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Dynamic methodologies for reliability and probabilistic risk assessment (PRA)

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Języki publikacji
EN
Abstrakty
EN
Dynamic methodologies in reliability and PRA are those that explicitly account for the time element in probabilistic system evolution. Dynamic methodologies are usually needed when the system has more than one failure mode, control loops, and/or hardware/process/ software/human interaction. An overview of the dynamic methodologies proposed to date is given, including those that use dynamic event tree generation, continuous time-state space representation, the cell-to-cell mapping technique and graphical schemes. The use of dynamic methodologies for state/parameter estimation in on-line applications is also discussed. Potential on-line use of dynamic methodologies as operator assistance tools for risk informed accident management or normal operation is described and illustrated.
Rocznik
Tom
Strony
7--12
Opis fizyczny
Bibliogr. 47 poz.
Twórcy
autor
  • The Ohio State University, Columbus, Ohio, U.S.A.
Bibliografia
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  • [4] Aldemir, T. (1991). Utilization of the Cell-To-Cell Mapping Technique to Construct Markov Failure Models for Process Control Systems. In: Apostolakis G ed. Elsevier, New York, 1431-1436.
  • [5] Aldemir, T., Miller, D. W., Stovsky, M., Kirschenbaum, J., Bucci, P., Fentiman, A. W. & Mangan, L. M. (2006). Current State of Reliability Modeling Methodologies for Digital Systems and Their Acceptance Criteria for Nuclear Power Plant Assessments. U. S. Nuclear Regulatory Commission, Washington, D.C.
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  • [7] Aldemir, T., Stovsky, M.,P., Kirschenbaum, J., Mandelli, D., Mangan L. A., Miller, D. W., Fentiman, A. W., Ekici, E., Guarro, S., Yau, M., Johnson, B., Elks, C. & Arndt, S. A., (2007). Dynamic Reliability Modeling of Digital Instrumentation and Control Systems for Nuclear Reactor Probabilistic Risk Assessments. U.S. Nuclear Regulatory Commission, Washington, D.C.
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  • [12] Belhadj, M. & Aldemir, T. (1996). Some Computational Improvements in Process System Reliability and Safety Analysis Using Dynamic Methodologies. Reliab Engng & System Safety, 52, 339-347.
  • [13] Belhadj, M., Hassan, M. & Aldemir, T. (1992). On the Need for Dynamic Methodologies in Risk and Reliability Studies. Reliab Engng & System Safety, 38, 219-236.
  • [14] Bucci, P., Kirschenbaum, J., Aldemir, T., Smith, C. L. & Wood, T. S. (2006). Constructing Dynamic Event Trees from Markov Models. In: Stamataletos M, Blackman HS eds. ASME Press, Inc.
  • [15] Bucci, P., Kirschenbaum, J., Aldemir, T., Smith, C. L. & Wood, R. T. (2006). Generating Dynamic Fault Trees from Markov Models.
  • [16] Bucci, P., Mangan, L. A., Kirschenbaum, J., Mandelli, D., Aldemir, T. & Arndt, S. (2006). Incorporation of Markov Reliability Models for Digital Instrumentation and Control Systems into Existing PRAs. American Nuclear Society, La Grange, IL.
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  • [23] Devooght, J., Smidts, C. (1996). Probabilistic dynamics as a tool for dynamic PSA. Reliab Engng & System Safety, 52, 185-196.
  • [24] Dutuit, Y. (1997). Dependability Modeling and Evaluation by Using Stochastic Petri Nets: Application to Two Test Cases, 117-124.
  • [25] Galluzo, M. & Andow, P. K. (1998). Failures in Control Systems. Reliability Engineering, 7, 125-128.
  • [26] Gribaudo, M., Horvaacute, A., Bobbio, A., Tronci, E., Ciancamerla, E. & Minichino, M. (2006). Fluid Petri Nets and Hybrid Model-checking: A Comparative Case Study, 239-257.
  • [27] Guarro, S., Yau, M. & Motamed, M. (1996). Development of Tools for safety Analysis of Control Software in Advanced Reactors, U.S. Nuclear Regulatory Commission, Washington, D.C.
  • [28] Hassan, M. & Aldemir, T. (1990). A Data Base Oriented Dynamic Methodology for the Failure Analysis of Closed Loop Control Systems in Process Plants. Reliability Engineering & System Safety, 27, 275-322.
