Issue |
EPJ Web Conf.
Volume 146, 2017
ND 2016: International Conference on Nuclear Data for Science and Technology
|
|
---|---|---|
Article Number | 02008 | |
Number of page(s) | 6 | |
Section | Evaluation | |
DOI | https://doi.org/10.1051/epjconf/201714602008 | |
Published online | 13 September 2017 |
https://doi.org/10.1051/epjconf/201714602008
Characterization of the energy-dependent uncertainty and correlation in silicon neutron displacement damage metrics
1 Sandia National Laboratories, Albuquerque, USA
2 Paul Scherrer Institut, Villigen, Switzerland
3 International Atomic Energy Agency, Vienna, Austria
a e-mail: uthor@e-mail.org
Published online: 13 September 2017
A rigorous treatment of the uncertainty in the underlying nuclear data on silicon displacement damage metrics is presented. The uncertainty in the cross sections and recoil atom spectra are propagated into the energy-dependent uncertainty contribution in the silicon displacement kerma and damage energy using a Total Monte Carlo treatment. An energy-dependent covariance matrix is used to characterize the resulting uncertainty. A strong correlation between different reaction channels is observed in the high energy neutron contributions to the displacement damage metrics which supports the necessity of using a Monte Carlo based method to address the nonlinear nature of the uncertainty propagation.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.