This paper presents the results of an experimental campaign to measure thruster-relevant parameters for a high-power (180kW) inductive propulsion system utilising Ar, $ {\textrm{O}}_{2}$ , $ \textrm{N}_{2}$ , and $ \textrm{CO}_{2}$ as propellants. Results from the investigation show that inductive thrusters can make use of these propellants without the severe degradation seen in other electric propulsion systems. Furthermore, the collection of experimental data at powers greater than 100kW provides a reference of performance for the high-power electric propulsion devices intended for missions in the near future. Thrust and specific impulse in inductive systems can be improved by preferentially combining the chemical properties of atomic and molecular propellants. The maximum thrust recorded during these experiments was 7.9N, obtained using a combination of argon and oxygen (0.68 Ar + 0.32 $\textrm{O}_{2}$ ). The combination of argon and molecular propellants also decreased thermal losses within the discharge volume. Specific impulse can be doubled for the same input electric power by combining propellants, and future modifications to the thruster geometry and acceleration mechanism can be used to further improve the performance of such systems.

This work presents an alternative methodology for monitoring flight performance during airline operations using the available inboard instrumentation system. This method tries to reduce the disadvantages of the traditional specific range monitoring technique where instrumentation noise and cruise stabilisation conditions affect the quality of the performance monitoring results. The proposed method consists of using an unscented Kalman filter for aircraft performance identification using Newton’s flight dynamic equations in the body X, Y and Z axis. The use of the filtering technique reduces the effect of instrumentation and process noise, enhancing the reliability of the performance results. Besides the better quality of the monitoring process, using the proposed technique, additional results that are not possible to predict with the specific range method are identified during the filtering process. An example of these possible filtered results that show the advantages of this proposed methodology are the aircraft fuel flow offsets, as predicted in the specific range method, but also other important aircraft performance parameters as the aircraft lift and drag coefficients (CL and CD), sideslip angle (β) and wind speeds, giving the operator a deeper understanding of its aircraft operational status and the possibility to link the operational monitoring results to aircraft maintenance scheduling. This work brings a cruise stabilisation example where the selected performance monitoring parameters such as fuel flow factors, lift and drag bias, winds and sideslip angle are identified using only the inboard instrumentation such as the GPS/inertial sensors, a calibrated anemometric system and the angle-of-attack vanes relating each flight condition to a specific aircraft performance monitoring result. The results show that the proposed method captures the performance parameters by the use of the Kalman filter without the need of a strict stabilisation phase as it is recommended in the traditional specific range method, giving operators better flexibility when analysing and monitoring fleet performance.

Flight-deck Interval Management (FIM) is a modern airborne self-spacing technology that improves arrival route throughput and runway utilisation and increases hourly arrival capacity by up to four aircraft per hour and per runway, compared to conventional air traffic controller guided arrivals. The National Aeronautics and Space Administration (NASA) has been the leader in FIM research and formulated a logic that was put to an actual flight test in 2017. Despite the overall success of the project, operational deficiencies concerning the number of speed commands, which led to several recommendations for future research before operational implementation, were discovered. In this study, a new logic that implements a two-stage rule-based selection algorithm was developed to overcome those deficiencies. The proposed logic was compared to NASA’s logic on an arrival in Tokyo International Airport with multiple induced error patterns. The results indicate that the new logic significantly decreases the number of speed commands with only minor aggravations in spacing performance. The results that highlight the strengths and weaknesses of both concepts are discussed, and an outlook on and ideas for future research on FIM and the proposed logic are presented.

The ever-growing need to improve manufacturing processes has led recently to an increase in the number of automation solutions used to assemble aircraft structural elements. A process of interest to this industry is the alignment of fuselage sections, which is currently done either manually or by complex, expensive automated systems. The manual method introduces a significant production delay and most automated systems have limited flexibility. This article presents an integration solution implemented in an alternative low-cost, high-flexibility alignment robotic cell. The performance of an optical coordinate measuring machine (CMM) as feedback source for the adaptive control of a conventional industrial manipulator is assessed. Laser interferometry readings are used as reference. The contribution of the work lies in the execution of experiments based on the EN ISO 9283 standard (Manipulating industrial robots - performance criteria and related test methods) to determine the adequacy of the commercial off-the-shelf system to the tolerances and requirements of the fuselage alignment process at hand. The optimal configuration of the integrated system attained the nominal alignment position with an average accuracy of 0.16mm and $0.004^\circ$ , partially meeting the required tolerances, and the obtained values are nearly 16x better compared to a baseline, open-loop manipulator. These results serve as reference for the aerospace industry in the development of the next generation of tools and automated assembly processes.

Exergy efficiency can be used as an objective function in order to improve systems efficiency. Thus, the most efficient regions for the operation parameters can be searched easily. Exergy efficiency data of a turboprop engine’s components that have been calculated using basic engine parameters in the previous studies are modeled using cubic spline curve fitting methodology. Spline curves are on the two dimensional plane, where x axis is the input parameter and y axis is the exergy efficiency of the component. A spline curve is defined by the points subject to arbitrary selection of number and position. Initially positions of the points are located with two different methods and then in order to obtain better accuracy point positions are improved by ‘Ant colony’ and ‘Goldsection’ optimisation methods. Sum of Squares of the errors between the fitted value and data value was used as the fitness function. Least square error of 5 × 10−9 is assumed as acceptable accuracy which yields to a minimum R = 0.9998 linear correlation coefficient. In the optimisation step, independent engine variable versus calculated engine performance parameters were checked against spline fitted values. Improvement of the fitness function is observed as the number of fitting points is increased. Ant colony optimisation in engine exergy efficiency parametric modeling is a new approach in authors’ point of view.

The Goal-Oriented methodology (GO methodology) is an effective method for the reliability analysis of complex systems. It is especially suitable for the reliability analysis of multi-state complex systems containing the actual logistics, such as current, airflow and liquid flow. In order to solve the limitation that the GO methodology is not suitable for the reliability analysis of the system with feedback loop, the Boolean algebra idea is introduced to construct the Boolean operation formula of the feedback loop. In this paper, a certain type of civil aircraft flap hydraulic system with feedback loop is taken as the research object. According to the structural schematic diagram of the flap hydraulic system, the GO model of the flap hydraulic system is established. Next, the GO calculation is carried out to obtain the reliability of the flap hydraulic system. The comparison between the system reliability without feedback loop and that with feedback loop proves that the GO methodology with feedback loop is more accurate. The reliability of the system is analyzed by using the fault tree analysis (FTA) method, and the GO methodology with feedback loop is compared with the FTA method to verify the availability and correctness of the GO methodology in the reliability analysis and safety evaluation of aircraft flap hydraulic system.

The research paper addresses the problem of estimating aerodynamic parameters using a Gauss-Newton-based optimisation method. The process of the optimisation method lies on the principle of minimising the residual error between the measured and simulated responses of the system. Usually, the simulated response is obtained by integrating the dynamic equations of the system, which is found to be susceptible to the initial values, and the integration method. With the advent of the feedforward neural network, the data-driven regression methods have been widely used for identification of the system. Among them, a variant of feedforward neural network, extreme learning machine, which has proven the performance in terms of computational cost, generalisation, and so forth, has been addressed to predict the responses in the present study. The real flight data of longitudinal and lateral-directional motion have been considered to estimate their respective aerodynamic parameters. Furthermore, the estimates have been validated with the values of the classical estimation methods, such as the equation-error and filter-error methods. The sample standard deviations of the estimates demonstrate the effectiveness of the proposed method. Lastly, the proof-of-match exercise has been conducted with the other set of flight data to validate the estimated parameters.