr, Ni, and Cu. In tires, Na, Al, Si, Ca, Fe, and Zn were mainly found, and S, K, and Ti were also detected. Thus, there was a difference in the trace elements found in the aircraft source particulate matter. These results aid in determining the component features of particles emitted from an aircraft.

To achieve the elemental characterization of particles emitted from the aircraft, we performed elemental analysis using micro-PIXE for those emitted from carbon disc brakes and tires in addition to the turbine blade particles and engine reverser particles of the exhaust produced by jet engines, and identified the characteristics of individual particles from the elemental maps. As for the elemental characteristics of aircraft source particles, the turbine blade particles contained 16 elements (Na, Mg, Al, Si, S, K, Ca, Se, Ti, Cr, Mn, Fe, Co, Ni, Cu and W), and were considered to be those of the same origin. In the case of the engine reverser particles, in addition to turbine blade particles and turbine blade wear particles (nickel alloy), atmospheric particles were found. As one hypothesis, particles containing Ti–V, Mn–W and Cu–Zn may have got altered or aggregated in the process of particles moving from the turbine blade to the engine reverser. Clumps of particles were exhibited only in the elemental maps of tire particles. These clumps of particles were shaped like they had been scraped away, and were believed to have been caused by friction between the tire and the runway. These results aid in determining the component features of particles emitted from an aircraft.

In order to characterize particles emitted from aircraft, we analyzed the elemental composition information of particles collected from aircraft using positive matrix factorization (PMF). The factor profile and source contribution were deduced based on PMF analysis with five factors and 30 random starting points. Factor 1 contains particles derived from engine oil. Factor 2 contains particles originating from the friction between the runway surface and the tire. Factor 3 contains particles deposited on the runway surface, mainly composed of soil components. Factor 4 contains particles derived from the turbine blade. Factor 5 contains particles derived from plant combustion and particles scattered during landing. Engine reversers accounted for more than 85% of the element total value with factor 2, factor 4, and factor 5. The carbon disc brakes had different main factors depending on the sample. For the tire grooves, factor 2 and factor 3 accounted for the majority of the element total value. The PMF analysis revealed that the particles collected from aircraft contained elements with different modes of generation. In addition, it was found that particles derived from plant combustion, which are presumed to have little relevance to particles emitted from aircraft, were included in the particles collected from the engine reverser, carbon disc brakes, and tire grooves.

The performance of landing gear retraction mechanism in aircraft directly affects its safe operation. Therefore, it is important to analyze and evaluate its comprehensive performance during the design process. Multiple single kinematic and dynamic performance indexes of landing gear retraction mechanism could be solved by CAD/CAE software. The weighting factors of every single performance index are used to distinguish the different effects of comprehensive evaluation, and also achieved by the expert investigation method. Combining the a priori information of the mechanism, the comprehensive performance of landing gear retraction mechanism could be analyzed by Relative Principal Component Analysis (RPCA) method, and the scale of the landing gear retraction mechanism with the best comprehensive performance could be effectively selected. Further, RPCA could also provide a scientific reference basis for the optimization design of landing gear retraction mechanism.

As an airframe has finite lifetime and has to be designed lightweight, the maintenance of airframe is indispensable to operate aircraft without any serious troubles. After an airframe begins to operate, it suffers stresses and the stress causes the damage such as cracks of the airframe. Cracks grow with operation time and cause catastrophic phenomenon such as the mid-air disintegration when they become greater than a critical size. So, the managerial crack size is prespecified and Preventive Maintenance (PM) undergoes when the inspected crack size exceeds it. In this paper, optimal PM policies of airframe crack failure are discussed. Airframe states are represented as the Markov renewal process, and one-step transition probabilities are discussed. The total expected cost from the start of operation to the end by failure is defined and the optimal PM policies which minimize it is discussed.

