Refine your search:     
Report No.
 - 

Reduction and resource recycling of high-level radioactive wastes through nuclear transformation; Theoretical predictions of the nuclear reaction data for nuclei involved in the nuclear transformation system

Furutachi, Naoya; Minato, Futoshi; Iwamoto, Osamu

For the feasibility study of the nuclear transmutation system for the long-lived fission products(LLFPs), the simulation calculation to estimate the efficiency of the transmutation system is essential. The precision of the simulation calculation largely depends on the evaluated nuclear data used in the calculation. To improve the precision of the simulation calculation, developing nuclear data not only of LLFPs but also of all the nuclei involved in the simulation calculation is desirable. When we study the transmutation system using the nuclear reaction such as spallation reaction, it is anticipated that a wide range of nuclei including unstable nuclei with no or scarce experimental are produced. In particular, the shortage of nuclear experimental data in resonance region is a problem for nuclear data evaluation, because it is difficult to predict the resonant structure precisely in a theoretical way. One of the methods mitigating this problem is to use the resonance parameters randomly determined from the statistical properties of the resonance parameters. This approach is already adopted in TENDL nuclear data library. However, the cross section calculated using such a method would have a large uncertainty arising from the statistical fluctuation of the resonance parameters in principle. This uncertainty wasn't discussed in the previous study. In this study, we investigated the statistical method to predict the nuclear reaction data in resonance region focusing on its statistical uncertainties. Particularly, we shall discuss the neutron capture cross sections of nuclei expected to be produced via the transmutation of Se-79, Zr-93, Pd-107 and Cs-135.

Accesses

:

- Accesses

InCites™

:

Altmetrics

:

[CLARIVATE ANALYTICS], [WEB OF SCIENCE], [HIGHLY CITED PAPER & CUP LOGO] and [HOT PAPER & FIRE LOGO] are trademarks of Clarivate Analytics, and/or its affiliated company or companies, and used herein by permission and/or license.