Decay Heat Uncertainty Research Articles

Use of correlations for neutron induced fission yields in DARWIN/PEPIN2 Uncertainty Quantification

Uncertainty quantification on Decay Heat is of utmost importance for the safety evaluations linked to nuclear waste management. International nuclear data libraries like JEFF, ENDF/B or JENDL provide evaluations on independent fission yields, but generally no correlations between those fission yields. With those data, independent fission yields can be considered as the most important contributor to the Decay Heat uncertainty. Nevertheless, other data are available, like correlation matrices for some fissile systems, or the use of fission yields by mass. Complete correlation matrices appear in nuclear data libraries, like JEFF-4, but are still very scares as only the most prominent fissile systems for nuclear reactor applications have been added. Another approach is to consider the use of the fission yields by mass, which uncertainty is smaller than those of independent fission yields, and adding a constraint when propagating uncertainties. In the work, we show the impact of considering the fission yields by mass, as it was implemented in DARWIN/PEPIN2.4.8. We compare DARWIN/PEPIN2.4.8 results, obtained on a first order direct perturbation approach, with a random sampling method through the use of an URANIE/MENDEL scheme.

Uncertainty analyses of spent nuclear fuel decay heat calculations using SCALE modules

Decay heat residuals of spent nuclear fuel (SNF), i.e., the differences between calculations and measurements, were obtained previously for various spent fuel assemblies (SFA) using the Polaris module of the SCALE code system. In this paper, we compare decay heat residuals to their uncertainties, focusing on four PWRs and four BWRs. Uncertainties in nuclear data and model inputs are propagated stochastically through calculations using the SCALE/Sampler super-sequence. Total uncertainties could not explain the residuals of two SFAs measured at GE-Morris. The combined z-scores for all SFAs measured at the Clab facility could explain the resulting deviations. Nuclear-data-related uncertainties contribute more in the high burnup SFAs. Design and operational uncertainties tend to contribute more to the total uncertainties. Assembly burnup is a relevant variable as it correlates significantly with the SNF decay heat. Additionally, burnup uncertainty is a major contributor to decay heat uncertainty, and assumptions relating to these uncertainties are crucial. Propagation of nuclear data and design and operational uncertainties shows that the analyzed assemblies respond similarly with high correlation. The calculated decay heats are highly correlated in the PWRs and BWRs, whereas lower correlations were observed between decay heats of SFAs that differ in their burnups.

Uncertainty quantification in decay heat calculation of spent nuclear fuel by STREAM/RAST-K

This paper addresses the uncertainty quantification and sensitivity analysis of a depleted light-water fuel assembly of the Turkey Point-3 benchmark. The uncertainty of the fuel assembly decay heat and isotopic densities is quantified with respect to three different groups of diverse parameters: nuclear data, assembly design, and reactor core operation. The uncertainty propagation is conducted using a two-step analysis code system comprising the lattice code STREAM, nodal code RAST-K, and spent nuclear fuel module SNF through the random sampling of microscopic cross-sections, fuel rod sizes, number densities, reactor core total power, and temperature distributions. Overall, the statistical analysis of the calculated samples demonstrates that the decay heat uncertainty decreases with the cooling time. The nuclear data and assembly design parameters are proven to be the largest contributors to the decay heat uncertainty, whereas the reactor core power and inlet coolant temperature have a minor effect. The majority of the decay heat uncertainties are delivered by a small number of isotopes such as 241Am, 137Ba, 244Cm, 238Pu, and 90Y.

NUCLEAR DATA UNCERTAINTY QUANTIFICATION FOR THE DECAY HEAT OF PWR MOX FUELS USING DATA ASSIMILATION OF ELEMENTARY FISSION BURSTS

Currently there is no integral experimental data for code validation regarding the decay heat of MOX fuels, excepted fission burst experiments (for fission products contributions at short cooling times) or post-irradiated experiments on nuclide inventories (restricted number of nuclide of interest for decay heat). The uncertainty quantification mainly relies on uncertainty propagation of nuclear data covariances. In the recent years, the transposition method, based on the data assimilation theory, was used in order to transpose the experiment-to-calculation discrepancies at a given set of parameters (cooling time, fuel burnup) to another set of parameters. As an example, this method was used on the CLAB experiments and the experiment-to-calculation discrepancies at 13 years were transposed to an UOX fuel between 5 and 27 years and for burnups from 10 to 50 GWd/t. The purpose of this paper is to study to what extent the transposition method could be used for MOX fuels. In particular, the Dickens fission burst experiment of 239Pu was considered for MOX fuels at short cooling times (< 1h30) and low burnup (< 10 GWd/t). The impact of fission yields (FY) correlations was also discussed. As a conclusion, the efficiency of the transposition process is limited by the experimental uncertainties larger than nuclear data uncertainties, and by the fact that fission burst experiments would only be representative to the FY contribution of the decay heat uncertainty of an irradiated reactor fuel. Nevertheless, this method strengthens the decay heat uncertainties at very short cooling times, previously based only on nuclear data covariance propagation through computation.

