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Identifying Key 239,241Pu Fission Products to Reexamine for the Electron Antineutrino Energy Spectrum with the Summation Model

ORAL

Abstract

The latest series of nuclear reactor antineutrino experiments, (Daya Bay, Double Chooz, RENO, NEOS), have consistently demonstrated a discrepancy based on the current model of choice, the Huber-Mueller model. Each measurement found an unexplained 6% deficit in their antineutrino spectra. The model itself was derived from the integral electron spectra of 235U and 239,241Pu measured at the Institut Laue-Langevin (ILL). But in light of the recent publication on the 235U/239Pu spectra ratio by Kopeikin and collaborators, the Huber-Mueller model could have a normalization issue stemming from the original ILL measurements. For an entirely different method of determining antineutrino spectra, we used the summation model. Summation utilizes fission yield data from all the fission products of 235U and 239,241Pu to produce electron spectra. But not all data is of good quality due to cost, time, and difficulty for each and every fission product. In such a predicament, our group sought to identify several key nuclei that should be remeasured with high fidelity to produce antineutrino spectra. We began with electron spectrum data measured at ORNL and proceeded to use it to benchmark the JEFF-3.3 fission yields. Electron spectra were measured at regular time intervals for a short 1-second, medium 5 or 10 seconds, and long 50 or 100 seconds, thermal neutron irradiations. Because of the time dependence, the data was not only sensitive to the fission products' electron spectrum but also to their half-lives. In doing so, we could precisely identify nuclei with significant error and contribution.

Presenters

  • Bryan Palaguachi

    Colgate University

Authors

  • Bryan Palaguachi

    Colgate University

  • Zharia Harris

    University of Arkansas

  • Becket Hill

    Rensselaer Polytechnic Institute

  • Letty Krejci

    Brookhaven National Laboratory

  • Andrea Mattera

    Brookhaven National Laboratory, Brookhaven National Lab

  • Matthew Seeley

    Stony Brook University, Stony Brook University (SUNY)

  • Alejandro A Sonzogni

    Brookhaven National Laboratory