Program - Brookhaven National Laboratory

Session NC Covariances
Thursday March 7, 2013
Room: Empire East at 10:30 AM
NC 1 10:30 AM
Estimation of Nuclear Reaction Model Parameter Covariances and the Related Neutron
Induced Cross Sections with Physical Constraints
C. De Saint Jean, P. Archier, G. Noguere
CEA, DEN, DER, SPRC, Cadarache, F-13108 Saint-Paul-lez-Durance, France
In neutron induced reactions between 0 eV and 20 MeV, a general problem arises during the evaluation of
cross sections. Most of the time, the evaluation work is done independently between the resolved resonance
range and the continuum, giving rise to mismatches for the cross sections, larger uncertainties on boundary
and no cross correlation between high energy domain and resonance range. This paper will present several
methodologies that may be used for avoiding such effects. A first idea based on the use of experiments
overlapping two energy domains appeared in a near past. It will be reviewed and extended to the use of
systematic uncertainties (normalization for example) and for integral experiments as well. In addition, we
propose a methodology taking into account physical constraints on an overlapping energy domain where
both nuclear reaction models is used (continuity of both cross sections or derivatives for example). The use
of Lagrange multipliers (related to these constraints) in a classical generalized least square procedure will
be presented as well the numerical algorithm that may be used to find the minimum of such a cost function.
Some academic examples will then be presented for both point-wise and multigroup cross sections.
NC 2 11:00 AM
Uncertainty Propagation with Fast Monte Carlo Techniques
D. Rochman
Nuclear Research and Consultancy Group NRG, Petten, The Netherlands
W. Zwermann
Gesellschaft für Anlagen- und Reaktorsicherheit (GRS) mbH Forschungszentrum, Garching, Germany
S.C. van der Marck and A.J. Koning
Nuclear Research and Consultancy Group NRG, Petten, The Netherlands
Since 2008, several methods for nuclear data uncertainty propagation based on Monte Carlo techniques
were developed and presented. They are based on a two-step approach: (1) the random sampling of
nuclear model parameters to generate n nuclear observables such as cross sections, nubar (or alternatively
n perturbations of nuclear observables, based on covariance information), and (2) the use of these random
nuclear data in n calculations with a particle transport code (n � 1000). With the use of a stochastic
simulation code, each individual calculation is usually time-consuming because the statistical uncertainty of
the stochastic simulation should be smaller than the nuclear data uncertainty. Repeated n times, the Monte
Carlo uncertainty propagation with a Monte Carlo particle transport code becomes a large computer-time
consumer. To remedy this problem, two methods of ”fast” uncertainty propagation with a Monte Carlo
simulation code were developed, first at GRS and later at NRG. They provide a substantial reduction
of the number of Monte Carlo histories needed. In favorable cases, the uncertainty of a quantity can be
calculated in only twice the amount of computer time that is needed for the quantity itself. In this way,
the use of Monte Carlo uncertainty propagation method is possible without a large computer cluster. The
new methods will be presented and results will be compared for criticality and burn-up calculations.
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