A Statistical Methodology for Determination of Safety Systems Actuation Setpoints Based on Extreme Value Statistics

This paper provides a novel and robust methodology for determination of nuclear reactor trip setpoints which accounts for uncertainties in input parameters and models, as well as accounting for the variations in operating states that periodically occur. Further it demonstrates that in performing best estimate and uncertainty calculations, it is critical to consider the impact of all fuel channels and instrumentation in the integration of these uncertainties in setpoint determination. This methodology is based on the concept of a true trip setpoint, which is the reactor setpoint that would be required in an ideal situation where all key inputs and plant responses were known, such that during the accident sequence a reactor shutdown will occur which just prevents the acceptance criteria from being exceeded. Since this true value cannot be established, the uncertainties in plant simulations and plant measurements as well as operational variations which lead to time changes in the true value of initial conditions must be considered. This paper presents the general concept used to determine the actuation setpoints considering the uncertainties and changes in initial conditions, and allowing for safety systems instrumentation redundancy. The results demonstrate unique statistical behavior with respect to both fuel and instrumentation uncertainties which has not previously been investigated

Cross-Section covariance propagation for LWR FUEL cells in one and two dimensions

Within the framework of the Uncertainty Analysis in Modeling (UAM) for Design, Operation and Safety Analysis of LWRs Benchmark sponsored by the OECD/NEA, a tool has been developed for the propagation of covariance uncertainty through resonance self-shielding and other neutron kinetics calculations using a direct, cross-section generation and substitution approach. The motivation behind the work described in this paper was to develop a portable uncertainty propagation tool that could be easily implemented with several neutron kinetics codes, without relying on detailed knowledge of the internal workings of those codes or access to adjoint solutions. Implemented initially with the SCALE code package, “self-shielded” covariance matrices for common LWR fuel cells have been calculated, as well as contributions to Keff uncertainty by selected neutron cross-sections and processes in both one and two dimensions. The one dimensional results generated by the tool are compared against those obtained using the TSUNAMI-1D module of SCALE in order to verify the efficacy of the methodology. Onedimensional results show good agreement with TSUNAMI-1D, but there is also an indication that the loss of dimensionality corresponding to one-dimensional equivalent geometries of twodimensional fuel cells may lead to significant changes in the calculated uncertainty on Keff arising from particular neutron-nuclide reactions

The Dilution Dependency of Multigroup Uncertainties

The propagation of nuclear data uncertainties through reactor physics calculation has received attention through the Organization for Economic Cooperation and Development—Nuclear Energy Agency’s Uncertainty Analysis in Modelling (UAM) benchmark. A common strategy for performing lattice physics uncertainty analysis involves starting with nuclear data and covariance matrix which is typically available at infinite dilution. To describe the uncertainty of all multigroup physics parameters—including those at finite dilution—additional calculations must be performed that relate uncertainties in an infinite dilution cross-section to those at the problem dilution. Two potential methods for propagating dilution-related uncertainties were studied in this work. The first assumed a correlation between continuous-energy and multigroup cross-sectional data and uncertainties, which is convenient for direct implementation in lattice physics codes. The second is based on a more rigorous approach involving the Monte Carlo sampling of resonance parameters in evaluated nuclear data using the TALYS software. When applied to a light water fuel cell, the two approaches show significant differences, indicating that the assumption of the first method did not capture the complexity of physics parameter data uncertainties. It was found that the covariance of problem-dilution multigroup parameters for selected neutron cross-sections can vary significantly from their infinite-dilution counterparts

A blind, numerical Benchmark Study on Supercritical Water Heat Transfer Experiments in a 7-Rod Bundle

Heat transfer in supercritical water reactors (SCWR) shows a complex behavior, especially when the temperatures of the water are near the pseudo-critical value. For example, a significant deterioration of heat transfer may occur, resulting in unacceptably high cladding temperatures. The underlying physics and thermodynamics behind this behavior is not well understood yet. To assist the worldwide development in SCWRs, it is therefore of paramount importance to assess the limits and capabilities of currently available models, despite the fact that most of these models were not meant to describe supercritical heat transfer. For this reason, the Gen-IV International Forum initiated the present blind, numerical benchmark, primarily aiming to show the predictive ability of currently available models when applied to a real-life application with flow conditions that resemble those of an SCWR. This paper describes the outcomes of ten independent numerical investigations and their comparison with wall temperatures measured at different positions in a seven-rod bundle with spacer grids in a supercritical water test facility at JAEA. The wall temperatures were not known beforehand to guarantee the blindness of the study. A number of models have been used, ranging from a 1D, analytical approach with heat transfer correlations to a RANS simulation with the SST turbulence model on a mesh consisting of 62 million cells. None of the numerical simulations accurately predicted the wall temperature for the test case in which deterioration of heat transfer occurred. Furthermore, the predictive capabilities of the subchannel analysis were found to be comparable to those of more laborious approaches. It has been concluded that predictions of supercritical heat transfer in rod bundles with the help of currently available numerical tools and models should be treated with caution