Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6758876 | Nuclear Engineering and Design | 2018 | 16 Pages |
Abstract
Uncertainty quantification (UQ) and sensitivity analyses (SA) are performed for coupled simulations between VERA-CS, a coupled pin resolved neutron transport and subchannel thermal hydraulics code, and the fuel performance code BISON. The interface between VERA-CS and BISON is performed in a multiphysics environment known as the LOCA Toolkit for U.S. light water reactors (LOTUS) currently under development at Idaho National Laboratory (INL). A focus is placed on using a variety of SA measures, including two regression based (Pearson and Spearman), one variance based (Sobol indices), and three moment independent measures (Delta moment independent measures with L1, L2, and Lâ norms). The problem under inspection is a single assembly depletion case for three fuel cycles. The figures of merit are the minimum departure from nucleate boiling ratio (MDNBR), maximum fuel centerline temperature (MFCT), and gap conductance at peak power (GCPP). SA results show MDNBR to be linear with consistent rankings throughout the fuel cycles. MFCT is linear, but with a change in rankings at the switch from open gap to closed gap models. GCPP is nonlinear at intermediate states that coincide with the onset of contact between fuel and cladding. These nonlinear states allow for the showcasing of higher order SA measures over first order methods.
Keywords
MCNPConsortium for Advanced Simulation of Light Water ReactorsMPACTBEPUMonte Carlo N-particleCOBRA-TFReactivity insertion accidentORNLVERA-CSMDNBRPWRCASLINLHPCRIAFOMLocacIPSOak Ridge National LaboratoryIdaho National LaboratoryRisk assessmentLoss of coolant accidentBest estimate plus uncertaintyBisonSensitivity analysisPressurized Water ReactorNodal expansion methodProbability distribution functionLOTUSFigure of meritNEMPdfUncertainty quantificationMoose
Related Topics
Physical Sciences and Engineering
Energy
Energy Engineering and Power Technology
Authors
Cole Blakely, Hongbin Zhang, Charlie Folsom, Heng Ban, Ronaldo Szilard,