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**Harvard**

Hernández-Solís, A., Demazière, C. och Ekberg, C. (2011) *Bayesian Uncertainty Analysis of BWR Core Parameters based on Flux Measurements*.

** BibTeX **

@conference{

Hernández-Solís2011,

author={Hernández-Solís, Augusto and Demazière, Christophe and Ekberg, Christian},

title={Bayesian Uncertainty Analysis of BWR Core Parameters based on Flux Measurements},

booktitle={Transactions of American Nuclear Society},

pages={803-804},

abstract={During the last two decades, fuel loading strategies of
many nuclear power plants have been based on best
estimate (BE) calculations, allowing an optimization of
the fuel depletion efficiency along the different cycles of
the plant life. Core BE simulators aim to solve the twogroup
diffusion equation in order to predict the spatial
dependence of the scalar neutron flux. Their input
parameters are the two-group macroscopic cross-sections
and diffusion coefficients, respectively, as a function of
the state variables such as moderator temperature, void
fraction, history variables, burnup, etc.
Ringhals 1 (R1) is an ASEA-Atom Boling Water
Reactor (BWR) located at the Ringhals power plant
complex in western Sweden. 36 Traversing Incore Prove
(TIP) detectors are permanently positioned within the
core, and during each cycle a few TIP measurements at
different burnup conditions are performed in order to
estimate the actual spatial neutron flux throughout the
core and thus, the spatial distribution of the power and
thermal margins. Therefore, the accuracy of core
simulator calculations along the cycle can be assessed by
computing the difference between predicted and measured
quantities; such a procedure builds confidence in using
the simulator for the long term fuel loading plans. In this
paper, discrepancies between spatial measured and
calculated fluxes in R1 are used to perform an inverse
uncertainty analysis on the spatial dependence of the input
parameters of the Westinghouse POLCA7 [1] core
simulator (i.e. macroscopic cross-sections and diffusion
coefficients per control volume or node, that are inputs to
the discretized two-group diffusion equation). This
analysis is carried out using Bayesian statistics, where, for
a certain cycle, the frequency distributions of the
simulator inputs at every assembly node are updated
based on the error distribution of the spatial thermal flux.},

year={2011},

}

** RefWorks **

RT Conference Proceedings

SR Print

ID 154387

A1 Hernández-Solís, Augusto

A1 Demazière, Christophe

A1 Ekberg, Christian

T1 Bayesian Uncertainty Analysis of BWR Core Parameters based on Flux Measurements

YR 2011

T2 Transactions of American Nuclear Society

SP 803

OP 804

AB During the last two decades, fuel loading strategies of
many nuclear power plants have been based on best
estimate (BE) calculations, allowing an optimization of
the fuel depletion efficiency along the different cycles of
the plant life. Core BE simulators aim to solve the twogroup
diffusion equation in order to predict the spatial
dependence of the scalar neutron flux. Their input
parameters are the two-group macroscopic cross-sections
and diffusion coefficients, respectively, as a function of
the state variables such as moderator temperature, void
fraction, history variables, burnup, etc.
Ringhals 1 (R1) is an ASEA-Atom Boling Water
Reactor (BWR) located at the Ringhals power plant
complex in western Sweden. 36 Traversing Incore Prove
(TIP) detectors are permanently positioned within the
core, and during each cycle a few TIP measurements at
different burnup conditions are performed in order to
estimate the actual spatial neutron flux throughout the
core and thus, the spatial distribution of the power and
thermal margins. Therefore, the accuracy of core
simulator calculations along the cycle can be assessed by
computing the difference between predicted and measured
quantities; such a procedure builds confidence in using
the simulator for the long term fuel loading plans. In this
paper, discrepancies between spatial measured and
calculated fluxes in R1 are used to perform an inverse
uncertainty analysis on the spatial dependence of the input
parameters of the Westinghouse POLCA7 [1] core
simulator (i.e. macroscopic cross-sections and diffusion
coefficients per control volume or node, that are inputs to
the discretized two-group diffusion equation). This
analysis is carried out using Bayesian statistics, where, for
a certain cycle, the frequency distributions of the
simulator inputs at every assembly node are updated
based on the error distribution of the spatial thermal flux.

LA eng

OL 30