Journal of Electrical Engineering and Technology

  • 제8권4호
  • /
  • Pages.780-786
  • /
  • 2013
  • /
  • 1975-0102(pISSN)
  • /
  • 2093-7423(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지
DOI QR코드

DOI QR Code

A Second-Order Design Sensitivity-Assisted Monte Carlo Simulation Method for Reliability Evaluation of the Electromagnetic Devices

  • Ren, Ziyan (College of Electrical and Computer Engineering, Chungbuk National University) ;
  • Koh, Chang-Seop (College of Electrical and Computer Engineering, Chungbuk National University)
  • 투고 : 2012.07.24
  • 심사 : 2013.03.05
  • 발행 : 2013.07.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In the reliability-based design optimization of electromagnetic devices, the accurate and efficient reliability assessment method is very essential. The first-order sensitivity-assisted Monte Carlo Simulation is proposed in the former research. In order to improve its accuracy for wide application, in this paper, the second-order sensitivity analysis is presented by using the hybrid direct differentiation-adjoint variable method incorporated with the finite element method. By combining the second-order sensitivity with the Monte Carlo Simulation method, the second-order sensitivity-assisted Monte Carlo Simulation algorithm is proposed to implement reliability calculation. Through application to one superconductor magnetic energy storage system, its accuracy is validated by comparing calculation results with other methods.

키워드

참고문헌

  1. P. T. Lin, H. C. Gea, and Y. Jaluria, "A modified reliability index approach for reliability-based design optimization," ASME J. Mech. Des., Vol. 33, pp. 44501-044507, Apr. 2011.
  2. Z. Y, Ren, D. H. Zhang, M. T. Pham, and C. S. Koh, "A new reliability calculation algorithm based on sensitivity analysis and its application to reliabilitybased robust global optimization of electromagnetic device with uncertain design variables," Mater. Sci. Forum, Vol. 721, pp. 165-170, Jun. 2012. https://doi.org/10.4028/www.scientific.net/MSF.721.165
  3. M. H. Kim, H. B. Lee, H. S. Kim, and J. K. Byun, "A new unified design environment for optimization of electric machines based on continuum sensitivity and B-spline parameterization," Journal of Electrical Engineering & Technology, Vol. 6, No. 4, pp. 513-518, 2011. https://doi.org/10.5370/JEET.2011.6.4.513
  4. J. Y. Ding, Z. K. Pan, and L. Q. Chen, "Second-order sensitivity analysis of multibody systems described by differential/algebraic: adjoint variable approach," Int. J. Comput. Math., Vol. 85, No. 6, pp. 899-913, Jun. 2008. https://doi.org/10.1080/00207160701519020
  5. N. K. Kim, et al, "Robust optimization utilizing the second order design sensitivity information," IEEE Trans. Magn., Vol. 46, No. 8, pp. 3117-3120, Aug. 2010. https://doi.org/10.1109/TMAG.2010.2043719
  6. Z. X. Ren, H. Qu, and X. Y. Xu, "Computation of second order capacitance sensitivity using adjoint method in finite element modeling," IEEE Trans. Magn., Vol. 48, No. 2, pp. 231-234, Feb. 2012. https://doi.org/10.1109/TMAG.2011.2172194
  7. A. J. Haug, K. K. Choi, and V. Komkov, Design sensitivity analysis of structural systems. Academic press, INC, London, 1986.
  8. D.W. Kim, et al, "Reliability assessment on different designs of a SMES system based on reliability index approach," Journal of Electrical Engineering & Technology, Vol. 7, No. 1, pp. 46-50, 2012. https://doi.org/10.5370/JEET.2012.7.1.46
  9. D. Sutanto and K. Cheng, "Superconducting magnetic energy storage systems for power system applications," IEEE Inter. Conf. on Applied Superconductivity & Electromagnetic Devices (ASEMD 2009), pp. 377-380.
  10. P. G. Alotto, et al, "SMES optimization benchmark: TEAM workshop problem 22," Available: http://www.igte.tugraz.at/team22.
  11. B. D. Youn and K. K. Choi, "Selecting probabilistic approaches for reliability-based design optimization," AIAA, Vol. 42, No. 1, pp. 124-131, Jan. 2004. https://doi.org/10.2514/1.9036
  12. R. H. C. Takahashi, J. A. Vasconcelos, J. A. Ramirez, and L. Krahenbuhl, "A multiobjective methodology for evaluating genetic operators," IEEE Trans. Magn., Vol. 39, No. 3, pp. 1321-1324, May 2003. https://doi.org/10.1109/TMAG.2003.810371
  13. F. G. Guimaraes, et al, "A multiobjective proposal for the TEAM benchmark problem 22," IEEE Trans. Magn., Vol. 42, No. 4, pp. 1471-1474, Apr. 2006. https://doi.org/10.1109/TMAG.2006.871570
  14. F. G. Guimaraes, P. H. L. Barros, and J. A. Ramirez, "An object-oriented library based on computational intelligence techniques for optimization in electromagnetic," IEEE Trans. Magn., Vol. 39, No. 4, pp. 2121-2124, Jul. 2003. https://doi.org/10.1109/TMAG.2003.810363
  15. L. D. S. Batista, F. G. Guimaraes, and J. A. Ramirez, "A distributed clonal selection algorithm for optimization in electromagnetic," IEEE Trans. Magn., Vol. 45, No. 3, pp. 1598-1601, Mar. 2009. https://doi.org/10.1109/TMAG.2009.2012752

피인용 문헌

  1. Second-order adjoint sensitivity analysis methodology (2nd-ASAM) for computing exactly and efficiently first- and second-order sensitivities in large-scale linear systems: I. Computational methodology vol.284, 2015, https://doi.org/10.1016/j.jcp.2014.12.042
  2. A Novel Reliability-Based Optimal Design of Electromagnetic Devices Based on Adaptive Dynamic Taylor Kriging vol.53, pp.6, 2017, https://doi.org/10.1109/TMAG.2017.2654261
  3. A New Reliability Analysis Algorithm With Insufficient Uncertainty Data for Optimal Robust Design of Electromagnetic Devices vol.51, pp.3, 2015, https://doi.org/10.1109/TMAG.2014.2360753