By Nathan O. Siu (auth.), Tunc Aldemir, Nathan O. Siu, Ali Mosleh, P. Carlo Cacciabue, B. Gül Göktepe (eds.)
Current concerns and methods within the reliability and safeguard research of dynamic approach platforms are the topic of this publication. The authors of the chapters are specialists from nuclear, chemical, mechanical, aerospace and safety process industries, and from associations together with universities, nationwide laboratories, inner most consulting businesses, and regulatory our bodies. either the normal ways and dynamic methodologies which explicitly account for the time point in process evolution in failure modeling are represented. The papers on traditional techniques be aware of the modeling of dynamic results and the necessity for better equipment. The dynamic methodologies coated contain the DYLAM technique, the idea of continuing occasion timber, a number of Markov version development systems, Monte Carlo simulation, and usage of common sense flowgraphs at the side of Petri nets. precise emphasis is put on human elements comparable to systems and training.
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On the contrary, if the system behaviour is strongly sensitive to the process variables values, then any reliability analysis should properly take into account these dynamic aspects and therefore a dynamic PRA approach is almost mandatory. Unfortunately this approach introduces a great deal of difficulties, essentially due to the fact that while the classical methods may be carried out in terms only of the hardware stochastic characteristics, now, for each hardware configuration, a suitable model for the process variables evolution must be introduced.
6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. : Dynamic Probabilistic Systems. Vols. G. : Finite Markov Chains. D. : Loss Prevention in the Process Industries. Vol. 1, Butterworths, Guilford, UK, 1986, Chapter 7 Henley, E. : Probabilistic Reliability: An Engineering Approach. McGraw-Hill (1969) Singh, C. : System Reliability Modeling and Evaluation. S. : Engineering Reliability: New Techniques and Applications. : Reliability Modeling in Electric Power Systems. , Carnino, A. : Use of Markov Processes for Reliability Problems.
6000 7000 42 References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. : Dynamic Probabilistic Systems. Vols. G. : Finite Markov Chains. D. : Loss Prevention in the Process Industries. Vol. 1, Butterworths, Guilford, UK, 1986, Chapter 7 Henley, E. : Probabilistic Reliability: An Engineering Approach. McGraw-Hill (1969) Singh, C. : System Reliability Modeling and Evaluation. S. : Engineering Reliability: New Techniques and Applications. : Reliability Modeling in Electric Power Systems. , Carnino, A.