Data assimilation of post-irradiation examination data for fission yields from GEF

Nuclear data, especially fission yields, create uncertainties in the predicted concentrations of fission products in spent fuel which can exceed engineering target accuracies. Herein, we present a new framework that extends data assimilation methods to burnup simulations by using post-irradiation examination experiments. The adjusted fission yields lowered the bias and reduced the uncertainty of the simulations. Our approach adjusts the model parameters of the code GEF. We compare the BFMC and MOCABA approaches to data assimilation, focusing especially on the effects of the non-normality of GEF's fission yields. In the application that we present, the best data assimilation framework decreased the average bias of the simulations from 26% to 14%. The average relative standard deviation decreased from 21% to 14%. The GEF fission yields after data assimilation agreed better with those in JEFF3.3. For Pu-239 thermal fission, the average relative difference from JEFF3.3 was 16% before data assimilation and after it was 12%. For the standard deviations of the fission yields, GEF's were 100% larger than JEFF3.3's before data assimilation and after were only 4% larger. The inconsistency of the integral data had an important effect on MOCABA, as shown with the Marginal Likelihood Optimization method. When the method was not applied, MOCABA's adjusted fission yields worsened the bias of the simulations by 30%. BFMC showed that it inherently accounted for this inconsistency. Applying Marginal Likelihood Optimization with BFMC gave a 2% lower bias compared to not applying it, but the results were more poorly converged.

Data assimilation of post irradiation examination experiments to adjust fission yields

Mathieu Hursin, Andreas Pautz, Daniel Jerôme Siefman

Nuclear data, especially fission yields, create uncertainties in the predicted concentrations of fission products in spent fuel. Herein, we present a new framework that extends data assimilation methods to burnup simulations by using data from post-irradiation examination experiments. The adjusted fission yields improve the bias and reduce the uncertainty of predicted fission product concentrations in spent fuel. Our approach modifies fission yields by adjusting the model parameters of the code GEF with post-irradiation examination experiments. We used the BFMC data assimilation method to account for the non-normality of GEF's fission yields. In the application that we present, the assimilation decreased the average bias of the predicted fission product concentrations from 26% to 15%. The average relative standard deviation decreased from 21% to 14%. The GEF fission yields after data assimilation agreed better with those in ENDF/B-VIII.O. For Pu-239 thermal fission, the average relative difference from ENDF/B-VIII.0 was 16% before data assimilation and 11% after. For the standard deviations of the fission yields, GEF's were, on average, 16% larger than those from ENDF/B-VIII.0 before data assimilation and 15% smaller after.

E D P SCIENCES2020

Development and Application of Data Assimilation Methods in Reactor Physics

Daniel Jerôme Siefman

Simulations of nuclear reactor physics can disagree significantly from experimental evidence, even when the most accurate models are used. An important part of this bias from experiment is caused by nuclear data. The nuclear data have inherent uncertainties due to the way they are evaluated, which then propagate to nuclear reactor simulations. This creates a bias and an uncertainty in a predicted reactor parameter like \keff~or the composition of spent fuel. This thesis focuses on data assimilation techniques to ameliorate the effects of nuclear data. Data assimilation takes integral experiments and assimilates them in a Bayesian way to improve simulations. It can also be used to find trends and areas needing improvement in evaluated nuclear data. The research focuses on advancing the data assimilation theory and knowledge used in reactor physics, especially on techniques that require stochastic sampling of the nuclear data. Furthermore, the research takes advantage of rich experimental data available from the Proteus research reactor at the Paul Scherrer Institute. The thesis showed, for the first time, that two methods based on stochastic sampling (called MOCABA and BMC) gave equivalent results to each other and to the traditional method called GLLS. This was corroborated with two independent studies that used different experiments, neutron transport codes, nuclear data, and processing codes. The first study used the JEZEBEL-Pu239 benchmark, the Serpent2 neutron transport code, and NUSS. The second study used reactivity experiments from the LWR-Phase II experiments at Proteus, CASMO-5 for neutron transport, and SHARK-X. While using Serpent2, several questions pertaining to the stochastic uncertainty of its sensitivity coefficients arose. To address these, a new method called eXtended GLLS, or xGLLS, was proposed and tested in the thesis. xGLLS showed that the uncertainties associated with sensitivity coefficients have a negligible effect on the data assimilation as long as the calculated integral parameters themselves were converged. The final study focused on adjusting the fission yields and covariances made by the GEF code with post-irradiation examination experiments from Proteus. The adjustment improved the accuracy of predicted nuclide concentrations in spent fuel and improved the agreement between the GEF fission yields and those of ENDF/B-VIII.0 and JEFF3.3.

