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.
Probabilistic Methods for Uncertainty Propagation Applied to Aircraft Design
20th AIAA Applied Aerodynamics Conference ; 2002 ; Saint Louis, MO, United States
2002-01-01
Miscellaneous
No indication
English
Probabilistic Methods for Uncertainty Propagation Applied to Aircraft Design
British Library Conference Proceedings | 2002
|Prediction of probabilistic design models for uncertainty propagation
Automotive engineering | 2006
|Prediction of Probabilistic Design Models for Uncertainty Propagation
SAE Technical Papers | 2006
|Aerospatiale Probabilistic Methods Applied to Aircraft Maintenance
British Library Conference Proceedings | 1993
|