Document Type
Article
Abstract
This work presents paradigm applications to reactor physics of the innovative mathematical methodology for "predictive modeling of coupled multi-physics systems (PMCMPS)" developed by Cacuci (2014). This methodology enables the assimilation of experimental and computational information and computes optimally predicted responses and model parameters with reduced predicted uncertainties, taking fully into account the coupling terms between the multi-physics systems, but using only the computational resources that would be needed to perform predictive modeling on each system separately. The paradigm examples presented in this work are based on a simple neutron diffusion model, chosen so as to enable closed-form solutions with clear physical interpretations. These paradigm examples also illustrate the computational efficiency of the PMCMPS, which enables the assimilation of additional experimental information, with a minimal increase in computational resources, to reduce the uncertainties in predicted responses and best-estimate values for uncertain model parameters, thus illustrating how very large systems can be treated without loss of information in a sequential rather than simultaneous manner. © 2013 Elsevier Ltd. All rights reserved.
Digital Object Identifier (DOI)
Publication Info
Published in Annals of Nuclear Energy, Volume 9, 2014, pages 279-291.
Rights
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (https://creativecommons.org/licenses/by/4.0/).
APA Citation
Fang, R., Cacuci, D., & Badea, M. (2016). Predictive Modeling of a Paradigm Mechanical Cooling Tower Model: II. Optimal Best-Estimate Results with Reduced Predicted Uncertainties. Energies, 9(9), 747.https://doi.org/10.1016/j.anucene.2013.11.025