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On the transient models of the VITAS code: applications to the C5G7-TD pin-resolved benchmark problem

This article describes the transient models of the neutronics code VITAS that are used for solving time-dependent, pin-resolved neutron transport equations. VITAS uses the stiffness confinement method (SCM) for temporal discretization to transform the transient equation into the corresponding transi...

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Bibliographic Details
Published in:Nuclear science and techniques 2023-02, Vol.34 (2), p.28-57, Article 20
Main Authors: Xiao, Wei, Yin, Han, Liu, Xiao-Jing, He, Hui, Zhang, Teng-Fei
Format: Article
Language:English
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Summary:This article describes the transient models of the neutronics code VITAS that are used for solving time-dependent, pin-resolved neutron transport equations. VITAS uses the stiffness confinement method (SCM) for temporal discretization to transform the transient equation into the corresponding transient eigenvalue problem (TEVP). To solve the pin-resolved TEVP, VITAS uses a heterogeneous variational nodal method (VNM). The spatial flux is approximated at each Cartesian node using finite elements in the x - y plane and orthogonal polynomials along the z -axis. Angular discretization utilizes the even-parity integral approach at the nodes and spherical harmonic expansions at the interfaces. To further lower the computational cost, a predictor–corrector quasi-static SCM (PCQ-SCM) was developed. Within the VNM framework, computational models for the adjoint neutron flux and kinetic parameters are presented. The direct-SCM and PCQ-SCM were implemented in VITAS and verified using the two-dimensional (2D) and three-dimensional (3D) exercises on the OECD/NEA C5G7-TD benchmark. In the 2D and 3D problems, the discrepancy between the direct-SCM solver’s results and those reported by MPACT and PANDAS-MOC was under 0.97% and 1.57%, respectively. In addition, numerical studies comparing the PCQ-SCM solver to the direct-SCM solver demonstrated that the PCQ-SCM enabled substantially larger time steps, thereby reducing the computational cost 100-fold, without compromising numerical accuracy.
ISSN:1001-8042
2210-3147
DOI:10.1007/s41365-023-01170-x