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Massachusetts Institute of Technology

Quantifying time-dependent uncertainty in the BEAVRS benchmark using time series analysis

Abstract

dc:description.abstract

Advances in computational capabilities have enabled the development of high-fidelity methods for large-scale modeling of nuclear reactors. However, such techniques require proper benchmarking and validation to ensure correct and consistent modeling of real problems. Thus, the BEAVRS benchmark was developed to legitimize the advancements of new 3-D full-core algorithms in the field of reactor physics. However, in order to address the issue of BEAVRS uncertainty quantification (UQ) of Uranium-235 fission reaction rate data, this thesis proposes a new method for measuring uncertainty that goes beyond merely conducting statistical analysis of multiple measurements at one given point in time. Instead, this work hinges on principles of time series analysis and develops a rigorous method for quantifying the uncertainty in using "tilt-corrected" data in an attempt to evaluate time-dependent uncertainty. Such efforts show consistent results across the four dierent methods and will ultimately assist in demonstrating that BEAVRS is a non-proprietary international benchmark for the validation of high-fidelity tools.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kumar, Shikhar, S.M. Massachusetts Institute of Technology
Advisor dc:contributor.advisor
  • Benoit Forget and Kord Smith.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/119052
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/119052

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kumar, Shikhar, S.M. Massachusetts Institute of Technology. Quantifying time-dependent uncertainty in the BEAVRS benchmark using time series analysis. Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119052