Aerostatic Aircraft Flight Environment Modeling and Investigation

Paper #:
  • 2014-01-2147

Published:
  • 2014-09-16
DOI:
  • 10.4271/2014-01-2147
Citation:
Neydorf, R., Sigida, Y., Kudinov, N., and Portnova, E., "Aerostatic Aircraft Flight Environment Modeling and Investigation," SAE Technical Paper 2014-01-2147, 2014, doi:10.4271/2014-01-2147.
Pages:
9
Abstract:
Airship dimensions define the application of the computer modeling methods under their development and investigation. Herein, the need to simulate the flight environment state - the atmospheric conditions of their traffic route - arises. The atmospheric parameters have both regular and random components, which is due to the nonstationarity of the atmospheric phenomena. Hence, it is essential to define the actual ranges, and the representative values of the atmospheric effects. Weather data are used for the analysis and the airflow performance computation in the operational area. Through their statistical processing, we need to obtain the most informative characteristics of the weather conditions in whole, and of their trends. The investigation has shown that the weather data gathering system is nonperfect. The sampling frequency is irregular and not high, test values in the specific parameters are obtained asynchronously. At this, altitude is the most critical parameter under measuring, and all the observable parameters are to be referenced to the altitude in the problem on the flight environment parameter simulation. Consequently, the problem on the statistical processing of the weather data array acquires importance and specificity.Efficient algorithms of the Integrated Global Radiosonde Archive application are considered in the paper. It is shown how the most informative estimates of the route time and calendar conditions affecting the flight aerodynamics can be obtained on the base of the data statistical processing. The research and calculation algorithm is based on the fact that all the controlled parameters are to be referenced to the altitude. Thus, the problem on the data statistical processing acquires clear directionality from the preprocessing and efficient data structuring up to the objective estimation of their processing results.
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