A Study on Uncertainty Analyses of Monte Carlo Techniques Using Sets of Double Uniform Random Numbers

  • Lee, Dong Kyu (Institute of Structural Mechanics, University of Stuttgart) ;
  • Sin, Soo Mi (Department of Architecture, Pusan National University)
  • Received : 2005.09.08
  • Published : 2006.12.30

Abstract

Structural uncertainties are generally modeled using probabilistic approaches in order to quantify uncertainties in behaviors of structures. This uncertainty results from the uncertainties of structural parameters. Monte Carlo methods have been usually carried out for analyses of uncertainty problems where no analytical expression is available for the forward relationship between data and model parameters. In such cases any direct mathematical treatment is impossible, however the forward relation materializes itself as an algorithm allowing data to be calculated for any given model. This study addresses a new method which is utilized as a basis for the uncertainty estimates of structural responses. It applies double uniform random numbers (i.e. DURN technique) to conventional Monte Carlo algorithm. In DURN method, the scenarios of uncertainties are sequentially selected and executed in its simulation. Numerical examples demonstrate the beneficial effect that the technique can increase uncertainty degree of structural properties with maintaining structural stability and safety up to the limit point of a breakdown of structural systems.

Keywords

References

  1. Ulam, S., Richtmyer, R. D. & von Neumann, J. Statistical methods in neutron diffusion. Los Alamos Scientific Laboratory report LAMS-551
  2. Hart, G. C. (1982) Uncertainty analysis, loads, and safety in structural engineering. Prentice-Hall, Englewood Cliffs, New Jersey
  3. D.E. Kunth (1981) The Art of Computer Programming Vol. 2: Seminumerical Methods. Addison-Wesley, Reading, Mass
  4. Klir, G. J. & Folger, T. A. (1988) Fuzzy set. Uncertainty and information. Prentice-Hall International
  5. Gould, H. & Tobochnik, J. (1988) An Introduction to Computer Simulation Methods. Vol. 2, Addison-Wesley, Reading, Mass
  6. Binder K. & Heermann, D. W. (1988) Monte Carlo Simulation in Statistical Physics. Springer-Verlag, Berlin
  7. Kim U. H. & Yoo Y. H. (1999) Matrix Structural Analysis. Kong-Sung
  8. Geschwindner, L. F. & Disque, R.O. (1994) Load and Resistance Factor Design of Steel Structures. Prentice- Hall, Inc. Englewood Cliffs, N.J
  9. Sen, M. & Powers, J. (2001) LECTURE NOTES ON 24. MATHEMATICAL METHODS. pp.86-109
  10. Metropolis, N. & Ulam S.M. (1949) 'The Monte Carlo method.' J. Am. Statistical Association, Vol. 44
  11. Noh, H. I. (1998) Reinforce Concrete Structure. Sanup-Dose, pp.17-18
  12. Dwyer, P.S. (1951) Linear Computation. Wiley
  13. Bevington, P. R. (1969) Data Reduction and Error Analysis for the Physical Sciences. McGraw-Hill, New York
  14. Chen, S. H. & Yang, X. W. (2000) 'Interval finite element method for beam structures.' Finite Elements in Analysis and Design, Vol. 34, pp.75-88 https://doi.org/10.1016/S0168-874X(99)00029-3
  15. Yang, T. Y. (1986) Finite Element Structural Analysis. Prentice-Hall, Inc. Englewood Cliffs, N.J