Uncertainty and sensitivity analysis of PWR mini-core transients in the presence of nuclear data uncertainty using non-parametric tolerance limits-Reference-Cited by-同舟云学术

Uncertainty and sensitivity analysis of PWR mini-core transients in the presence of nuclear data uncertainty using non-parametric tolerance limits

Published:2020-03 Issue: Volume:137 Page:107146
ISSN:0306-4549
Container-title:Annals of Nuclear Energy
language:en
Short-container-title:Annals of Nuclear Energy

Author:

Aures A.,Berner N.,Pautz A.,Zwermann W.

Funder

German Federal Ministry for Economic Affairs and Energy

Publisher

Elsevier BV

Subject

Nuclear Energy and Engineering

Reference23 articles.

1. Sensitivity indices for nuclear data uncertainty analysis with XSUSA and TSUNAMI;Bostelmann,2018

2. Ivanov, K., Avramova, M., Kamerow, S., Kodeli, I., Sartori, E., Ivanov, E., Cabellos, O., 2016. Benchmark for Uncertainty Analysis in Modelling (UAM) for Design, Operation and Safety Analysis of LWRs. Volume I: Specification and Support Data for the Neutronics Cases (Phase I), Version 2.1, NEA/NSC/DOC(2012) 10.

3. Reactor simulations with nuclear data uncertainties;Aures,2018

4. Validation of PSI best estimate plus uncertainty methodology against SPERT-III reactivity initiated accident experiments;Dokhane;Ann. Nucl. Energy,2018

5. Benchmark for uncertainty analysis in modelling (UAM) for design;Hou,2014

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Demonstration of a random sampling approach to uncertainty propagation for generic pebble-bed fluoride-salt-cooled high temperature reactor (gFHR);Nuclear Engineering and Design;2022-08

2. HELIOS-2/XSUSA sensitivity and uncertainty analyses with ENDF/B-VII.1 covariance data;Annals of Nuclear Energy;2022-03

3. Extension of SCALE/Sampler’s sensitivity analysis;Annals of Nuclear Energy;2022-01

4. Overview of the Tolerance Limit Calculations with Application to TSURFER;Energies;2021-10-29

5. Sensitivity and uncertainty analysis for the UAM-SFR sub-exercises with linear regression from random sampling;Annals of Nuclear Energy;2020-12