Improved block-Jacobi parallel algorithm for the SN nodal method with unstructured mesh. (March 2021)

• Record Type: Journal Article
• Authors: Qiao, Liang; Zheng, Youqi; Wu, Hongchun; Wang, Yongping; Du, Xianan
• Is Part Of: Progress in nuclear energy. Volume 133(2021)
• Publication Date: 2021-03
• Subjects: Parallel calculation -- SN method -- Unstructured mesh -- Block-Jacobi parallel algorithm; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 333.7924
• DOI: 10.1016/j.pnucene.2021.103629
• Languages: English
• ISSNs: 0149-1970

Abstract

Abstract: The substantial time required for solving the neutron transport equation can be reduced through parallel calculation. The block-Jacobi algorithm is a common method for parallel neutron transport calculation in an unstructured mesh; however, iteration degradation is an inevitable problem that limits the application of this algorithm by reducing the parallel efficiency. In this study, we applied the block-Jacobi algorithm to the S N nodal method with a triangular-z mesh and proposed an improvement to achieve high parallel efficiency. The interface prediction (IP) method was developed to prevent iteration degradation. This method is based on extrapolating the interface information instead of using the information from the preceding iteration at the interfaces in sub-domains. Meanwhile, the prediction was used recursively to accelerate the self-group scattering source iteration in the entire space; this process is referred to as the inner iteration prediction method (IIP). These two methods effectively prevent iteration degradation and reduce time required for self-group scattering source iteration. A more stable and improved parallel performance was thus achieved. Graphical abstract: Image 1 Highlights: Block-Jacobi parallel algorithm was applied in S N nodal transport solver with unstructured mesh. Iteration degradation of Block-Jacobi parallel algorithm was mitigated by predicting the fluxes at interfaces of subdomains. In inner group scattering source iteration, the prediction can be used to reduced the number of iterations.