MPACT Development Activities at University of Michigan

Technical Report · Fri Sep 29 00:00:00 EDT 2017

DOI:https://doi.org/10.2172/3004268· OSTI ID:3004268

Kochunas, Brendan ^[1]; Dodson, Zack ^[1]; Fitzgerald, Andrew ^[1]; Jarrett, Mike ^[1]; Yee, Ben ^[1]; Stimpson, Shane G. ^[2]

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1. Univ. of Michigan, Ann Arbor, MI (United States)
2. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

This report documents the efforts of general development tasks in MPACT performed primarily at the University of Michigan during FY17. These tasks included: 1. Unstructured CMFD - The unstructured CMFD supports the RIA and BWR challenge problems. It allows MPACT to simulate mixed lattice cores (e.g. 8x8 next to 9x9). This design feature is common to operating BWRs and also the SPERT experiments being used to validate VERA-CS for RIA. 2. Higher order spatial sources for MOC - The higher order sources are for improving the overall performance of MPACT. Higher order spatial sources in MOC provide accurate solutions with potentially significantly fewer mesh regions, thus speeding up every calculation. This method is also particularly important for BWRs. 3. Improving fine source region visualization - The improvement of the visualization of the flat source region mesh in MPACT is to support users and communication of models and results from MPACT. VERAView provides visualization of pin-wise information, however MPACT resolves the spatial solution to intra pin level. The capability provided here will let users visualize the full model geometry and components of the solution at the highest spatial resolution available from MPACT. 4. Automated spatial decomposition - The automated spatial decomposition removes the burden from the user to know how to spatially decompose the model for MPACT; a task that has been rather tricky in the past. Instead the user may give some number of processors that is a multiple of the axial mesh and MPACT will determine a nearly optimal decomposition that gives better load balance than most decompositions used currently. 5. Optimal relaxation factors for feedback - The development of optimal relaxation factor is to improve the stability and robustness of problems with feedback. Presently the default feedback values are 0.5, which may or may not be optimal. Without relaxation the fixed point iteration that is currently used is known to be unstable for large problems. The optimal relaxation factors are derived by utilizing a previous Fourier analysis. From the original milestone there was a scope change where the work on the Intel MIC was deferred for work on the automated spatial decomposition.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Nuclear Energy (NE)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 3004268
• Report Number(s): CASL-U--2017-1423-000
• Country of Publication: United States
• Language: English

Related Subjects

22 GENERAL STUDIES OF NUCLEAR REACTORS
97 MATHEMATICS AND COMPUTING