dc.contributor.author | Kumar, Shikhar | |
dc.contributor.author | Liang, Jingang | |
dc.contributor.author | Forget, Benoit Robert Yves | |
dc.contributor.author | Smith, Kord S. | |
dc.date.accessioned | 2017-06-12T16:49:26Z | |
dc.date.available | 2017-06-12T16:49:26Z | |
dc.date.issued | 2016-05 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/109793 | |
dc.description.abstract | Introduction - Advances in computation have brought about significant improvements in creating fast-running high-fidelity simulations of nuclear cores. The BEAVRS benchmark [1] is a highly-detailed PWR specification with two cycles of measured operational data used to validate high-fidelity core analysis methods. This PWR depletion benchmark captures the fine details of the LWR fuel assemblies, burnable absorbers, in-core fission detectors, core loading and shuffling patterns. Specifically, 58 of the 193 assemblies contain in-core detectors with measurements taken over 61 axial positions every month.
These detectors are U-235 fission chambers with slightly varying mass of U-235. The collected signals are normalized on a given assembly permitting full core comparisons. The fuel layout for cycle 1 and instrument tube locations for the reactor are given in figures 1 and 2 respectively. Through a series of data processing and comparisons, it was shown [2] that axially integrated radial maps of reaction rates were in close
agreement between provided detector data and calculated data | en_US |
dc.description.sponsorship | United States. Department of Energy (Nuclear Energy University Program Grant) | en_US |
dc.language.iso | en_US | |
dc.publisher | American Nuclear Society | en_US |
dc.relation.isversionof | www.ans.org/meetings/file/682 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | Prof. Forget via Chris Sherratt | en_US |
dc.title | Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Kumar, Shikhar, Jingang Liang, Benoit Forget and Kord Smith. "Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods." PHYSOR 2016. Unifying Theory and Experiments in the 21st Century (May 1-5, 2016) | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Nuclear Science and Engineering | en_US |
dc.contributor.mitauthor | Kumar, Shikhar | |
dc.contributor.mitauthor | Liang, Jingang | |
dc.contributor.mitauthor | Forget, Benoit Robert Yves | |
dc.contributor.mitauthor | Smith, Kord S. | |
dc.relation.journal | ANS Winter Meeting & Expo. PHYSOR 2016. Unifying Theory and Experiments in the 21st Century | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dspace.orderedauthors | Kumar, Shikhar ; Liang, Jingang ; Forget, Benoit ; Smith, Kord | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-8876-4878 | |
dc.identifier.orcid | https://orcid.org/0000-0003-1459-7672 | |
dc.identifier.orcid | https://orcid.org/0000-0003-2497-4312 | |
mit.license | OPEN_ACCESS_POLICY | en_US |
mit.metadata.status | Complete | |