• 검색어에 아래의 연산자를 사용하시면 더 정확한 검색결과를 얻을 수 있습니다.
  • 검색연산자
검색연산자 기능 검색시 예
() 우선순위가 가장 높은 연산자 예1) (나노 (기계 | machine))
공백 두 개의 검색어(식)을 모두 포함하고 있는 문서 검색 예1) (나노 기계)
예2) 나노 장영실
| 두 개의 검색어(식) 중 하나 이상 포함하고 있는 문서 검색 예1) (줄기세포 | 면역)
예2) 줄기세포 | 장영실
! NOT 이후에 있는 검색어가 포함된 문서는 제외 예1) (황금 !백금)
예2) !image
* 검색어의 *란에 0개 이상의 임의의 문자가 포함된 문서 검색 예) semi*
"" 따옴표 내의 구문과 완전히 일치하는 문서만 검색 예) "Transform and Quantization"
쳇봇 이모티콘
ScienceON 챗봇입니다.
궁금한 것은 저에게 물어봐주세요.

논문 상세정보


Descriptive sampling (DS) is an alternative to crude Monte Carlo sampling (CMCS) in finding solutions to structural reliability problems. It is known to be an effective sampling method in approximating the distribution of a random variable because it uses the deterministic selection of sample values and their random permutation. However, because this method is difficult to apply to complex simulations, the sample size is occasionally determined without thorough consideration. Input sample variability may cause the sample size to change between runs, leading to poor simulation results. This paper proposes a numerical method for choosing a suitable sample size for use in DS. Using this method, one can estimate a more accurate probability of failure in a reliability problem while running a minimal number of simulations. The method is then applied to several examples and compared with CMCS and conventional DS to validate its usefulness and efficiency.

참고문헌 (30)

  1. D. H. Evans, An application of numerical integration techniques to statistical tolerancing, Technometrics, 9 (3) (1967) 441-456. 
  2. H. S. Seo and B. M. Kwak, Efficient statistical tolerance analysis for general distributions using three-point infonnation, International Journal of Production Research, 40 (4) (2000) 931-944. 
  3. J. H. Min, Reliability analysis technique using local approximation of cumulative distribution Function, MS. Thesis, Hanyang University, Korea, (2005). 
  4. A. D. Kiureghian, H. Z. Lin and S. J. Hwang, Second order reliability analysis approximations, Journal of Engineering Mechanics, 113 (8) (1987) 1208-1225. 
  5. B. Fiessler, H. J. Neumann and R, Rackwitz, Quadratic limit states in structural reliability, Journal of Engineering Mechanics, 1095 (4) (1979) 661-676. 
  6. C. A. Comell, A probability-based structural code, Journal of the American Concrete Institute, 66 (12) (1969) 974-985. 
  7. O. S. Lee, D. H. Kim and Y. C. Park, Reliability of structures by using probability and fatigue theories, Journal of Mechanical Science and Technology, 22 (4) (2008) 672-682. 
  8. S. J. Yoon and D. H. Choi, Reliability-based design optimization of slider air bearings, Journal of Mechanical Science and Technology, 18 (10)(2004) 1722-1729. 
  9. A. H. Ang and W. H. Tang, Probability concepts in engineering planning and design, John Wiley & Sons, New York, USA, (1984). 
  10. A. Harbitz, An efficient sampling method for probability of failure calculation, Structural Safety, 3 (1986) lO9-115. 
  11. N. P. Buslenko, D. I. Golenko, Y. A. Shreider, I. M. Sobol and V. G. Sragowich, The Monte Carlo method, Pergamon Press, New York, USA, (1964). 
  12. M. L. Shooman, Probability reliability: An engineering approach, McGraw-Hill, New York, USA, (1968). 
  13. R. E. Melcher, Structural reliability: Analysis and Prediction, Ellis Horwood, (1987). 
  14. E. Saliby, A reappraisal of some simulation fundamentals, Ph.D. Thesis, University of Lancaster, (1980). 
  15. E. Saliby, Descriptive sampling: A better approach to Monte Carlo simulation, Journal of the Operational Research Society, 41 (12) (1990) 1133-1142. 
  16. E. Saliby, Rethinking simulation: descriptive sampling, Sao Paulo: Atlas/EDUFRJ, Portuguese, (1989). 
  17. G. S. Fishman, Monte-Carlo: Concepts, algorithms and applications, Springer-Vedag, (1997). 
  18. K. W. Ross, D. Tsang and J. Wang, Monte-Carlo summation and integration applied to multichain Queueing networks, Journal Association Computer Machine, 41 (6) (1994) 1110-1135. 
  19. K. Ziha, Descriptive sampling in structural safety, Structural Safety, 17 (1995) 33-41. 
  20. B. A. Cullimore, Dealing with uncertainties and variations in thermal design, Proceedings of InterPack '01 Pacific Rim International Electronic Packaging Conference, Kauai, Hawaii (2001). 
  21. D. J. McCormick and J. R. Olds, A design of experimentsbased method for point selection in approximating output distributions, 2002 AIAAlISSMO Symposium on Multidisciplinary Analysis and Design Optimization, Atlanta, GA (2002). 
  22. E. Saliby and F. Pacheco, An empirical evaluation of sampling methods in risk analysis simulation: Quasi-Monte Carlo, descriptive sampling and Latin Hypercube Sampling, Proceedings of the 2002 Winter Simulation Conference, 1606-16l0 (2002). 
  23. J. Staum, S. Ehrlichman and V. Lesnevski, Work reduction in financial simulations, Proceedings of the 2003 Winter Simulation Conference (2003). 
  24. R Development Core Team, R(ver. 2.6.1):A language and environment for statistical computing, R Foundation for statistical computing, Vienna, Austria, URL http://www.rproject.project.org., (2007) . 
  25. E. Saliby, Understanding the variability of simulation estimates: an empirical study, Journal of the Operational Research Society, 41 (1990) 319-327. 
  26. E. Saliby and R. J. Paul, Implementing descriptive sampling in three-phase discrete event simulation models, Journal of the Operational Research Society, 44 (1993) 147-160. 
  27. E. Saliby, Input sample size determination when using descriptive sampling, Proceedings 13th International Conference ITI-1991, Dubrovnik, Croatia (1991). 
  28. L. Wang and R. V. Gradhi, Efficient safety index calculation for structural reliability analysis, Computer and Structures, 52 (1) (1994) 103-111. 
  29. Southwest Research Institute, Probabilistic structural analysis methods (PSAM) for select space propulsion .systerns components, NESSUS Version 6.0 release notes, (1992). 
  30. H. Madsen, S. Krenk and N. Lind, Methods of structural safety, Prentice-Hall, (1986). 

이 논문을 인용한 문헌 (1)

  1. 2011. "" Journal of mechanical science and technology, 25(9): 2151~2159 


원문 PDF 다운로드

  • 원문 PDF 정보가 존재하지 않습니다.

원문 URL 링크

원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다. (원문복사서비스 안내 바로 가기)

상세조회 0건 원문조회 0건

DOI 인용 스타일