TAILIEUCHUNG - Evaluating nuclear data and their uncertainties

This paper discusses some uncertainty quantification methodologies in use today, their strengths, their pitfalls, and alternative approaches that have proved to be highly successful in other fields. | Evaluating nuclear data and their uncertainties EPJ Nuclear Sci. Technol. 4 29 2018 Nuclear Sciences P. Talou published by EDP Sciences 2018 amp Technologies https epjn 2018032 Available online at https REGULAR ARTICLE Evaluating nuclear data and their uncertainties Patrick Talou Nuclear Physics Group Theoretical Division Los Alamos National Laboratory LosAlamos USA Received 8 December 2017 Received in final form 21 February 2018 Accepted 17 May 2018 Abstract. In the last decade or so estimating uncertainties associated with nuclear data has become an almost mandatory step in any new nuclear data evaluation. The mathematics needed to infer such estimates look deceptively simple masking the hidden complexities due to imprecise and contradictory experimental data and natural limitations of simplified physics models. Through examples of evaluated covariance matrices for the soon-to-be-released . ENDF library . cross sections spectrum multiplicity this paper discusses some uncertainty quantification methodologies in use today their strengths their pitfalls and alternative approaches that have proved to be highly successful in other fields. The important issue of how to interpret and use the covariance matrices coming out of the evaluated nuclear data libraries is discussed. 1 The current paradigm combination of differential quantities. Perhaps the most emblematic integral data in our field is the neutron The last two decades have seen a significant rise in efforts to multiplication factor keff of the Jezebel Pu fast critical quantify uncertainties associated with evaluated nuclear assembly see Fig. 2 . This factor does not represent a data. Most general purpose libraries now contain a quantity intrinsic to the isotope 239Pu or to a particular relatively large number of covariance matrices associated reaction channel as opposed to differential data. Its with various nuclear data types reaction cross sections modeling requires a .

• Năng lượng
• Uncertainty quantification methodologies
• Evaluating nuclear data
• Contradictory experimental data
• Nuclear data evaluation
• Nuclear data types
• Nuclear science and engineering
• Void fraction prediction
• Separated flows in the nearly horizontal tubes
• Passive auxiliary feedwater system
• Experimental data covering various types