Abstract
An entropy-based biasing rule for the guidance of Dynamic PRA simulations is introduced in this paper. The rule aims to continuously adjust itself based on simulation results, in order to guide the simulations towards groups of sequences for which the highest amount of uncertainty exists regarding their end states. The simple rule described in this paper behaves as intended, even though it has limitations that make it unfit for large scale application.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
C. Acosta and N. Siu. Dynamic event trees in accident sequence analysis: application to steam generator tube rupture. Reliability Engineering and System Safety, v41, p135–154, 1993.
Chaloner, K. and Verdinelli, I., Bayesian Experimental Design: A Review, Statistical Science v10 p273–304, 1995.
Cojazzi, G; The DYLAM approach for the dynamic reliability analysis of systems, Reliability Engineering & System Safety, vol. 52, Issue 3, pp.279–296, 1996
Devooght J., Smidts C., Probabilistic reactor dynamics. I. The theory of continuous event trees, Nuclear Science & Engineering vol.111, pp 229–240, 1992.
Hsueh Kae-Sheng and Mosleh A., The development and application of the accident dynamic simulator for dynamic probabilistic risk assessment of nuclear power plants Reliability Engineering & System Safety, vol. 52, Issue 3, pp.297–314, 1996
Labeau, P.E; Smidts, C; Swaminathan, S; Dynamic reliability: towards an integrated platform for probabilistic risk assessment; Reliability Engineering and System Safety, vol. 68 pp. 219–254, 2000
Labeau, P.E.; Zio, E; Biasing schemes in component-based and system-based Monte Carlo algorithms in system engineering, Proceedings of Esre12001 vol.2, pp. 903–910. 2001
Loredo, T.J., Chernoff, D.F., Bayesian Adaptive Exploration, Statistical Challenges in Modern Astronomy III, in press, 2003.
Lindley D.V., On the Measure of Information Provided by an Experiment, Annals of Statistics, v27 p986–1005, 1956.
Maggio, Gaspare, Space Shuttle Probabilistic Risk Assessment: Methodology and Application, Proceedings of the Annual Reliability and Maintainability Symposium, pp. 121-132. 1996
Mosleh, A., et al., Simulation Based Probabilistic Risk Assessment, Technical Report, University of Maryland, College Park, MD, 2003.
Marseguerra, M; Zio, E; Devooght, J; Labeau, P.E. A concept paper on dynamic reliability via Monte Carlo simulation, Mathematics and Computers in Simulation vol. 47:2–5 (1998), pp.371-382, 1998
Siu, N; Risk assessment for dynamic systems: An overview, Reliability Engineering & System Safety, vol. 43, Issue 1,, pp. 43–73, 1994
Smidts C, Devooght J., Probabilistic reactor dynamics. II. A Monte Carlo study of a fast reactor transient, Nuclear Science & Engineering, vol.111, pp 241–256 (1992)
Smidts C., Devooght J. and Labeau P.E., Dynamic Reliability: Future Directions, International Workshop Series on Advanced Topics in Reliability and Risk Analysis, CRE Publication, August 2000.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag London
About this paper
Cite this paper
Hu, Y., Groen, F., Mosleh, A. (2004). An Entropy-Based Exploration Strategy in Dynamic PRA. In: Spitzer, C., Schmocker, U., Dang, V.N. (eds) Probabilistic Safety Assessment and Management. Springer, London. https://doi.org/10.1007/978-0-85729-410-4_384
Download citation
DOI: https://doi.org/10.1007/978-0-85729-410-4_384
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1057-6
Online ISBN: 978-0-85729-410-4
eBook Packages: Springer Book Archive