Thermal neutron scattering evaluation framework
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 implementat...
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2017-01-01
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Series: | EPJ Web of Conferences |
Online Access: | https://doi.org/10.1051/epjconf/201714613007 |
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doaj-9095a9ff418a468f8ede14c4eedff5362021-08-02T10:20:26ZengEDP SciencesEPJ Web of Conferences2100-014X2017-01-011461300710.1051/epjconf/201714613007epjconf-nd2016_13007Thermal neutron scattering evaluation frameworkChapman Chris0Leal Luiz1Rahnema Farzad2Danon Yaron3Arbanas Goran4Georgia Inst Technol, 770 State St NW, Room 3-39SPSN-EXP/SNC/LNR, IRSNGeorgia Inst Technol, 770 State St NW, Room 3-39SRensselaer Polytech Inst, Gaerttner LINAC CtrOak Ridge Natl Lab, Reactor & Nucl Syst DivA 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.https://doi.org/10.1051/epjconf/201714613007 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chapman Chris Leal Luiz Rahnema Farzad Danon Yaron Arbanas Goran |
spellingShingle |
Chapman Chris Leal Luiz Rahnema Farzad Danon Yaron Arbanas Goran Thermal neutron scattering evaluation framework EPJ Web of Conferences |
author_facet |
Chapman Chris Leal Luiz Rahnema Farzad Danon Yaron Arbanas Goran |
author_sort |
Chapman Chris |
title |
Thermal neutron scattering evaluation framework |
title_short |
Thermal neutron scattering evaluation framework |
title_full |
Thermal neutron scattering evaluation framework |
title_fullStr |
Thermal neutron scattering evaluation framework |
title_full_unstemmed |
Thermal neutron scattering evaluation framework |
title_sort |
thermal neutron scattering evaluation framework |
publisher |
EDP Sciences |
series |
EPJ Web of Conferences |
issn |
2100-014X |
publishDate |
2017-01-01 |
description |
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. |
url |
https://doi.org/10.1051/epjconf/201714613007 |
work_keys_str_mv |
AT chapmanchris thermalneutronscatteringevaluationframework AT lealluiz thermalneutronscatteringevaluationframework AT rahnemafarzad thermalneutronscatteringevaluationframework AT danonyaron thermalneutronscatteringevaluationframework AT arbanasgoran thermalneutronscatteringevaluationframework |
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1721234023827636224 |