Integral data assimilation of the MERCI-1 experiment for the nuclear data associated with the PWR decay heat computation

Nuclear decay heat is a crucial issue for PWR in-core safety after reactor shutdown and back-end cycle. It is a dimensioning parameter for safety injection systems (SIS) to avoid a dewatering of the reactor core. The decay heat uncertainty needs to be controlled over the largest range of applications. The assimilation of the MERCI-1 experiment was studied to provide feedbacks on nuclear data. This experiment consisted in the measurement of the decay heat of a PWR UOX fuel sample irradiated in the OSIRIS reactor, for cooling times between 45 minutes and 42 days. More specifically, the consideration of several experimental values of MERCI-1 at different cooling times was tested. This raised issues about correlations to consider between different measurements. Besides, the impact of considering correlations between independent fission yields in covariance matrices on the decay heat uncertainty calculation and on the feedbacks on nuclear data is discussed.

Uncertainty propagation of fission product yields to nuclide composition and decay heat for a PWR UO2 fuel assembly

The assessment of the fission yield uncertainties on neutronic parameters is of great interest for criticality and spent fuel behavior studies. In this work, several fission yield perturbation methodologies are used to propagate the uncertainties for a PWR fuel assembly. Aside from the TENDL-2011 fission yields, a Generalized Least Square method is used on the JEFF-3.1.1 and the ENDF/B-VII.1 fission yields to generate correlations in agreement with the conservation equations. The branching ratios are also perturbed using this technique. Moreover the GEF code is employed to generate correlated fission yields from perturbed model parameters but also, coupled to a Bayesian process, to generate correlated fission yields for ENDF/B-VII.1. The resulting kinf uncertainty versus the exposure are assessed and discussed as well as nuclide density uncertainties at 60 GWd/tIHM and the decay heat uncertainty up to 105 days (274 years).

Fission yield covariance matrices for the main neutron-induced fissioning systems contained in the JEFF-3.1.1 library

Nuclear data improvement, validation and completion are one of the major concerns for ensuring safety-by-design standards and economic optimization for modern nuclear facilities. Uncertainty and sensitivity analyses must be carried out to estimate the nuclear data influence on integral reactor parameters, highlighting margins of improvement needed to get full benefit from modern advanced modeling. The quality of any uncertainty quantification analysis strongly depends on the covariance matrices made available in the evaluated nuclear data libraries. In modern nuclear data libraries (e.g. JEFF, ENDF/B or JENDL) no correlations for fission yields (FY) are provided, so in the present work we propose a covariance generation methodology which yielded reasonable results for application-relevant thermal and fast neutron-induced fission product yields. The main goal was not to perform a new evaluation but to reproduce coherently the JEFF-3.1.1 fission yield library and add covariance information. We did so using the Generalized Least Square Method (GLSM) and the Marginalization techniques implemented in the CONRAD code, developed at CEA-Cadarache. Results on the thermal neutron-induced fission of 235U,239Pu,241Pu and on the fast-neutron induced fission of 238U,239Pu and 240Pu are presented and tested on elementary fission decay heat uncertainty quantifications.

Decay heat uncertainty for BWR used fuel due to modeling and nuclear data uncertainties

Characterization of the energy released from radionuclide decay in nuclear fuel discharged from reactors is essential for the design, safety, and licensing analyses of used nuclear fuel storage, transportation, and repository systems. There are a limited number of decay heat measurements available for commercial used fuel applications. Because decay heat measurements can be expensive or impractical for covering the multitude of existing fuel designs, operating conditions, and specific application purposes, decay heat estimation relies heavily on computer code prediction. Uncertainty evaluation for calculated decay heat is an important aspect when assessing code prediction and a key factor supporting decision making for used fuel applications. While previous studies have largely focused on uncertainties in code predictions due to nuclear data uncertainties, this study discusses uncertainties in calculated decay heat due to uncertainties in assembly modeling parameters as well as in nuclear data. Capabilities in the SCALE nuclear analysis code system were used to quantify the effect on calculated decay heat of uncertainties in nuclear data and selected manufacturing and operation parameters for a typical boiling water reactor (BWR) fuel assembly. The BWR fuel assembly used as the reference case for this study was selected from a set of assemblies for which high-quality decay heat measurements are available, to assess the significance of the results through comparison with calculated and measured decay heat data.

