| 1. |
- Alhassan, Erwin, 1984-
(författare)
-
Nuclear data uncertainty quantification and data assimilation for a lead-cooled fast reactor : Using integral experiments for improved accuracy
- 2015
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- For the successful deployment of advanced nuclear systems and optimization of current reactor designs, high quality nuclear data are required. Before nuclear data can be used in applications they must first be evaluated, tested and validated against a set of integral experiments, and then converted into formats usable for applications. The evaluation process in the past was usually done by using differential experimental data which was then complemented with nuclear model calculations. This trend is fast changing due to the increase in computational power and tremendous improvements in nuclear reaction models over the last decade. Since these models have uncertain inputs, they are normally calibrated using experimental data. However, these experiments are themselves not exact. Therefore, the calculated quantities of model codes such as cross sections and angular distributions contain uncertainties. Since nuclear data are used in reactor transport codes as input for simulations, the output of transport codes contain uncertainties due to these data as well. Quantifying these uncertainties is important for setting safety margins; for providing confidence in the interpretation of results; and for deciding where additional efforts are needed to reduce these uncertainties. Also, regulatory bodies are now moving away from conservative evaluations to best estimate calculations that are accompanied by uncertainty evaluations.In this work, the Total Monte Carlo (TMC) method was applied to study the impact of nuclear data uncertainties from basic physics to macroscopic reactor parameters for the European Lead Cooled Training Reactor (ELECTRA). As part of the work, nuclear data uncertainties of actinides in the fuel, lead isotopes within the coolant, and some structural materials have been investigated. In the case of the lead coolant it was observed that the uncertainty in the keff and the coolant void worth (except in the case of 204Pb), were large, with the most significant contribution coming from 208Pb. New 208Pb and 206Pb random nuclear data libraries with realistic central values have been produced as part of this work. Also, a correlation based sensitivity method was used in this work, to determine parameter - cross section correlations for different isotopes and energy groups.Furthermore, an accept/reject method and a method of assigning file weights based on the likelihood function are proposed for uncertainty reduction using criticality benchmark experiments within the TMC method. It was observed from the study that a significant reduction in nuclear data uncertainty was obtained for some isotopes for ELECTRA after incorporating integral benchmark information. As a further objective of this thesis, a method for selecting benchmark for code validation for specific reactor applications was developed and applied to the ELECTRA reactor. Finally, a method for combining differential experiments and integral benchmark data for nuclear data adjustments is proposed and applied for the adjustment of neutron induced 208Pb nuclear data in the fast energy region.
|
|
| 2. |
- Sjöstrand, Henrik, 1978-, et al.
(författare)
-
Adjustment of nuclear data libraries using integral benchmarks
- 2017
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Integral experiments can be used to adjust ND-libraries and consequently the uncertainty response in important applications. . In this work we show how we can use integral experiments in a consistent way to adjust the TENDL library. A Bayesian method based on assigning weights to the different random files using a maximum likelihood function [1] is used. Emphasis is put on the problems that arise from multiple isotopes being present in a benchmark [2]. The challenges in using multiple integral experiments are also addressed, including the correlation between the different integral experiments.Methods on how to use the Total Monte Carlo method to select benchmarks for reactor application will further be discussed. In particular in respect to the so-called fast correlation coefficient and the fast-TMC method [3]
|
|
| 3. |
- Sjöstrand, Henrik, 1978-, et al.
(författare)
-
TENDL adjustments using integral benchmarks
- 2017
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Integral experiments can be used to adjust ND-libraries. In this work we show how we can use integral experiments in a consistent way to adjust the TENDL library. A Bayesian method based on assigning weights to the different random files using a maximum likelihood function [1] is used. Emphasis is put on the problems that arise from multiple isotopes being present in a benchmark [2]. The challenges in using multiple integral experiments are also addressed, including the correlation between the different integral experiments. [1] P. Helgesson, H. Sjöstrand, A.J. Koning, J. Rydén, D. Rochman, E. Alhassan, S. Pomp, Combining Total Monte Carlo and Unified Monte Carlo: Bayesian nuclear data uncertainty quantification from auto-generated experimental covariances, Progress in Nuclear Energy, Volume 96, 2017, Pages 76-96, ISSN 0149-1970, http://dx.doi.org/10.1016/j.pnucene.2016.11.006.[2]E. Alhassan, H. Sjöstrand, P. Helgesson, M. Österlund, S. Pomp, A.J. Koning, D. Rochman, On the use of integral experiments for uncertainty reduction of reactor macroscopic parameters within the TMC methodology, Progress in Nuclear Energy, Volume 88, 2016, Pages 43-52, ISSN 0149-1970, http://dx.doi.org/10.1016/j.pnucene.2015.11.015.
|
|
| 4. |
|
|