EPFL2019

Fission Rates Measured Using High-Energy Gamma-Rays from Short Half-Life Fission Products in Fresh and Spent Nuclear Fuel

Hanna Kröhnert

In recent years, higher discharge burn-ups and initial fuel enrichments have led to more and more heterogeneous core configurations in light water reactors (LWRs), especially at the beginning of cycle when fresh fuel assemblies are loaded next to highly burnt ones. As this trend is expected to continue in the future, the Paul Scherrer Institute has, in collaboration with the Swiss Association of Nuclear Utilities, swissnuclear, launched the experimental programme LIFE@PROTEUS. The LIFE@PROTEUS programme aims to better characterise interfaces between burnt and fresh UO2 fuel assemblies in modern LWRs. Thereby, a novel experimental database is to be made available for enabling the validation of neutronics calculations of strongly heterogeneous LWR core configurations. During the programme, mixed fresh and highly burnt UO2 fuel lattices will be investigated in the zero-power research reactor PROTEUS. One of the main types of investigations will be to irradiate the fuel in PROTEUS and measure the resulting fission rate distributions across the interface between fresh and burnt fuel zones. The measurement of fission rates in burnt fuel re-irradiated in a zero-power reactor requires, however, the development of new experimental techniques which are able to discriminate against the high intrinsic activity of the fuel. The principal goal of the present research work has been to develop such a new measurement technique. The selected approach is based on the detection of high-energy gamma-ray lines above the intrinsic background (i.e. above 2200 keV), which are emitted by short-lived fission products freshly created in the fuel. The fission products 88Kr, 142La, 138Cs, 84Br, 89Rb, 95Y, 90mRb and 90Rb, with half-lives between 2.6 min and 2.8 h, have been identified as potential candidates. During the present research work, the gamma-ray activity of short-lived fission products has, for the first time, been measured and quantitatively evaluated for re-irradiated burnt UO2 fuel samples with burn-ups of about 36 and 46GWd/t. Based on experiments carried out with these fuel samples in a reference test lattice of the PROTEUS reactor, fresh-to-burnt-fuel fission rate ratios could be determined. The 1σ uncertainties on the derived fission rate ratios are 1.7 to 3.4% and are mainly due to the statistical uncertainties. Calculated values of the fission rate ratios, as obtained using the Monte Carlo code MCNPX, have been shown to agree with the experimental results within these uncertainties. In deriving fresh-to-burnt-fuel fission rate ratios,142La and 138Cs have emerged as the preferred fission products. Their fission yields for the main fissile isotope (235U, 239Pu and 241Pu) are similar, which makes them relatively insensitive to the exact composition of the burnt fuel. Finally, a measurement station for the future LIFE@PROTEUS experiments has been proposed and evaluated, along with a detailed formulation of recommendations for optimised irradiation and measurement strategies. The estimated accuracy for the foreseen measurements of fission rate ratios between fresh and highly burnt fuel pins is 1 to 2%. The contribution of nuclear-data related uncertainties have been pointed out as possibly representing the main constraint on the achievable accuracy in future experiments. In brief, the present research work has established a novel experimental technique for measuring and comparing fission rates in fresh and highly burnt fuels in a zero-power research reactor such as PROTEUS. Moreover, possibilities have been presented for the further optimisation needed for a future, routine application of the technique.