Generation of fission yield covariances to correct discrepancies in the nuclear data libraries

Fiorito, Luca; Stankovskiy, Alexey; Eynde, Gert Van den; Díez, C.J.; Cabellos, Ó.; Labeau, Pierre-Etienne

doi:10.1016/j.anucene.2015.10.027

Cited by 36 publications

(21 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are several possible approaches to generate covariance data being considered based upon; (i) minimisation of physical constraints, (ii) perturbation of the model parameters underlying the yield distributions, (iii) LSQ or maximum likelihood methods using both an underlying model of fission and experimental data, examples can be found in the [6,[11][12][13][14] and the references therein. However, as the cumulative yields can be directly calculated from the independent yields using decay data, it is also possible to determine the covariance terms iteratively from the experimental data in this evaluation [15].…”

Section: Future Developments 41 Uncertainties On Engineering Quantimentioning

confidence: 99%

A new UK fission yield evaluation UKFY3.7

Mills

2017

EPJ Web Conf.

View full text Add to dashboard Cite

The JEFF neutron induced and spontaneous fission product yield evaluation is currently unchanged from JEFF-3.1.1, also known by its UK designation UKFY3.6A. It is based upon experimental data combined with empirically fitted mass, charge and isomeric state models which are then adjusted within the experimental and model uncertainties to conform to the physical constraints of the fission process. A new evaluation has been prepared for JEFF, called UKFY3.7, that incorporates new experimental data and replaces the current empirical models (multi-Gaussian fits of mass distribution and Wahl Zp model for charge distribution combined with parameter extrapolation), with predictions from GEF. The GEF model has the advantage that one set of parameters allows the prediction of many different fissioning nuclides at different excitation energies unlike previous models where each fissioning nuclide at a specific excitation energy had to be fitted individually to the relevant experimental data. The new UKFY3.7 evaluation, submitted for testing as part of JEFF-3.3, is described alongside initial results of testing. In addition, initial ideas for future developments allowing inclusion of new measurements types and changing from any neutron spectrum type to true neutron energy dependence are discussed. Also, a method is proposed to propagate uncertainties of fission product yields based upon the experimental data that underlies the fission yield evaluation. The covariance terms being determined from the evaluated cumulative and independent yields combined with the experimental uncertainties on the cumulative yield measurements.

show abstract

Section: Future Developments 41 Uncertainties On Engineering Quantimentioning

confidence: 99%

A new UK fission yield evaluation UKFY3.7

Mills

2017

EPJ Web Conf.

View full text Add to dashboard Cite

show abstract

“…SANDY can generate such covariances using the generalized least-squares method described in [9], which adjusts the current data to the available knowledge of observables such as the chain fission yields [10]. Figure 6 shows that the impact of independent fission yield covariances on the decay heat uncertainty reduces by far the importance of such data.…”

Section: Decay Heat Uncertainty Quantificationmentioning

confidence: 99%

“…The uncertainty propagation was carried out with the NUDUNA code [3] for the cross section data and with the SANDY code [4] for fission yields, decay constants and energies. Both codes base the uncertainty propagation on the random sampling of the input nuclear data according to their uncertainty/covariance information.…”

Section: Decay Heat Uncertainty Quantificationmentioning

confidence: 99%

“…Then, the uncertainties/covariances of decay constants, decay energies, independent fission yields and cross sections were propagated through the model and the decay heat uncertainty was quantified. NUDUNA [3] and SANDY [4] were the codes selected for the nuclear data uncertainty propagation. From the analysis of the results we were able to assess which nuclear data introduce the largest uncertainties on the decay heat evaluation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Decay heat uncertainty quantification of MYRRHA

Fiorito

Buss²,

Hoefer³

et al. 2017

EPJ Web Conf.

View full text Add to dashboard Cite

Abstract. 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.

show abstract

“…), is one of the major contributor to the uncertainty on computed reactor physics quantities (see for example [1]). Furthermore, the uncertainty propagation can not be properly done since the yield variance-covariance matrices are missing from the evaluated data libraries, despite recent efforts to address this issue [2][3][4][5]. Additionally, some discrepancies between the major libraries exist and need to be understood.…”

Section: Introductionmentioning

confidence: 99%

New measurements on isobaric fission product yields and mean kinetic energy for ²⁴¹Pu thermal neutron-induced fission

et al. 2018

View full text Add to dashboard Cite

Abstract. Nuclear fission yields data measurements for thermal neutron induced fission of 241 Pu have been carried out at the Institut Laue Langevin (ILL) in Grenoble, using the Lohengrin mass spectrometer. Mass, isotopic and isomeric yields have been extracted for the last measurements. A focus is given in this document to the mass yield results which are obtained for almost the entire heavy peak and most of the light high yields masses, along with the covariance matrix. The mean kinetic energy as a function of the fission product mass has also been extracted from the measurements. The total mean kinetic energy pre and post neutron emission have been assessed and compared to other works showing a rather good agreement.

show abstract

Generation of fission yield covariances to correct discrepancies in the nuclear data libraries

Cited by 36 publications

References 10 publications

A new UK fission yield evaluation UKFY3.7

A new UK fission yield evaluation UKFY3.7

Decay heat uncertainty quantification of MYRRHA

New measurements on isobaric fission product yields and mean kinetic energy for ²⁴¹Pu thermal neutron-induced fission

Contact Info

Product

Resources

About

Generation of fission yield covariances to correct discrepancies in the nuclear data libraries

Cited by 36 publications

References 10 publications

A new UK fission yield evaluation UKFY3.7

A new UK fission yield evaluation UKFY3.7

Decay heat uncertainty quantification of MYRRHA

New measurements on isobaric fission product yields and mean kinetic energy for 241Pu thermal neutron-induced fission

Contact Info

Product

Resources

About

New measurements on isobaric fission product yields and mean kinetic energy for ²⁴¹Pu thermal neutron-induced fission