Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
권호 표지

Quantification of Entire Change of Distributions Based on Normalized Metric Distance for Use in PSAs

  • Published : 2001.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

A simple measure of uncertainty importance based on normalized metric distance to quantify the entire change of cumulative distribution functions (CDFs) has been developed for use in probability safety assessments (PSAs). The metric distance measure developed in this study reflects the relative impact of distributional changes of inputs on the change of an output distribution, white most of the existing uncertainty importance measures reflect the magnitude of relative contribution of input uncertainties to the output uncertainty. Normalization is made to make the metric distance measure a dimensionless quantity. The present measure has been evaluated analytically for various analytical distributions to examine its characteristics. To illustrate the applicability and strength of the present measure, two examples are provided. The first example is an application of the present measure to a typical problem of a system fault tree analysis and the second one is for a hypothetical non-linear model. Comparisons of the present result with those obtained by existing uncertainty importance measures show that the metric distance measure is a useful tool to express the measure of uncertainty importance in terms of the relative impact of distributional changes of inputs on the change of an output distribution.

Keywords

References

  1. K. Nakashima and K. Yamato, 'Variance-importance of system components,' IEEE Transactions on Reliability, R-31(1), (1982)
  2. V. M. Bier, 'A measure of uncertainty importance for components in fault trees,' Transactions of the American Nuclear Society, 45(1), 384 (1983)
  3. S. C. Hora and R. L. Iman, 'A Comparison of Maxiums/Bounding and Bayes/Monte Carlo for Fault Tree Uncertainty Analysis,' SAND85-2839, Sandia National Laboratories (1986)
  4. R. L. Iman, 'A matrix-based approach to uncertainty and sensitivity analysis for fault trees,' Risk Analysis, 7(1), 21 (1987) https://doi.org/10.1111/j.1539-6924.1987.tb00966.x
  5. J. C. Helton, R. L. Iman, J. D. Johnson, and C. D. Leigh, 'Uncertainty and sensitivity analysis of a model for multicomponent aerosol dynamics,' Nuclear Technology, 73, 320 (1986)
  6. R. S. Andsten and J. K. Vaurio, 'Sensitivity, uncertainty, and importance analysis of a risk assessment,' Nuclear Technology, 98, 160 (1992)
  7. R. L. Iman and S. C. Hora, 'A robust measure of uncertainty importance for use in fault tree system analysis,' Risk Analysis, 10(3), 401 (1990) https://doi.org/10.1111/j.1539-6924.1990.tb00523.x
  8. M. Khatib-Rahbar, E. Cassolil, M. Lee, H. Nourbakhsh, R. Davis, and E. Schmidt, 'A probabilistic approach to quantifying uncertainties in the progression of severe accidents,' Nuclear Science and Engineering, 102, 219 (1989)
  9. C. K. Park and K. I. Ahn, 'A new approach for measuring uncertainty importance and distributional sensitivity in probabilistic safety assessment,' Reliability Engineering and System Safety, 46, 253 (1994) https://doi.org/10.1016/0951-8320(94)90119-8
  10. G. J. Klir and T. A. Folger, Fuzzy Sets, Uncertainty and Information, Prentice Hall, New Jersey, (1988)
  11. S. J. Han, Uncertainty analysis methods for quantification of source terms using a large computer code, Ph. D. dissertation, KAIST, (1996)
  12. T. Ishigami and T. Homma, 'An importance quantification technique in uncertainty analysis for computer models,' Proceedings of the ISUMA '90, First International Symposium on Uncertainty Modeling and Analysis, University of Maryland, USA, 3-5, pp.398-403 (December 1990)
  13. T. Homma and A. Saltelli, 'Use of Sobol's Quasirandom Sequence Generator for Integration of Modified Uncertainty Importance Measure,' Journal of Nuclear Science and Technology, 32, 1164 (1995)
  14. T. Homma and A. Saltelli, 'Importance measures in global sensitivity analysis of nonlinear models,' Reliability Engineering and System Satety, 52, 1 (1996) https://doi.org/10.1016/0951-8320(96)00002-6