On data assimilation with Monte-Carlo-calculated and statistically uncertain sensitivity coefficients

International audienceSensitivity coefficients from Monte Carlo neutron transport codes have uncertainties that can affect nuclear data adjustments with integral experiments. This paper presents an extended version of Generalized Linear Least Squares (GLLS), called xGLLS, that accounts for these uncertainties. With very large sensitivity uncertainties, xGLLS constrains the nuclear data adjustments so that the posterior biases and uncertainties are larger than with GLLS. However, for the range of sensitivity uncertainties realistically encountered, xGLLS does not produce adjustments different from GLLS. This indicates that sensitivity uncertainties are not important compared to experimental, modeling, methodological, and nuclear data uncertainties. To balance a simulation’s accuracy with its computational cost, we recommend stopping a simulation once the uncertainty of a calculated integral parameter, caused by modeling and methodologies and by the sensitivities, is an order of magnitude smaller than that caused by nuclear data

Methods and Models for the Coupled Neutronics and Thermal-Hydraulics Analysis of the CROCUS Reactor at EFPL

In order to analyze the steady state and transient behavior of the CROCUS reactor, several methods and models need to be developed in the areas of reactor physics, thermal-hydraulics, and multiphysics coupling. The long-term objectives of this project are to work towards the development of a modern method for the safety analysis of research reactors and to update the Final Safety Analysis Report of the CROCUS reactor. A first part of the paper deals with generation of a core simulator nuclear data library for the CROCUS reactor using the Serpent 2 Monte Carlo code and also with reactor core modeling using the PARCS code. PARCS eigenvalue, radial power distribution, and control rod reactivity worth results were benchmarked against Serpent 2 full-core model results. Using the Serpent 2 model as reference, PARCS eigenvalue predictions were within 240 pcm, radial power was within 3% in the central region of the core, and control rod reactivity worth was within 2%. A second part reviews the current methodology used for the safety analysis of the CROCUS reactor and presents the envisioned approach for the multiphysics modeling of the reactor

Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

Developments in data assimilation theory allow to adjust integral parameters and cross sections with stochastic sampling. This work investigates how two stochastic methods, MOCABA and BMC, perform relative to a sensitivity-based methodology called GLLS. Stochastic data assimilation can treat integral parameters that behave non-linearly with respect to nuclear data perturbations, which would be an advantage over GLLS. Additionally, BMC is compatible with integral parameters and nuclear data that have non-Gaussian distributions. In this work, MOCABA and BMC are compared to GLLS for a simple test case: JEZEBEL-Pu239 simulated with Serpent2. The three methods show good agreement between the mean values and uncertainties of their posterior calculated values and nuclear data. The observed discrepancies are not statistically significant with a sample size of 10000. BMC posterior calculated values and nuclear data have larger uncertainties than MOCABA's at equivalent sample sizes