The definition of the few-group structure for the analysis of fast spectrum reactors is still an open issue in reactor physics.Recent works have demonstrated that heuristic search algorithms, such as the evolutionary ones, are promising techniques for choosing the group boundaries.In this work, some advancements in this field are reported in the frame of lead fast reactors analysis, thanks to the development of a flexible, application-independent genetic a lgorithm.The exploration of the optimal group structures for the EU ALFRED core design is carried out by coupling the genetic algorithm with the FRENETIC nodal diffusion c ode, w hich h as b een d eveloped w ith t he computationally efficient si mulation of li quid-metal co oled re actors.Th e se arch fo r th e ne arly-optimal few-group representation is carried out by comparing the output of FRENETIC with the reference keff, flux and power density computed with the Serpent Monte Carlo code.Two possible chromosomic representations of the group structures are introduced and tested in the genetic optimisation process, showing different convergence performances.
Advancements in the Genetic-Driven Optimisation of the Few-Group Structures for Lead Fast Reactors Analysis
Massone M.;
2024-01-01
Abstract
The definition of the few-group structure for the analysis of fast spectrum reactors is still an open issue in reactor physics.Recent works have demonstrated that heuristic search algorithms, such as the evolutionary ones, are promising techniques for choosing the group boundaries.In this work, some advancements in this field are reported in the frame of lead fast reactors analysis, thanks to the development of a flexible, application-independent genetic a lgorithm.The exploration of the optimal group structures for the EU ALFRED core design is carried out by coupling the genetic algorithm with the FRENETIC nodal diffusion c ode, w hich h as b een d eveloped w ith t he computationally efficient si mulation of li quid-metal co oled re actors.Th e se arch fo r th e ne arly-optimal few-group representation is carried out by comparing the output of FRENETIC with the reference keff, flux and power density computed with the Serpent Monte Carlo code.Two possible chromosomic representations of the group structures are introduced and tested in the genetic optimisation process, showing different convergence performances.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