Decay heat uncertainty quantification of MYRRHA

MYRRHA is a lead-bismuth cooled MOX-fueled accelerator driven system (ADS) currently in the design phase at SCK·CEN in Belgium. The correct evaluation of the decay heat and of its uncertainty level is very important for the safety demonstration of the reactor. In the first part of this work we assessed the decay heat released by the MYRRHA core using the ALEPH-2 burnup code. The second part of the study focused on the nuclear data uncertainty and covariance propagation to the MYRRHA decay heat. Radioactive decay data, independent fission yield and cross section uncertainties/covariances were propagated using two nuclear data sampling codes, namely NUDUNA and SANDY. According to the results, 238 U cross sections and fission yield data are the largest contributors to the MYRRHA decay heat uncertainty. The calculated uncertainty values are deemed acceptable from the safety point of view as they are well within the available regulatory limits.

Feasibility study of decay heat uncertainty reduction using nuclear data adjustment method with experimental data

ABSTRACTThe accurate prediction of the decay heat is essential, especially for nuclear power plant safety purposes. However, it is known that the decay heat predicted by nuclear fuel burn-up calculations is uncertain because of uncertainty of nuclear data employed in the calculations. If the decay heat uncertainty can be reduced, the safety margin of the predicted decay heat can also be reduced, and feasible design ranges of various types of equipments related to the decay heat can be extended. In the present study, we use the nuclear data adjustment method for the decay heat uncertainty reduction with several types of the experimental data. As a result, we clarify that the decay heat uncertainty with short- and long-term cooling periods can be reduced by this method with appropriate experimental data.

Comparison of deterministic and stochastic approaches for isotopic concentration and decay heat uncertainty quantification on elementary fission pulse

Uncertainty quantification of interest outputs in nuclear fuel cycle is an important issue for nuclear safety, from nuclear facilities to long term deposits. Most of those outputs are functions of the isotopic vector density which is estimated by fuel cycle codes, such as DARWIN/PEPIN2, MENDEL, ORIGEN or FISPACT. CEA code systems DARWIN/PEPIN2 and MENDEL propagate by two different methods the uncertainty from nuclear data inputs to isotopic concentrations and decay heat. This paper shows comparisons between those two codes on a Uranium-235 thermal fission pulse. Effects of nuclear data evaluation’s choice (ENDF/B-VII.1, JEFF-3.1.1 and JENDL-2011) is inspected in this paper. All results show good agreement between both codes and methods, ensuring the reliability of both approaches for a given evaluation.

Probabilistic approach for decay heat uncertainty estimation using URANIE platform and MENDEL depletion code

The knowledge of the decay heat quantity and the associated uncertainties are important issues for the safety of nuclear facilities. Many codes are available to estimate the decay heat. ORIGEN, FISPACT, DARWIN are part of them. MENDEL is a new depletion code developed at CEA, with new software architecture, devoted to the calculation of physical quantities related to fuel cycle studies, in particular decay heat.The purpose of this paper is to present a probabilistic approach to assess decay heat uncertainty due to the decay data uncertainties from nuclear data evaluation like JEFF-3.1.1 or ENDF/B-VII.1. This probabilistic approach is based both on the MENDEL code and URANIE software which is a CEA uncertainty analysis platform. As preliminary applications, single thermal fission of Uranium 235 and Plutonium 239 are investigated.

Decay Heat of Fast Reactor Spent Fuel

Decay heat from JOYO Mk-II spent fuel subassemblies was measured to obtain experimental data and to improve the accuracy of related calculations. The measurement was taken in the JOYO spent fuel storage pond. The fuel burn-up was approximately 66 GWd/t and the cooling time was between 40 and 385 days. The decay heat was calculated with the ORIGEN2 code using the JENDL-3.2 cross section library and the JNDC-V2 decay data and fission yield data library. The fuel power used as an input to ORIGEN2 was calculated by the MAGI core management code system. The ratios between calculated and experimental values were between 0.94 and 0.89 and decreased with a longer cooling time. This systematic discrepancy is not fully understood, but the change with cooling time appears to be due to the actinide decay heat uncertainty. This indicated that cross sections of actinides are important to evaluate decay heat accurately.