EPJ Web Conf.
Volume 146, 2017ND 2016: International Conference on Nuclear Data for Science and Technology
|Number of page(s)||4|
|Section||Thermal Scattering Laws and Libraries|
|Published online||13 September 2017|
Thermal neutron scattering evaluation framework
1 Georgia Inst Technol, 770 State St NW, Room 3-39S, Atlanta, GA 30318, USA
2 PSN-EXP/SNC/LNR, IRSN, Fontenay-aux-Roses, France
3 Rensselaer Polytech Inst, Gaerttner LINAC Ctr, Troy, NY 12180, USA
4 Oak Ridge Natl Lab, Reactor & Nucl Syst Div, Oak Ridge, TN 37831, USA
a e-mail: firstname.lastname@example.org This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
Published online: 13 September 2017
A neutron scattering kernel data evaluation framework for computation of model-dependent predictions and their uncertainties is outlined. In this framework, model parameters are fitted to double-differential cross section measurements and their uncertainties. For convenience, the initial implementation of this framework uses the molecular dynamics model implemented in the GROMACS code. It is applied to light water using the TIP4P/2005f interaction model. These trajectories computed by GROMACS are then processed using nMOLDYN to compute the density of states, which is then used to calculate the scattering kernel using the Gaussian approximation. Double differential cross sections computed from the scattering kernel are then fitted to double-differential scattering data measured at the Spallation Neutron Source detector at Oak Ridge National Laboratory. The fitting procedure is designed to yield optimized model-parameters and their uncertainties in the form of a covariance matrix, from which new evaluations of thermal neutron scattering kernel will be generated. The Unified Monte Carlo method will be used to fit the simulation data to the experimental data.
© The Authors, published by EDP Sciences, 2017
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