Extended Applications of Subgrid Representation in the 2D/1D Method. (3rd July 2021)

• Record Type: Journal Article
• Authors: Stimpson, S.; Graham, A.; Collins, B.
• Is Part Of: Nuclear science and engineering. Volume 195:Number 7(2020)
• Page Start: 778
• Page End: 793
• Publication Date: 2021-07-03
• Subjects: Subplane -- subgrid -- 2D/1D method -- MOC, MPACT; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; Nuclear energy; Nuclear engineering; Periodicals; 539.705
• DOI: 10.1080/00295639.2021.1871994
• Languages: English
• ISSNs: 0029-5639

Abstract

Abstract: Recent efforts in MPACT have focused on improving the performance of the 2D/1D subplane implementation to help target computational performance goals. This paper builds on previous efforts that targeted the use of subgrid treatments to improve the accuracy of control rod representation, presenting three additional applications of subgrid treatments with the goal of reducing the computational burden of simulations. These subgrid applications include treatment of spacer grids, thermal feedback, and axial reflector material representation. With these approaches, a single method of characteristics (MOC) plane can contain several different materials axially that are represented explicitly via subgrids on the coarse mesh finite difference (CMFD) mesh but are axially homogenized on the MOC mesh. This allows for a substantial reduction in the number of MOC planes needed in the calculation through the introduction of an approximate treatment, particularly with regard to the self-shielded cross sections and MOC-informed radial current coupling coefficients in CMFD. Several test problems ranging from single rod to quarter core are used to assess the solution accuracy and performance of these various subgrid representations. Overall, the accuracy of the approximations seems very reasonable, with extremely small differences in eigenvalue observed and maximum pin power errors in the 0.5% to 1.0% range. Several cases show substantial value in the compromise between accuracy and computational performance. Others highlight the new computational hurdles that future research will aim to resolve.