Alejandro Castillo

A new system to optimize both control rod pattern and fuel-loading design in boiling water reactors is shown. The system is named OCOTH, and it is based on heuristic techniques such as genetic algorithms, neural networks, and ant colonies. Each heuristic technique is used to design ...

Resumen La Comisión Federal de Electricidad anunció recientemente el comienzo de los trabajos relacionados con el aumento de la potencia a 120% de la nominal original en los reactores de agua en ebullición (BWR) de la Central Laguna Verde (CLV). En el Instituto Nacional de Investigaciones Nucleares (ININ) se realizan estudios del impacto sobre el diseño de la recarga de combustible derivado de este aumento. Uno de los efectos principales del tipo de aumento de potencia, que se esta promoviendo, es el incremento del flujo de vapor generado, lo que lleva, a una mayor fracción de vacíos en el núcleo presentándose valores incrementados de la máxima fracción al límite, tanto de la razón de generación lineal de calor (XFLPD) como de la razón de potencia crítica (MFLCPR). En los estudios efectuados, se encuentra que estas fracciones se elevan linealmente con el aumento de la potencia nominal. Considerando que los reactores de la CLV actualmente operan a 105% de la potencia nominal original...

In this paper a new system, called ohtli-PR, is presented. This system was developed for fuel lattice design optimization in Boiling Water Reactors (BWR) using the Path Relinking and Scatter Search techniques. As input data, the system uses an initial uranium enrichment ...

Resumen En este trabajo se presenta un nuevo sistema de optimización axial de combustible basado en una red neuronal recurrente multiestado llamado RENODC. Se describen con detalle las características principales de este tipo de red neuronal ( ...

ABSTRACT Fuel reload pattern optimization is a crucial fuel management activity in nuclear power reactors. Along the years, a lot of work has been done in this area. In particular, several metaheuristic optimization techniques have been applied with good results for boiling water reactors (BWRs). In this paper, a comparison of different metaheuristics: genetic algorithms, tabu search, recurrent neural networks and several ant colony optimization techniques, were applied, in order to evaluate their performance. The optimization of an equilibrium core of a BWR, loaded with mixed oxide fuel composed of plutonium and minor actinides, was selected to be optimized. Results show that the best average values are obtained with the recurrent neural networks technique, meanwhile the best fuel reload was obtained with tabu search. However, according to the number of objective functions evaluated, the two fastest optimization techniques are tabu search and Ant System.