Multimodal Simulation Method for System Reliability Analysis
Publication: Journal of Engineering Mechanics
Volume 119, Issue 6
Abstract
In system reliability analysis, it is frequently necessary to resort to Monte Carlo simulation (MCS). The importance sampling method (ISM) is an advanced MCS method that may greatly improve the efficiency and accuracy of simulation approaches. Its application to structural system reliability analysis is focused here. Importance of proper determination of the sampling density is emphasized based on a critical review of other suggested sampling densities. A new sampling density, the weighted general normal sampling density (WGNSD), is proposed. This density is proportional to the ideally optimal one at the most important points of the variable space, and it is general for structural system reliability analysis. A variety of applications of this method are presented for illustration, as well as for demonstration of success with the proposed sampling density, including nondifferentiable failure surfaces and higher‐dimensional problems.
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References
1.
Fu, G. (1988). “Error analysis for importance sampling method.” Proc. An NSF Workshop on Research Needs for Applications of System Reliability Concepts and Techniques in Structural Analysis, Design and Optimization, Univ. of Colorado, Boulder, Colo., 132–146.
2.
Fu, G., and Moses, F. (1986). “Application of lifetime system reliability.” Preprint No. 52‐1, ASCE Structures Congress '86, ASCE, New York, N.Y.
3.
Fu, G., and Moses, F. (1987a). “Lifetime system reliability models with application to highway bridges.” Reliability and Risk Analysis in Civil Engineering, Proc. ICASP5, N. C. Lind, ed., Vancouver, Canada, 71–78.
4.
Fu, G., and Moses, F. (1987b). “A sampling distribution for system reliability assessment.” IFIP 1st Working Conf. on Reliability and Optimization of Structural Systems, Aalborg, Denmark, 141–155.
5.
Fu, G., and Moses, F. (1988). “Importance sampling in structural system reliability.” Proc. the 5th ASCE Specialty Conf. Probabilistic Methods in Civil Engineering, ASCE, New York, N.Y., 340–343.
6.
Fushimi, M., and Tezuka, S. (1983). “The k‐distribution of generalized feedback shift register pseudorandom numbers.” Commun. ACM, 26(7), 516–523.
7.
Grigoriu, M., and Turkstra, C. (1979). “Safety of structural systems with correlated resistances.” Appl. Math. Modeling, 3, 130–136.
8.
Hammersley, J. M., and Handscomb, D. C. (1964). Monte Carlo Methods, Methuen & Co. Ltd., London, England.
9.
Kahn, H. (1956). “Use of different Monte Carlo sampling techniques.” Symp. on Monte Carlo Methods, H. A. Meyer, ed., John Wiley & Sons, Inc., New York, N.Y., 146–190.
10.
Kleijnen, J. P. C. (1974). Statistical techniques in simulation: Part I. Marcell Dekker, Inc., New York, N.Y.
11.
Marsaglia, G. (1968). “Random numbers fall mainly in the planes.” Proc. Nat. Acad. Sci., USA 61, 25–28.
12.
Moses, F. (1982). “System reliability developments in structural engineering.” Struct. Safety, 1, 3–13.
13.
“Tables of the bivariate normal distribution function and related functions.” (1959). Appl. Math. Series 50, Nat. Bureau of Standards.
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Copyright © 1993 American Society of Civil Engineers.
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Received: Apr 7, 1992
Published online: Jun 1, 1993
Published in print: Jun 1993
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