Abstract
ANSWERS® is developing a set of uncertainty quantification (UQ) tools for use with its major physics codes: WIMS/PANTHER (reactor physics), MONK (criticality and reactor physics) and MCBEND (shielding and dosimetry). The Visual Workshop integrated development environment allows the user to construct and edit code inputs, launch calculations, post-process results and produce graphs, and recently uncertainty quantification and optimisation tools have been added. Prior uncertainties due to uncertainties in nuclear data or manufacturing tolerances can be estimated using the sampling method or using the sensitivity options in the physics codes combined with appropriate covariance matrices. To aid the user in the choice of appropriate validation experiments, the MONK categorisation scheme and/or a similarity index can be used. An interactive viewer has been developed which allows the user to search through, and browse details of, over 2,000 MONK validation experiments that have been analysed from the ICSBEP and IRPhE validation sets. A Bayesian updating approach is used to assimilate the measured data with the calculated results. It is shown how this process can be used to reduce bias in calculated results and reduce the calculated uncertainty on those results. This process is illustrated by application to a PWR fuel assembly.
Highlights
When calculating best estimate reactor parameters of interest it is important to provide an accurate estimated value of a given parameter, and to provide a reliable estimate of the uncertainty on that estimated value
Initial uncertainty quantification (UQ) tool development focused on the sampling method in which the user can specify statistical distributions rather than numerical values for user-specified input parameters [3]
Capabilities have been included in the physics codes to calculate sensitivities which can be combined with a covariance matrix for the input parameters as an alternative way of undertaking UQ
Summary
When calculating best estimate reactor parameters of interest it is important to provide an accurate estimated value of a given parameter, and to provide a reliable estimate of the uncertainty on that estimated value. For some years ANSWERS has been developing Visual Workshop, an Integrated Development Environment to accompany the physics codes This allows the user to construct and edit code inputs, launch calculations, post-process results and produce graphs, and recently uncertainty quantification and optimisation tools have been added. These methods are described and results for a PWR fuel assembly are presented. In this paper we concentrate on the Bayesian updating approach and describe how this is implemented in ANSWERS software It is shown how this process can be used to reduce bias in calculated results and reduce the uncertainty on the estimated quantities. This process is illustrated by application to a PWR fuel assembly
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