  • [29] Izquierdo, J. M., Hortal, J., Sanches-Perea, J. & Melendez, E. (1994). Automatic Generation of Dynamic Event Trees: A Tool for Integrated Safety Assessment. In: Aldemir T, Siu N, Mosleh A, Cacciabue PC, Goktepe BG eds. Springer-Verlag, Heidelberg, 135-150.
  • [30] Kae-Sheng, H. & Mosleh, A. (1996). The Development and Application of the Accident Dynamic Simulator for Dynamic Probabilistic Risk Assessment of Nuclear Power Plants. Reliability Engineering & System Safety, 52, 297-314.
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  • [32] Kumamoto, H., Henley, E. J. & Inoue, K. (1981). Signal-flow-based graphs for failure mode analysis of systems with control loops. IEEE Trans Reliability, R-30, 110-116.
  • [33] Labeau, P. (1996). Probabilistic Dynamics: Estimation of Generalized Unreliability through Efficient Monte Carlo Simulation. Ann Nucl Energy, 23,1355-1369.
  • [34] Labeau, P. (2006). A survey on Monte Carlo estimation of small failure risks in dynamic reliability. International Journal of Electronics and Communication, 52, 205-211.
  • [35] Lajeunesse, S., Hutinet, T. & Signoret, J. P. (1996). Automatical fault trees generation on dynamic systems. In: Cacciabue PC, Papazoglou IA eds. Probabilistic Safety Assessment and Management, Springer-Verlag, New York, 1553-1559.
  • [36] Marchand, S., Tombuyes, B. & Labeau, P. (1998). DDET and Monte Carlo Simulation to Solve Some Dynamic Reliability Problems. In: Cacciabue PC, Papazoglou IA eds. Probabilistic Safety Assessment and Management, Springer-Verlag, New York, 2055-2060.
  • [37] Marseguerra, M. & Zio, E. (1996). Monte Carlo Approach to PSA for Dynamic Process Systems. Reliability Engineering & System Safety, 52, 227-241.
  • [38] Matsuoka, T. & Kobayashi, M. (1988). GO-FLOW: A New Reliability Analysis Methodology. Nuclear Science and Engineering, 98, 64-78.
  • [39] Matsuoka, T. & Kobayashi, M. (1991). An Analysis of a Dynamic System by the GO-FLOW Methodology. In: Cacciabue PC, Papazoglou IA eds. Probabilistic Safety Assessment and Management '96, Elsevier, New York, 1547-1436.
  • [40] Munteanu, I. & Aldemir, T. (2003). A Methodology for Probabilistic Accident Management. Nucl Technol, 144, 49-62.
  • [41] Senni S., Semenza S. M. & Galvani R. (1991). A.D.M.I.R.A. - An analytical dynamic methodology for integrated risk assessment, In: Apostolakis G ed. Probabilistic Safety Assessment and Management, Elsevier Science Publishing Co., New York, 413-418.
  • [42] Swaminathan S., Smidts C. (1999). The Mathematical Formulation of the Event Sequence Diagram Framework, 103-118.
  • [43] Tombuyes, B. & Aldemir, T. (1996). Dynamic PSA of Process Control-Systems Via Continuous Cell-To-Cell-Mapping, Probabilistic Safety Assessment and Management PSAM3. Elsevier, New York, 1541-1546.
  • [44] U. S. Nuclear Regulatory Commission. (1975). Reactor Safety Study − An Assessment of Accident Risks in U.S. Commercial Nuclear Power Plants, In: WASH-1400 (NUREG-75/014) ed. US Nuclear Regulatory Commission, Washington, D.C.
  • [45] Wang, P., Chen, X. M. & Aldemir, T. (2002). DSD: A Generic Software Package For Model-based Fault Diagnosis in Dynamic Systems. Reliability Engineering & System Safety, 75, 31-39.
  • [46] Yau, M. (1997). Dynamic Flowgraph Methodology for the Analysis of Software Based Controlled Systems. University of California, Los Angeles.
  • [47] Nuclear Energy Ageny (2005). Technical Opinion Paper on the Development and Use of Risk Monitors at Nuclear Power Plants, Organization for Economic Co-Operation And Development. Paris, France.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-36cdb2b0-c300-440a-ba32-f1c5a83983ec
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