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Partitioned Analysis of Coupled Numerical Models Considering Imprecise Parameters and Inexact Models
The present study develops an integrated coupling and uncertainty quantification framework for strongly coupled models that explicitly considers the propagation of uncertainty and bias inherent in model prediction between constituents during the iterative coupling process. Utilizing optimization techniques, three distinct configurations are formulated that differ in sequence of coupling and uncertainty quantification campaigns. Focusing on a controlled structural dynamics problem, the systematic biases from the constituents are quantified, from which the critical components of the model that require further improvement can be identified to aid in the prioritization of future code development efforts.
Partitioned Analysis of Coupled Numerical Models Considering Imprecise Parameters and Inexact Models
The present study develops an integrated coupling and uncertainty quantification framework for strongly coupled models that explicitly considers the propagation of uncertainty and bias inherent in model prediction between constituents during the iterative coupling process. Utilizing optimization techniques, three distinct configurations are formulated that differ in sequence of coupling and uncertainty quantification campaigns. Focusing on a controlled structural dynamics problem, the systematic biases from the constituents are quantified, from which the critical components of the model that require further improvement can be identified to aid in the prioritization of future code development efforts.
Partitioned Analysis of Coupled Numerical Models Considering Imprecise Parameters and Inexact Models
Farajpour, Ismail (author) / Atamturktur, Sez (author)
Journal of Computing in Civil Engineering ; 28 ; 145-155
2012-08-15
112014-01-01 pages
Article (Journal)
Electronic Resource
Unknown
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