Sensitivity analysis, surrogate modeling, and optimization of pebble-bed reactors considering normal and accident conditions
-
Published:2024-11
Issue:
Volume:428
Page:113466
-
ISSN:0029-5493
-
Container-title:Nuclear Engineering and Design
-
language:en
-
Short-container-title:Nuclear Engineering and Design
Author:
Prince Zachary M.ORCID,
Balestra PaoloORCID,
Ortensi JavierORCID,
Schunert Sebastian,
Calvin OlinORCID,
Hanophy Joshua T.,
Mo KunORCID,
Strydom Gerhard
Reference70 articles.
1. Balestra, P., Schunert, S., Carlsen, R.W., Novak, A.J., DeHart, M.D., Martineau, R.C., 2020. PBMR-400 benchmark solution of exercise 1 and 2 using the MOOSE based applications: MAMMOTH, Pronghorn. In: Proceedings of PHYSOR 2020: Transition to a Scalable Nuclear Future. Cambridge, United Kingdom, p. 06020.
2. Improved Decay Heat Prediction During HTGR Transients Scenarios;Balestra,2022
3. Approximation and learning by greedy algorithms;Barron;Ann. Statist.,2008
4. An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis;Blatman;Probab. Eng. Mech.,2010
5. In-core fuel management optimization of pebble-bed reactors;Boer;Ann. Nucl. Energy,2009