Versatility and stabilization improvements of full core neutronics/thermal-hydraulics coupling between RMC and CTF

Abstract This paper presents the versatility and stabilization improvements of high fidelity multi-physics coupling of neutronics and thermal-hydraulics. The coupling is accomplished between the Monte Carlo code RMC and the sub-channel code CTF. Target motion sampling method of RMC and the domain decomposition parallel strategy of CTF are used to decrease the memory requirement as well as to improve the calculation efficiency. The hybrid coupling method is adopted in coupled RMC/CTF code, in which CTF is invoked by RMC flexibly. For code versatility and stabilization, the HDF5 (hierarchical data format) file is used to replace text files in data transfer between two coupled codes, and the predictor-corrector method is also proposed to stabilize the coupling. The coupled code is validated as versatile by successfully testing two full-core problems with different scales. The BEAVRS full core calculation results show the efficiency improvement as a result of using the HDF5 file in the versatile coupled code, and the predictor-corrector method used in the simulation is demonstrated to be effective for stabilizing and accelerating the coupling convergence. Moreover, a modified PWR full core problem simulation indicates that the coupling between neutronics and thermal-hydraulic influences the power distribution both radially and axially, because of the Doppler broadening effect and coolant properties feedback.

[1]  J. F. Briesmeister.  MCNP-A General Monte Carlo N-Particle Transport Code , 1993 .

[2]  Kan Wang,et al.  Asymptotic Wielandt Method and Superhistory Method for Source Convergence in Monte Carlo Criticality Calculation , 2012 .

[3]  John S. Hendricks,et al.  Initial MCNP6 Release Overview , 2012 .

[4]  Kan Wang,et al.  Development of on-the-fly temperature-dependent cross-sections treatment in RMC code , 2016 .

[5]  Kan Wang,et al.  Coupled neutronics/thermal-hydraulics analysis of a full PWR core using RMC and CTF , 2017 .

[6]  Kostadin Ivanov,et al.  Coupled MCNP6/CTF code: Development, testing, and application , 2016 .

[7]  Kan Wang,et al.  Reaction rate tally and depletion calculation with on-the-fly temperature treatment , 2016 .

[8]  Daniele Marchisio,et al.  Implementation of the Quadrature Method of Moments in CFD codes for aggregation-breakage problems , 2003 .

[9]  Muhammad Aslam Noor,et al.  A predictor-corrector algorithm for general variational inequalities , 2001, Appl. Math. Lett..

[10]  R. Salko,et al.  Optimization and parallelization of the thermal–hydraulic subchannel code CTF for high-fidelity multi-physics applications , 2015 .

[11]  Paul K. Romano,et al.  Development of burnup methods and capabilities in Monte Carlo code RMC , 2013 .

[12]  Haomin Yuan,et al.  Coupling of RMC and CFX for analysis of Pebble Bed-Advanced High Temperature Reactor core , 2012 .

[13]  Yishu Qiu,et al.  RMC – A Monte Carlo code for reactor core analysis , 2015 .