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A Guide to Uncertainty Quantification for Experimental Engine Research and Heat Release Analysis
ISSN: 1946-3936, e-ISSN: 1946-3944
Published August 22, 2019 by SAE International in United States
Citation: Gainey, B., Longtin, J., and Lawler, B., "A Guide to Uncertainty Quantification for Experimental Engine Research and Heat Release Analysis," SAE Int. J. Engines 12(5):509-523, 2019, https://doi.org/10.4271/03-12-05-0033.
Performing an uncertainty analysis for complex measurement tasks, such as those found in engine research, presents unique challenges. Also, because of the excessive computational costs, modeling-based approaches, such as a Monte Carlo approach, may not be practical. This work provides a traditional statistical approach to uncertainty analysis that incorporates the uncertainty tree, which is a graphical tool for complex uncertainty analysis. Approaches to calculate the required sensitivities are discussed, including issues associated with numerical differentiation, numerical integration, and post-processing. Trimming of the uncertainty tree to remove insignificant contributions is discussed. The article concludes with a best practices guide in the Appendix to uncertainty propagation in experimental engine combustion post-processing, which includes suggested post-processing techniques and down-selected functional relationships for uncertainty propagation.