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Volumn 35, Issue 2, 2008, Pages 269-276

Application of minimum plutonium criteria at EOC to optimize the fuel loading pattern in VVER-1000 reactors

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; GENETIC ALGORITHMS; NUCLEAR REACTORS; OPTIMIZATION; PLUTONIUM;

EID: 37849004373     PISSN: 03064549     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.anucene.2007.06.011     Document Type: Article
Times cited : (17)

References (13)
  • 1
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    • Analysis of the burnup credit benchmark with an updated WIMS-D library
    • Aldama D.L., and Trkov A. Analysis of the burnup credit benchmark with an updated WIMS-D library. Annals of Nuclear Energy 27 (2000) 169
    • (2000) Annals of Nuclear Energy , vol.27 , pp. 169
    • Aldama, D.L.1    Trkov, A.2
  • 2
    • 0029724516 scopus 로고    scopus 로고
    • Back, T., Heistermann, J., Kappler, C., Zamparelli, M., 1996. Evolutionary algorithms support refuelling of pressurized water reactors. In: Proceedings of the Third IEEE Conference on Evolutionary Computation, Piscataway, NJ. pp. 104-108.
  • 3
    • 1842682654 scopus 로고    scopus 로고
    • Optimal fuel core loading pattern design in PWR nuclear power reactors using genetic algorithms and fuzzy nonlinear programming
    • Boroushaki M., Ghofrani M.B., and Lucas C. Optimal fuel core loading pattern design in PWR nuclear power reactors using genetic algorithms and fuzzy nonlinear programming. Journal of Intelligent and Fuzzy Systems 14 12 (2003) 85-93
    • (2003) Journal of Intelligent and Fuzzy Systems , vol.14 , Issue.12 , pp. 85-93
    • Boroushaki, M.1    Ghofrani, M.B.2    Lucas, C.3
  • 4
    • 37849029721 scopus 로고    scopus 로고
    • Fowler, T.B., 1999. CITATION-LDI2 nuclear reactor core analysis code system. CCC-643, ORNL, Oak Ridge, Tennessee.
  • 6
    • 37849023677 scopus 로고    scopus 로고
    • Generation IV International Forum, 2002. GIF-019-00. Generation IV roadmap technology goals for generation IV nuclear energy systems. Nuclear energy research advisory committee. Available at: http://gif.inel.gov/roadmap/pdfs/019_technology_goals.pdf.
  • 9
    • 31144447788 scopus 로고    scopus 로고
    • Development of a supporting tool for optimal fuel management in research reactors using artificial neural networks
    • Mazrou H., and Hamadouche M. Development of a supporting tool for optimal fuel management in research reactors using artificial neural networks. Nuclear Engineering and Design 236 (2006) 255-266
    • (2006) Nuclear Engineering and Design , vol.236 , pp. 255-266
    • Mazrou, H.1    Hamadouche, M.2
  • 10
    • 37849002457 scopus 로고    scopus 로고
    • NEA, 1999. NEA-1507, WIMSD-5B (98/11), Deterministic Multi-group Reactor Lattice Calculations.
  • 11
    • 0030246756 scopus 로고    scopus 로고
    • Multi-objective pressurized water reactor reload core design by non-dominated genetic algorithm search
    • Parks G.T. Multi-objective pressurized water reactor reload core design by non-dominated genetic algorithm search. Nuclear Science and Engineering 124 (1996) 178-187
    • (1996) Nuclear Science and Engineering , vol.124 , pp. 178-187
    • Parks, G.T.1
  • 12
    • 0033150096 scopus 로고    scopus 로고
    • Multi-objective fuel management optimization for self-fuel-providing LMFBR using genetic algorithms
    • Toshinsky V.G., Sekimoto H., and Toshinsky G.I. Multi-objective fuel management optimization for self-fuel-providing LMFBR using genetic algorithms. Annals Nuclear Energy 26 (1999) 783-802
    • (1999) Annals Nuclear Energy , vol.26 , pp. 783-802
    • Toshinsky, V.G.1    Sekimoto, H.2    Toshinsky, G.I.3
  • 13
    • 0033895669 scopus 로고    scopus 로고
    • A method to improve multi-objective genetic algorithms optimization of a self-fuel providing LMFBR by niche induction among non-dominated solutions
    • Toshinsky V.G., Sekimoto H., and Toshinsky G.I. A method to improve multi-objective genetic algorithms optimization of a self-fuel providing LMFBR by niche induction among non-dominated solutions. Annals Nuclear Energy 27 (2000) 397-410
    • (2000) Annals Nuclear Energy , vol.27 , pp. 397-410
    • Toshinsky, V.G.1    Sekimoto, H.2    Toshinsky, G.I.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.