Chemical model reduction under uncertainty

Type
Presentation

Authors
Najm, Habib
Galassi, R. Malpica
Valorani, M.

Date
2016-01-05

Abstract
We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.

Conference/Event Name
Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2016)

Additional Links
http://mediasite.kaust.edu.sa/Mediasite/Play/cf64569c53d5426d8a37d2f4b9f054331d?catalog=ca65101c-a4eb-4057-9444-45f799bd9c52

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