CRANE: A new SCALE super-sequence for neutron transport calculations

Congjian Wang, Hany S. Abdel-Khalik, Ugur Mertyurek

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A new "super-sequence" called CRANE has been developed to automate the application of reduced order modeling (ROM) to reactor analysis calculations under the SCALE code environment. This new super-sequence is designed to support computationally intensive analyses that require repeated execution of flux solvers with variations in design parameters and nuclear data. This manuscript provides a brief overview of CRANE and demonstrates its applications to representative reactor physics calculations. Specifically, two ROM applications are demonstrated, the intersection subspace-based approach for uncertainty quantification which is intended to reduce the number of uncertainty sources in a conventional uncertainty analysis, and the exact-to-precision generalized perturbation theory methodology intended as a physics-based surrogate model to replace the flux solver, i.e., NEWT. Our overarching goal is to provide a prototypic ROM capability that allows users to further explore and investigate the benefits of using ROM methods in their respective domain and help guide further developments of the methodology and evolution of the tools.

Original languageEnglish
Title of host publication5th Topical Meeting on Advances in Nuclear Fuel Management, ANFM 2015
Subtitle of host publicationAdvances in Nuclear Fuel Management V
PublisherAmerican Nuclear Society
Pages452-462
Number of pages11
ISBN (Electronic)9781510808034
StatePublished - 2015
Event5th Topical Meeting on Advances in Nuclear Fuel Management, ANFM 2015 - Hilton Head, United States
Duration: Mar 29 2015Apr 1 2015

Publication series

Name5th Topical Meeting on Advances in Nuclear Fuel Management, ANFM 2015: Advances in Nuclear Fuel Management V

Conference

Conference5th Topical Meeting on Advances in Nuclear Fuel Management, ANFM 2015
Country/TerritoryUnited States
CityHilton Head
Period03/29/1504/1/15

Keywords

  • EpGPT
  • Intersection subspace method
  • Reduced order modeling

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