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EN
Autonomous airships have gained a high degree of importance over the last decades, both theoretically as well and practically. This is due to their long endurance capability needed for monitoring, observation and communication missions. In this paper, a Multi-Objective Optimization approach (MOO) is followed for conceptual design of an airship taking aerody- namic drag, static stability, performance as well as the production cost that is proportional to the helium mass and the hull surface area, into account. Optimal interaction of the afo- rementioned disciplinary objectives is desirable and focused through the MOO analysis. Standard airship configurations are categorized into three major components that include the main body (hull), stabilizers (elevators and rudders) and gondola. Naturally, component sizing and positioning play an important role in the overall static stability and performance characteristics of the airship. The most important consequence of MOO analysis is that the resulting design not only meets the mission requirement, but will also be volumetrically optimal while having a desirable static and performance characteristics. The results of this paper are partly validated in the design and construction of a domestic unmanned airship indicating a good potential for the proposed approach.
EN
In this paper, selection and analysis of an atmospheric two stage separation system is di- scussed. The main purpose of this system is to test a supersonic parachute projectile, where a stage separation occurs after the burn out. Subsequently, the parachute is ejected from the payload after a minimum elapsed time. The separation times, for the supersonic parachute ejection, as well as the time needed for a safe clearing distance between the two stages are two critical issues in the separation process. In this respect, the knowledge of the relative position between the two stages is necessary to assure a safe distance and in order to ad- just the required system parameters. In addition, as the nature of the parameters involved in the separation process is not deterministic, it would be useful to utilize the concept of random variables in the dynamic modeling of the separation process. In this paper, the mo- deling and simulation of the separation process is initially performed and partially verified. Subsequently, an approximate statistical method is utilized to acquire some probabilistic in- formation about the relative distances at the two critical times. According to the simulation results, the relative distance between the two stages falls in a safe region. Finally, Monte Carlo simulation is also performed for comparison and verification of the statistical results that indicated a small and acceptable deviation between the two approaches. Thus, it can be concluded that the simpler approximate statistical approach is also valid for uncertainty analysis and can provide valuable knowledge needed in the preliminary design phase of the separation system.
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