Quantifying uncertainty in chemical systems modeling.
- The Johns Hopkins University, Baltimore, MD
This study compares two techniques for uncertainty quantification in chemistry computations, one based on sensitivity analysis and error propagation, and the other on stochastic analysis using polynomial chaos techniques. The two constructions are studied in the context of H{sub 2}-O{sub 2} ignition under supercritical-water conditions. They are compared in terms of their prediction of uncertainty in species concentrations and the sensitivity of selected species concentrations to given parameters. The formulation is extended to one-dimensional reacting-flow simulations. The computations are used to study sensitivities to both reaction rate pre-exponentials and enthalpies, and to examine how this information must be evaluated in light of known, inherent parametric uncertainties in simulation parameters. The results indicate that polynomial chaos methods provide similar first-order information to conventional sensitivity analysis, while preserving higher-order information that is needed for accurate uncertainty quantification and for assigning confidence intervals on sensitivity coefficients. These higher-order effects can be significant, as the analysis reveals substantial uncertainties in the sensitivity coefficients themselves.
- Research Organization:
- Sandia National Laboratories
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 990984
- Report Number(s):
- SAND2004-4500J
- Journal Information:
- Proposed for publication in International Journal of Chemical Kinetics., Journal Name: Proposed for publication in International Journal of Chemical Kinetics. Journal Issue: 6 Vol. 37; ISSN IJCKBO; ISSN 0538-8066
- Country of Publication:
- United States
- Language:
- English
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