نشریه مهندسی هوانوردی
سال هجدهم شماره 2 (پاییز و زمستان 1395)

In this paper, radar absorbent materials with complex permittivity and permeability coefficients are studied. A novel swarm algorithm called Imitation-base Swarm Optimization is proposed to solve the Rardar Absorbent Nano-Material problems. It is suggested that each individual in the swarm explores the search space for better positions. It is shown that our proposed method gives better and high quality results and numerous applications are foreseeable for it. The program is capable of arranging and prioritizing the layers. It can choose the optimum layer thickness and do the modeling for different frequency and incidence angles. Reflection losses are analyzed at the microwave range for different angles. This code can also be used for the case of both the electric and magnetic polarizations.

Reliability centered maintenance is one of the most affordable maintenance methods of third and fourth generation which is attractive to most industries particularly aviation industry. The scope of this study is to investigate the obstacles in pattern establishment for this maintenance in a flight unit that has a precautionary maintenance system for over 50 years. This investigation is a descriptive survey. The statistical society includes all of the personnel involved in a maintenance organization for aviation systems. This research work has been performed by a simple random sampling method and the sample size has been selected as 100 persons based on Cochrane method with limited society. After measurement tool design and verifying its validity and stability, t and F tests have been used from Smirnov and Kolmogrov tests in order to analyze the data. Results of this study show that maintenance pattern establishment based on reliability is not feasible in this organization and its establishment is only possible in native systems designed according to maintenance requirements based on reliability.

In this research, an investigation has been made to find out the reasons of failure occurred in the wing box connection of a commercial aircraft. The investigation consists of mechanical, metallurgical and fractographical tests. A procedure based on MIL-1530-C standard has then been developed for the purpose of re-engineering of the failed component to achieve a design with a higher performance. The results of this research emphasis that to get rid of the deficiencies in aeronautical structural components, an appropriate re-engineering procedure must be derived based on the original used design philosophy in conjunction with appropriate numerical and experimental tests. It is concluded that practical use of this standard can be a complicated task and therefore a refined methodology has to be derived instead based on the considered standard rules and judgments.

In this study, weight optimization of the prismatic core sandwich panel under the transverse and longitudinal loadings has been independently investigated. To solve the optimization problems corresponding to the mentioned loadings, the Improved Constrained Differential Evolution (ICDE) algorithm based on the multi-objective constraint handling method has been used. The constrains of the problems are buckling load and yield stress. By comparing the results of the ICDE with those obtained by the other evolutionary algorithms based on the penalty function method in the previous studies, it can be seen that the results of the transverse loading obtained in this study are equal to those of the previous works, but the results of the ICDE in the longitudinal loading are better. In addition to its better results and ease of Implementation, another advantage of ICDE is that there is no need to the process of trial and error to fine tuning of the penalty function parameters. It can be observed that for the both types of loading, values of the panel height, the thicknesses of the face and core in addition to the weight index are increased by increasing the load index to avoid yielding and buckling of the panel. But in a constant value of the load index, by increasing the core corrugate number, the weight index has a lowering behavior in the transverse loading and a rising behavior in the longitudinal loading. However, the thicknesses of the face and core have a lowering behavior and the panel height has a rising behavior.

In this study, given the importance of maintaining and improving the safety and quality of aircraft and also, the role of human factors in aviation accidents in particular, pilots is presented a conceptual model from the management perspective. In addition to, factors affecting on passenger pilot performance in terms of three variables is investigated: (a) Individual variables include intelligence, concentration, physical and mental health, language proficiency, experience and power the leadership (b) organizational variables include type and age of the aero planes, quality training, crew skills, technical support or maintenance and management method now and (c) environmental moderator variables, including flight area, weather conditions, the quality tools and communication systems navigation, air traffic bulk, the quality of airport airstrip and aviation rules country. This research is applied and descriptive-survey. It was used questionnaire to collect the data for this research. The samples of companies studied via census are 200 passenger pilots. Hypothesis testing is done with process analysis coefficients via maximum likelihood method by AMOS. Fitness indicators show that the proposed model is a good fit. Test the hypotheses are confirmed the effect of independent variables on performance. They show that between the parameters of individual factors, experience of pilot and in organizational factors, quality of training, and among the environmental factors, weather conditions, has the greatest impact on the performance pilot.

This paper presents a control augmentation system (CAS) based on the dynamic inversion (DI) and neural networks for a highly maneuverable aircraft. A neural flight control system is used to provide adaptive flight control, without requiring gain-scheduling or system identification. Neural networks on-line is used to compensate for inversion error which arise from imperfect modeling, approximate inversion, or sudden change in aircraft dynamics. A stable weights adjustment rule for the on-line neural network is derived by the Lyapunov stability theorem. Finally, nonlinear six-degree-of-freedom simulation results for an F-18 aircraft model are presented to demonstrate the effectiveness of the proposed CAS.