We consider here the governance of learning and the diffusion of technological knowledge in the civil aircraft industry. We describe a systemic process by which specialization in knowledge encourages depth whilst breadth is captured through the integration of contributions by the lead manufacturer, which acts as systems integrator. We explore the boundaries of the knowledge bases related to airframe structure and systems and aircraft instrumentation by using patents as tracers, considering the range of scientific and technological disciplines related to the industry as well as the sources of that knowledge. We conclude that knowledge base supporting the aeronautics industry is complex and multidisciplinary, and that firms acting as system integrators have to hold the broadest knowledge bases to co-ordinate design and production.

Temperature is one important factor which decides the assembly accuracy and reliability of the aircraft. Especially with the development of large-sized aircraft, the small temperature change in the aircraft assembly will result in a large displacement deviation and non-negligible internal stress. Therefore, it’s crucial to characterize and predict the temperature during the assembly process of aircraft. Selecting one type of assembly frame for aircraft wing as the study object, temperature in this structure was measured and recorded for one year. Based on the measured data, a model of an optimized BP neural network is proposed to analyze and predict the temperature distribution. The trained temperature model shows a good result with a relative error of 1% and an absolute error of $2^{\circ }$C. Finally, the displacement of assembly frame is obtained from the temperature distribution.

For the purpose of high-fidelity aircraft cabin noise simulations during early design phases, we examine three efficient solving approaches for the fully coupled finite element model of an aircraft fuselage segment. Obtaining an efficient solution with respect to consumed computational time and resources is challenging within a conventional simulation pipeline, as large-scale and complex vibroacoustic models demand crucially high computational costs with increasing frequency. In this contribution, we adopt (1) frequency and domain specific discretization, (2) domain-decomposition techniques, and (3) model order reduction with rational Arnoldi Krylov subspace methods for an aircraft fuselage model. The three approaches have shown remarkable advantage thereby reducing the solving time as well as the memory requirement that are essential when solving large-scale models. While the discretization and the model order reduction approaches accelerate the solving process by efficiently handling the complexity of the system to be solved, domain-decomposition techniques further handle the aspect of reducing the overall memory consumption. Finally with the help of active research aircraft segment models, we implement and showcase the achieved efficiency.

A method to predict areas of possible aircraft icing and its intensity is presented. Method is operated on model gridded output. An index I_ice to identify meteorological conditions which contribute to aircraft icing is calculated at each point of a three-dimensional grid as a product of pressure and difference between mixing ratio and saturation mixing ratio multiplied by given coefficient. An area of possible icing covers grid points where values of I_ice exceed zero. Icing intensity is determined by a value of I_ice; range of positive values of I_ice is divided into three intervals which correspond to light, moderate and severe icing. Presented method is tested on numerical output of the Weather Research and Forecasting (WRF) – Advanced Research WRF (WRF–ARW) with 5-km horizontal grid spacing for Eastern Siberia and Russian Far East. Preliminary evaluations of forecasts are presented.

This chapter presents an intelligent system to automate the pilot’s actions to control high-lift devices in commercial airplanes. The modular system designed uses fuzzy logic in the two main modules: flight phase identification and flap lever command, with the objective of safely adapting the aircraft speed envelope to assure flight safety. The fuzzy system decides when and how to change the position of the high-lift devices of the aircraft as a human pilot would do but automatically, based on the identified flight phase and the speed margins. The results in a simulated real scenario show the expected behavior and have been quantitatively evaluated using some metrics.

With the change of arms combat, in recent years, the guided method of having the terminal angle constraint get an increasing attention. In considering the requirements conditions of aircraft hit the target having landing speed and speed dip, based the idea of the zero reentry vehicle and goals vision angular rate, designed for attacking ground fixed targets optimal reentry guidance law, That is to improve the accuracy of the missile, make the missile hit the target quickly, and put stringent requirements for the terminal angle constraint. The idea of using the optimal control theory, when the aircraft hit the target to meet the conditions of the terminal angle constraint, and ensure reentry vehicle maneuvering speed to loss minimum.