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7.03: Reactor Physics & Analysis-Monte Carlo Methods
1:45pm - 3:15pm
Session Chair: Mohammad Alrwashdeh, Khalifa University of Science and Technology, United Arab Emirates
Analysis of Statistical Uncertainties in Monte Carlo Functional Expansion Tallies
Bamidele Francis Ebiwonjumi, Hyunsuk Lee, Peng Zhang, Deokjung Lee
Ulsan National Institute of Science and Technology
Functional expansion tallies (FETs) have been investigated as an alternative approach to improve the fidelity of light water reactor (LWR) multi-physics (MP) simulations. Although FETs have been implemented in some Monte Carlo (MC) codes, the statistical properties have not been studied for use in core neutronics analysis. This work examines the convergence and statistical properties of FETs used in a two-dimensional (2D) and three-dimensional (3D) LWR fuel pin and compares the sample, apparent and real standard deviation (STD) of mesh-based volume-integrated power FET with those of the histogram-based tallies. Inter-cycle correlation, autocorrelation coefficients (ACC), convergence rate, and sensitivity of the FET statistical uncertainty to the expansion order, size and number of tally regions are investigated. We show that for the 2D pin, the real STD of the Zernike-based radial power FET is lower compared to the zeroth-order tally (offering a kind of variance reduction). The inter-cycle correlation is low at all lags and negative for the high order coefficients. For the Legendre FET of axial power in the 3D pin, the coefficients have high inter-cycle correlation at lag 1. In addition, the real variance is underestimated. However, variance reduction can also be achieved depending on the size of the tally region.
Comparison of nodal and Monte Carlo approaches for BWR full core simulations
Anna Detkina1, Seddon Atkinson1, Dzianis Litskevich1, Bruno Merk1,2
1The University of Liverpool; 2National Nuclear Laboratory
Currently, steady state or transient operations of the reactor core are widely modelled using coupled nodal codes. Despite having been approved by regulatory bodies for decades, this approach has some disadvantages. The main concern is that nodal codes are unable to provide the correct pin power distribution, which required placing two additional safety margins. One related to the unknown maximal burnup of the fuel assembly and one with regards to knowledge of the pin temperature. This safety margins are large in estimation due to lack of knowledge of the exact pin power. High-fidelity approaches of full core simulations such as Monte Carlo can explicitly model each fuel pin and thus provide with accurate pin power distributions when coupled to detailed fluid dynamic tools. However, this method is computationally expensive.
The goal of the current research is to compare two approaches, nodal and Monte Carlo, and assess their limitations in application to BWRs. Nodal method was performed using Polaris/DYN3D sequence, while Monte Carlo method, using Serpent/CTF coupling.
This paper covers comparison of the two approaches for single BWR 10x10 fuel assembly with and without thermal-hydraulic feedback effect. Fuel assembly model is based on a patent registered by Global Nuclear Fuel-Americas in 2014. Assemblies are constructed from the set of different fuel pins which enrichment and gadolinia content varies as the height of the assembly.
Infinite multiplication factors over burnup were compared in Polaris and Serpent for 2D BWR assembly models to estimate the difference between codes for cross-section preparation. Neutronics and thermal-hydraulic parameters such as axial power distribution, coolant density and fuel temperature, were compared for the full 3D BWR assembly model in Polaris/DYN3D and Serpent/CTF. At the final stage, effective multiplication factor over burnup was estimated for the 3D BWR fuel assembly model in both sequences.
Initial verification of the CCCPO neutron transport solver for multiscale LWR reactor simulations
Dzianis Litskevich, Seddon Atkinson, Sebastian Davies, Anna Detkina
The University of Liverpool
The operation of nuclear reactors requires detailed knowledge of important safety parameters, such as the spatial power distribution, pin powers etc. Full core pin-by-pin coupled neutronic and thermal-hydraulics simulations are very computationally expensive even for the modern clusters.
Therefore, the industry-standard approach uses a coupled neutronic and thermal-hydraulics simulation. In these codes, the neutronic calculations are performed at a nodal level using the diffusion approximation and assembly-homogenized cross-sections sets while the thermal-hydraulics relies on a channel model. However, for determining safety limits, the knowledge of the power and temperature distribution on a nodal level is not sufficient.
Within this work, multiscale and multiphysics methods can be used to resolve the power distribution within the zones of interest. Pin-wise calculations, in this case, are performed by applying a transport solver using the heterogeneous fuel assembly geometry with boundary conditions extracted from the nodal diffusion solution. This approach allows us to obtain power distribution on the pin-level and perform coupled multiphysics simulations keeping the simulation time within reasonable limits.
To follow this strategy, a transport solver is required which can be used for the heterogeneous flux reconstruction. Current coupling collision probability (CCCP) method seems to be a good choice for the development of such a solver. In this study, initial verification of the developed transport solver utilising CCCP method with orthogonal flux expansion (CCCPO) is tested and verified via comparison with the results of Monte Carlo and deterministic codes. The expansion of the flux by orthogonal polynomials avoids discretisation of the calculation regions. The results of the calculations demonstrate good agreement with the results of Monte Carlo calculations. The comparison of the new solver with the flat flux approximation demonstrates either an improved quality of the result for identical cell discretisation or significantly increased computational efficiency to achieve an identical solution.