Published 2007 | Version v1
Computer medium

A new approach for optimal fuel core loading pattern design in VVER nuclear power reactors using genetic algorithm

  • 1. Dept. of Mechanical Engineering, Sharif Univ. of Technology, Tehran (Iran, Islamic Republic of)

Description

Most of strategies yet implemented to optimal fuel core loading pattern design in nuclear power reactors, are based on maximizing the core effective multiplication factor (Keff) to extract maximum energy and lowering the local power peaking factor (Pq) from a predetermined value. However, a new optimization criterion could be of interest, aiming maximum burn up of the plutonium content in nuclear fuel assemblies, i.e., minimization of remaining plutonium in spent fuel at the end of cycle (EOC). In this research, we developed a new strategy for optimal fuel core loading pattern of a VVER-1000 reactor, based on multi-objective optimization: lowering the Pq, maximization of the Keff and minimization of remaining plutonium (Pu) in fuels at EOC condition. This strategy has been implemented via exact calculations of fuel burn up during the equilibrium cycle using WIMS and CITATION calculation codes. We used genetic algorithm to find the optimum fuel loading pattern. (author)

Availability note (English)

Available from Japan Society of Mechanical Engineers, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-0016, Japan
Part of:
Proceedings of the ICONE-15 (Revised). The 15th international conference on nuclear engineering

Additional details

Publishing Information

Publisher
Japan Society of Mechanical Engineers
Imprint Place
Tokyo (Japan)
Imprint Title
Proceedings of the ICONE-15 (Revised). The 15th international conference on nuclear engineering
Imprint Pagination
[3174 p.]
Journal Page Range
[9 p.]

Conference

Title
15. international conference on nuclear engineering
Acronym
ICONE-15
Dates
22-26 Apr 2007
Place
Nagoya, Aichi (Japan)

Optional Information

Notes
This CD-ROM can be used for WINDOWS 9x/NT/2000/ME/XP, MACINTOSH; Acrobat Reader is included; Data in PDF format, Folder Name Final Paper, Paper ID ICONE15-10008.pdf; 12 refs., 9 figs., 2 tabs.