Abstract
The Advanced Multilevel Predictor-Corrector Quasi-static Method (AML-PCQM) is proposed in this work. The four computational levels, including transport, Multi-Group (MG) Coarse Mesh Finite Difference (CMFD), One-Group (1G) CMFD, and Exact Point-Kinetics Equation (EPKE), are coupled with a new dynamic iteration strategy. In each coupling algorithm, the original Transient Fixed Source Problem (TFSP) is solved in the predictor process using coarse time step, and then the flux distribution is factorized to the functions of amplitude and shape in the next corrector process. Finally, multiple fine time steps are used to adjust the predicted solution. Two heterogeneous single assembly problems with the prompt control rod withdrawal event are used to verify the AML-PCQM scheme’s accuracy and efficiency. The numerical results obtained by different cases are compared and analyzed. The final results indicate that the AML-PCQM performs the remarkable advantages of efficiency and accuracy with the reference cases.
Highlights
Since the high-performance computing clusters have significant advances recently, the state-of-theart computer simulation for nuclear reactors is three-dimensional (3D) whole-core time-dependent modeling with high-fidelity pin-resolved features
A new multilevel predictor-corrector quasi-static method for pinresolved neutron kinetics simulation named AML-Predictor-Corrector Quasi-static Method (PCQM) is proposed to implement a scheme in the HNET code
The initial Transient Fixed Source Problem (TFSP) is solved using a coarse time step in the predictor process, and the flux distribution is factorized to the amplitude and shape functions in the subsequent corrector process, where the predicted solution is rectified using numerous fine time steps
Summary
Since the high-performance computing clusters have significant advances recently, the state-of-theart computer simulation for nuclear reactors is three-dimensional (3D) whole-core time-dependent modeling with high-fidelity pin-resolved features. A significant challenge of the dramatically computational cost has happened to the direct simulation utilizing conventional 3D neutron transport techniques, the 3D complete nuclear reactor core. The real total number of numerical unknowns for a typical reactor core is much too large, approaching 1015 for steady-state simulation but significantly more for time-dependent simulation (Collins et al, 2016). The 2D/1D scheme has been successful in actual reactor applications in those
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