Department of Physics and Astronomy

Nuclear data evaluation and uncertainty propagation

Total Monte Carlo (TMC) is a method to propagate nuclear data uncertainties to different applications, such as fission reactors, fusion reactors and shielding applications.

The basic idea is to use a state-of-the-art nuclear model code like TALYS and randomize the input parameters within a reasonable range. This range may be defined as fixed. Alternativelly a feedback-loop may be used, which compares the resulting calculated cross sections with the existing data-set in the EXFOR database of nuclear reaction data, in order to decide whether the current parameter set leads to acceptable results.

In this way several hundred possible cross-section datasets are generated. TENDL is the TALYS Evaluated Nuclear data library.

These datasets are, after proper formatting, feed into a simulation code for the system (e.g. a reactor). In this way the macroscopic parameters and their corresponding uncertainties are calculated in direct dependence of basic nuclear physics input parameter. Since this is done "event-by-event" (parameter-set by parameter-set) the results are traceable back to the input data opening up for sensitivity analysis, studies of correlations, etc.

One part of this work is MACRO (MAssive Computation methodology for Reactor Operations), a contribution to the GENIUS collaboration.

In April 2013 we held the meeting Uncertainty propagations in the nuclear fuel cycle.

The TMC uncertainty propagation and TENDL production. In the TMC processes the final result is a spread in a macroscopic parameter. This spread is the systematic uncertainty in the calculation due to ND in the investigated parameter.

Contact person

Please contact Henrik Sjöstrand for more information about this project.

Selected publications

Petter Helgesson, Dimitri Rochman, Henrik Sjöstrand, Erwin Alhassan and Arjan Koning
UO2 vs MOX: propagated nuclear data uncertainty for keff, with burnup
To be published in Nuclear Science and Engineering

H. Sjöstrand, E. Alhassan, S. Conroy, J. Duan, C. Hellesen, S. Pomp, M. Österlund, A. Koning, and D. Rochman
Total Monte Carlo Evaluation for Dose Calculation
Radiation Protection Dosimetry (2013) doi: 10.1093/rpd/nct296

H. Sjöstrand, E. Alhassan, J. Duan, C. Gustavsson, A. Koning, S. Pomp, D. Rochman, M. Österlund
Propagation of nuclear data uncertainties for ELECTRA burn-up calculations
Proc. 2013 International Conference on Nuclear Data for Science & Technology (ND2013) arxiv.org/abs/1304.1701

D. Rochman, W. Zwermann, S.C. van der Marck, A.J. Koning, H. Sjöstrand, P. Helgesson and B. Krzykacz-Hausmann
Efficient use of Monte Carlo: uncertainty propagation
Submitted to Nuclear Science and Engineering, May 2013

E. Alhassan, H. Sjöstrand, J. Duan, C. Gustavsson, S. Pomp, M. Österlund, D. Rochman, A. J. Koning
Uncertainty analysis of Lead cross sections on reactor safety for ELECTRA
Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo, Paris, October 27-31, 2013 Fulltext in DiVA