Quantification of Margins and Mixed Uncertainties using Evidence Theory and Stochastic Expansions
The objective of this paper is to implement Dempster-Shafer Theory of Evidence (DSTE) in the presence of mixed (aleatory and epistemic) uncertainty to the Quantication of Margins and Uncertainties (QMU) of aerospace simulations. This study focuses on quantifying the simulation uncertainties, both in the design condition and the performance boundaries along with the determination of margins. To address the possibility of multiple sources and intervals for epistemic uncertainty characterization, DSTE is used for uncertainty quantification. An approach to incorporate aleatory uncertainty in Dempster-Shafer structures is presented by discretizing the probability distributions into sets of intervals. In view of excessive computational costs for large scale applications and repetitive simulations needed for DSTE analysis, a stochastic response surface based on point-collocation non-intrusive polynomial chaos (NIPC) has been implemented as the surrogate for the model response. The technique is demonstrated on a model problem with non-linear analytical functions representing the outputs and performance boundaries of two coupled systems. Finally, the QMU approach is demonstrated on a multi-disciplinary analysis of a high speed civiltransport (HSCT).
H. R. Shah et al., "Quantification of Margins and Mixed Uncertainties using Evidence Theory and Stochastic Expansions," Proceedings of the 16th AIAA Non-Deterministic Apporaches Conference (2014, National Harbor, MD), American Institute of Aeronautics and Astronautics (AIAA), Jan 2014.
The definitive version is available at https://doi.org/10.2514/6.2014-0300
16th AIAA Non-Deterministic Approaches Conference (2014: Jan. 13-17, National Harbor, MD)
Mechanical and Aerospace Engineering
Center for High Performance Computing Research
Article - Conference proceedings
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