EPJ Web Conf.
Volume 146, 2017ND 2016: International Conference on Nuclear Data for Science and Technology
|Number of page(s)||5|
|Section||Fission Physics and Observables|
|Published online||13 September 2017|
Macroscopic-microscopic model of nuclear potential energy
1 CEA, DEN, DER, SPRC, Cadarache, 13108 Saint-Paul-lez-Durance, France
2 Los Alamos National Laboratory, Theoretical Division, Los Alamos, NM 87545, USA
a e-mail: firstname.lastname@example.org
Published online: 13 September 2017
To improve the evaluation of nuclear observables, refined models are to be used more and more as underlying analysis tools. Fission is a complex process and is the less accurately described with current models. Standard evaluation models rely on the Hill-Wheeler formalism for the fission transmission coefficient, which in turns is based on phenomenological parameters “reflecting” the fission barrier heights and widths. To reduce the weight of phenomenology in the evaluation process, nuclear structure models are expected to embed more and more microscopic descriptions. As models are rarely exact, evaluators are often compelled to “tune” model parameters so that observables can be properly reproduced. Related computation time can thus be a major hindrance to the use of advanced models in evaluation as final adjustments are expected to remain necessary. For this reason, a macroscopic-microscopic model has been selected to replace the current phenomenological description of fission barriers. The Finite-Range Liquid-Drop Model (FRLDM) has been implemented in the CONRAD evaluation code and its present implementation shows remarkable consistency with experimental and published benchmark data. The CONRAD code can be used to provide expectation values but also related uncertainties and covariance data. Sensitivity of FRLDM parameters and the correlation matrix between these parameters have been obtained so that further uncertainty propagation on barrier heights can be carried out in the near future.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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