Nuclear Data for Sustainable Nuclear Energy

Final report of a coordinated action on nuclear data for industrial development in Europe (CANDIDE). The successful development of advanced nuclear systems for sustainable energy production depends on high-level modelling capabilities for the reliable and cost-effective design and safety assessment of such systems, and for the interpretation of key benchmark experiments needed for performance and safety evaluations. High-quality nuclear data, in particular complete and accurate information about the nuclear reactions taking place in advanced reactors and the fuel cycle, are an essential component of such modelling capabilities. In the CANDIDE project, nuclear data needs for sustainable nuclear energy production and waste management have been analyzed and categorized, on the basis of preliminary design studies of innovative systems. Meeting those needs will require that the quality of nuclear data files be considerably improved. The CANDIDE project has produced a set of recommendations, or roadmap, for sustainable nuclear data development. In conclusion, a substantial long-term investment in an integrated European nuclear data development program is called for, complemented by some dedicated actions targeting specific issues.JRC.D.5-Neutron physic

Results and lessons learned from the Generation IV SCWR-FQT comprehensive Monte Carlo computational benchmark

A joint European Canadian Chinese development of a supercritical water-cooled small modular reactor technology has been in progress since September 2020 in the framework of a Horizon 2020 project called ECC-SMART. A specific work package has been dedicated to studying the design- and safety-related neutronic parameters and reactor physics behavior of the SCW-SMR to support the pre-conceptual design process. Three Monte Carlo codes, viz., MCNP, OpenMC, and Serpent, were selected for pre-conceptual design applications and code-to-code comparison within the Gen-IV SCWR-FQT reactor physics computational benchmark. The effective multiplication factor, the axial power distribution within the fuel, the axial three-group neutron flux distribution, and the spatial distribution of the energy deposition due to neutron and photon interactions were determined. In this paper, results and lessons learned from this study are presented, and useful considerations are summarized to provide guidance in obtaining consistent results among the three Monte Carlo codes