Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
권호 표지
DOI QR코드

DOI QR Code

Approximate Multi-Objective Optimization of Gap Size of PWR Annular Nuclear Fuels

가압경수로용 환형 핵연료의 간극 크기 다중목적 근사최적설계

  • Doh, Jaehyeok (Graduate School of Mechanical Engineering, Yonsei University) ;
  • Kwon, Young Doo (School of Mechanical Engineering, Kyungpook National University) ;
  • Lee, Jongsoo (School of Mechanical Engineering, Yonsei University)
  • 도재혁 (연세대학교 기계공학과 대학원) ;
  • 권영두 (경북대학교 기계공학과) ;
  • 이종수 (연세대학교 기계공학과)
  • Received : 2015.01.12
  • Accepted : 2015.08.07
  • Published : 2015.09.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this study, we conducted the approximate multi-objective optimization of gap sizes of pressurized-water reactor (PWR) annular fuels. To determine the contacting tendency of the inner-outer gaps between the annular fuel pellets and cladding, thermoelastic-plastic-creep (TEPC)analysis of PWR annular fuels was performed, using in-house FE code. For the efficient heat transfer at certain levels of stress, we investigated the tensile, compressive hoop stress and temperature, and optimized the gap sizes using the non-dominant sorting genetic algorithm (NSGA-II). For this, response surface models of objective and constraint functions were generated, using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by NSGA-II were verified through the TEPC analysis, and we compared the obtained optimum solutions and generated errors from the CCD and D-optimal design. We observed that optimum solutions differ, according to design of experiments (DOE) method.

Keywords

References

  1. Kim, Y. W., "Development of Key Technology for Nuclear Hydrogen," Korea Atomic Energy Research Institute Research Report, p. 6, 2012.
  2. Rowinski, M. K., White, T. J., and Zhao, J., "Innovative Model of Annular Fuel Design for Lead-Cooled Fast Reactors," Progress in Nuclear Energy, Vol. 83, pp. 270-282, 2015. https://doi.org/10.1016/j.pnucene.2015.04.002
  3. Vitanza, C., "Ria Failure Threshold and Loca Limit at High Burn-Up," Journal of Nuclear Science and Technology, Vol. 43, No. 9, pp. 1074-1079, 2006. https://doi.org/10.1080/18811248.2006.9711197
  4. Lamarsh, J. R. and Barata, A. J., "Introduction to Nuclear Reactor Engineering," Prentice Hall, Inc., New Jersey, 3rd Ed., 2001.
  5. Ichikawa, M., Fujishiro, T., and Kawasaki, S., "LWR Fuel Safety Research with Particular Emphasis on Ria/Loca and Other Conditions," Journal of Nuclear Science and Technology, Vol. 26, No. 1, pp. 118-125, 1989. https://doi.org/10.1080/18811248.1989.9734276
  6. Lee, J. W., Lee, Y. S., Choi, Y. J., and Kang, Y. H., "Optimization for the Cylindrical Structure with Multi-Holes under Thermal Loading," Transactions of the Korean Society of Mechanical Engineers: A, Vol. 28, No. 10, pp. 1509-1516, 2004. https://doi.org/10.3795/KSME-A.2004.28.10.1509
  7. Kwon, Y.-D., Kwon, S.-B., Kim, S.-S., and Cho, H.-J., "Optimization of Gap Sizes for the High Performance of Annular Nuclear Fuels," Journal of Mechanical Science and Technology, Vol. 29, No. 4, pp. 1399-1405, 2015. https://doi.org/10.1007/s12206-015-0310-z
  8. Han, P. K. and Lee, J., "A Response Surface Based Sequential Approximate Optimization Using Constraint- Shifting Analogy," Journal of Mechanical Science and Technology, Vol. 23, No. 11, pp. 2903-2912, 2009. https://doi.org/10.1007/s12206-009-0806-5
  9. Park, S. H., "Modern Design of Experiments," Minyongsa, pp. 121-140, 2001.
  10. Triefenbach, F., "Design of Experiments: The DOptimal Approach and Its Implementation as a Computer Algorithm," B.Sc. Thesis, Department of Computing Science, Umea University, 2008.
  11. Kwon, Y. D., Kwon, S. B., Rho, K. T., Kim, M. S., and Song, H. J., "Thermo-Elastic-Plastic-Creep Finite Element Analyses of Annular Nuclear Fuels," International Journal of Modern Physics: Conference Series, Vol. 6, pp. 397-384, 2012. https://doi.org/10.1142/S2010194512003509
  12. Hong, K. J., Jeon, K. K., Cho, Y. S., Choi, D. H., and Lee, S. J., "A Study on the Construction of Response Surface for Design Optimization," Transactions of the Korean Society of Mechanical Engineers: A, Vol. 24, No. 6, pp. 1408-1418, 2000. https://doi.org/10.22634/KSME-A.2000.24.6.1408
  13. Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T., "A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II," IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, pp. 182-197, 2002. https://doi.org/10.1109/4235.996017
  14. Kim, H. C., Yang, Y. S., and Koo, Y. H., "Implementation of Effective-Stress-Function Algorithm for Nuclear Fuel Performance Code," Int. J. Precis. Eng. Manuf., Vol. 14, No. 5, pp. 791-796, 2013. https://doi.org/10.1007/s12541-013-0103-1
  15. Kojic, M. and Bathe, K. J., "The 'Effective-Stress- Function' Algorithm for Thermo-Elasto-Plasticity and Creep," International Journal for Numerical Methods in Engineering, Vol. 24, No. 8, pp. 1509-1532, 1987. https://doi.org/10.1002/nme.1620240808
  16. Kim, H. C, Yang, Y. S., Kim, D. H., Bang, J. G., Kim, S. K., et al., "Development of FE Module for Application of PWR Fuel Performance Code," Proc. of KSPE Spring Conference, pp. 963-964, 2012.
  17. SAS Institute Inc., Cary, NC, "SAS/CONNECT User's Manual Version 9.4," 2013.