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タイトルProbabilistic Methods for Uncertainty Propagation Applied to Aircraft Design
本文(外部サイト)http://hdl.handle.net/2060/20030003828
著者(英)Green, Lawrence L.; Khalessi, Mohammad R.; Lin, Hong-Zong
著者所属(英)NASA Langley Research Center
発行日2002-01-01
言語eng
内容記述Three methods of probabilistic uncertainty propagation and quantification (the method of moments, Monte Carlo simulation, and a nongradient simulation search method) are applied to an aircraft analysis and conceptual design program to demonstrate design under uncertainty. The chosen example problems appear to have discontinuous design spaces and thus these examples pose difficulties for many popular methods of uncertainty propagation and quantification. However, specific implementation features of the first and third methods chosen for use in this study enable successful propagation of small uncertainties through the program. Input uncertainties in two configuration design variables are considered. Uncertainties in aircraft weight are computed. The effects of specifying required levels of constraint satisfaction with specified levels of input uncertainty are also demonstrated. The results show, as expected, that the designs under uncertainty are typically heavier and more conservative than those in which no input uncertainties exist.
NASA分類Aircraft Design, Testing and Performance
レポートNOAIAA Paper 2002-3140
権利Copyright, Distribution as joint owner in the copyright
URIhttps://repository.exst.jaxa.jp/dspace/handle/a-is/90868


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