CFD/Monte-Carlo neutron transport coupling scheme, application to TRIGA reactor

Peng

Science and Technology of Nuclear Installations

et al. 2021

This paper develops a multi-physics interface code MC-FLUENT to couple the Monte Carlo code OpenMC with the commercial computational fluid dynamics code ANSYS FLUENT. The implementations and parallel performances of block Gauss–Seidel-type and block Jacobi-type Picard iterative algorithms have been investigated. In addition, this paper introduces two adaptive load-balancing algorithms into the neutronics and thermal-hydraulics coupled simulation to reduce the time cost of computation. Considering that the different scalability of OpenMC and FLUENT limits the performance of block Gauss–Seidel algorithm, an adaptive load-balancing algorithm that can increase the number of nodes dynamically is proposed to improve its efficiency. Moreover, with the natural parallelism of block Jacobi algorithm, another adaptive load-balancing algorithm is proposed to improve its performance. A 3 x 3 PWR fuel pin model and a 1000 MWt ABR metallic benchmark core were used to compare the performances of the two algorithms and verify the effectiveness of the two adaptive load-balancing algorithms. The results show that the adaptive load-balancing algorithms proposed in this paper can greatly improve the computing efficiency of block Jacobi algorithm and improve the performance of block Gauss–Seidel algorithm when the number of nodes is large. In addition, the adaptive load-balancing algorithms are especially effective when a case demands different computational power of OpenMC and FLUENT.

Section: Data Exchangementioning

confidence: 99%

An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing

Peng

Science and Technology of Nuclear Installations

et al. 2021

Science and Technology of Nuclear Installations

“…Applications of coupling involving system codes have been used to simulate BWR accidents such as anticipated transient without scram using Simulate-3K/RELAP5 [16] and BWR instability accidents with TRACE/PARCS [17]. Lastly, nuclear applications that involve coupling to computational fluid dynamics codes were performed in [18,19].…”

Section: Introductionmentioning

confidence: 99%

Multiphysics Modeling and Validation of Spent Fuel Isotopics Using Coupled Neutronics/Thermal-Hydraulics Simulations

Price

Radaideh

Mui

et al. 2020

Multiphysics coupling of neutronics/thermal-hydraulics models is essential for accurate modeling of nuclear reactor systems with physics feedback. In this work, SCALE/TRACE coupling is used for neutronic analysis and spent fuel validation of BWR assemblies, which have strong coolant feedback. 3D axial power profiles with coolant feedback are captured in these advanced simulations. The methodology is applied to two BWR assemblies (2F2DN23/SF98 and 2F2D1/F6), discharged from the Fukushima Daini-2 unit. Coupling is performed externally, where the SCALE/T5-DEPL module transfers axial power data in all axial nodes to TRACE, which in turn calculates the coolant density and temperature for each of these nodes. Within a burnup step, the data exchange process is repeated until convergence of all coupling parameters (axial power, coolant density, and coolant temperature) is observed. Analysis of axial power, criticality, and coolant properties at the assembly level is used to verify the coupling process. The 2F2D1/F6 benchmark seems to have insignificant void feedback compared to 2F2DN23/SF98 case, which experiences large power changes during operation. Spent fuel isotopic data are used to validate the coupling methodology, which demonstrated good results for uranium isotopes and satisfactory results for other actinides. This work has a major challenge of lack of documented data to build the coupled models (boundary conditions, control rod history, spatial location in the core, etc.), which encourages more advanced methods to approximate such missing data to achieve better modeling and simulation results.

“…While there are a number of benchmark problems prepared for deterministic codes with non-continuous energy cross sections, e.g., [4,[7][8][9], existing transient benchmarks on the Monte Carlo field are mostly proposed for coupled neutronics/thermal hydraulics calculations, without explicit time dependence and based on a series of static calculations or the improved quasi-static method as in, e.g., [10][11][12]. The need for defining a benchmark problem for time-dependent Monte Carlo simulations without feedback effects has only been recently realized.…”

Section: Introductionmentioning

confidence: 99%

Simulation of a research reactor reactivity transient with deterministic and GPU-assisted Monte Carlo reactor kinetics codes

et al. 2020

Reactor kinetic codes are crucial in safety assessment. Validating spatial and high temporal resolution kinetic solvers without thermal feedback is problematic as measurements seldom involve detailed spatial and fine temporal resolution. Benchmarking of deterministic codes thus often resorts to code-to-code comparison against Monte Carlo codes, which can only recently treat direct time dependence. In this paper, we have attempted to compare results from the GUARDYAN directly time-dependent Monte Carlo code and the SEnTRi transient driver developed for the PARTISN deterministic transport code to low power transient measured at the BME Training Reactor. Code-to-measurement comparisons were successful, despite a major uncertainty in the actual timing of the reactivity insertion and withdrawal originating from the instrumentation of the pneumatic rabbit system. Code-to-code comparisons concluded that time dependence was correctly implemented in both GUARDYAN and SEnTRi; furthermore, a hypothetical scenario was set up involving an instantaneous insertion of a negative reactivity into the BME TR core in order to compare spatially and temporally dependent fluxes. The simulations demonstrated the appearance of higher-order modes, and results showed a relatively good match, although fidelity of the comparison could be further improved by reducing the statistical uncertainty of the results provided by GUARDYAN.