After giving an introduction to nuclear data evaluation, we present implications of using the Bayesian inference to obtain evaluated cross sections and related uncertainties.
A computer code system, CCONE, was developed for nuclear data evaluation within the JENDL project.
The OECD Nuclear Energy Agency NEAA) organizes cooperation between the major nuclear data evaluation projects in the world.
The difference accounts for deficiencies in the design elements (nuclear data evaluation, neutronics code validation, and 3D modeling tools).
The NEA Working Party on International Nuclear Data Evaluation Cooperation WPECC) was established to promote the exchange of information on nuclear data evaluation, measurement, nuclear model calculation, validation, and related topics, and to provide a framework for cooperative activities between the participating projects.
This new database provides data essential for establishing the reliability of code systems for inventory predictions, but it also has broader potential application to nuclear data evaluation.
A Working Party at the NEA on International Nuclear Data Evaluation Co-operation is established to promote the exchange of nuclear data evaluations, measurements, nuclear model calculations and validation.
Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S thermal neutron scattering functions distributed with the MCNP code were used.
As an important result, it has been revealed that the neutron multiplication power of beryllium can be predicted with good accuracy using state-of-the-art nuclear data evaluations.
This paper based on the Monte Carlo method and real option theory to set up nuclear energy investment evaluation model.
