Automatic synthesis of fault trees from process modelling with application in ship machinery systems

PSAM 2014 - Probabilistic Safety Assessment and Management

Volumn , Issue , 2014, Pages

  Manno, Gabriele ^a   Zymaris, Alexandros S ^a   Kakalis, Nikolaos M P ^a  

^a DNV GL   (Norway)

Author keywords

Dynamic reliability; Fault trees; Flow sheet models; Hybrid automata; Markov chains

Indexed keywords

BRIDGES; FAULT TREE ANALYSIS; FORESTRY; MACHINERY; MARKOV PROCESSES; PROCESS ENGINEERING; SPACE RESEARCH;

DYNAMIC RELIABILITY; FAULT-TREES; FLOW SHEET; FUNCTIONAL DEPENDENCY; HYBRID AUTOMATONS; INPUT-OUTPUT RELATIONS; SEPARATION OF CONCERNS; STATE SPACE EXPLORATION;

SAFETY ENGINEERING;

ALGORITHMS; FAILURE; MATHEMATICAL MODELS; SAFETY;

EID: 84925061927     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (56)

1. Guidelines for Formal Safety Assessment (FSA) for use in the IMO rulemaking process. IMO, 2002: MSC/Circ. 1023-MEPC/Circ.392, IMO2002.
2. Villemeur, A., Reliability, Availability, Maintainability and Safety Assessment: Methods and Techniques Vol. 1. 1992: John Wiley & Sons.
3. Rausand, M. and A. Høyland, System Reliability Theory: Models, Statistical Methods and Applications. 2nd ed: John Wiley & Sons.
4. Haasl, D.F., et al., Fault Tree Handbook, 1981, Nuclear Regulatory Commission, Washington, DC (USA). Office of Nuclear Regulatory Research.
5. Recht, J.L., Failure Mode and Effect. National Safety Council, 1966.
6. nd edition 1996, Elsevier.
7. Dunjóa, J., et al., Hazard and operability (HAZOP) analysis. A literature review. Journal of Hazardous Materials, 2010. 173(1-3): p. 19-32.
8. Lawley, H.G., Operability study and hazards analysis. Chem. Eng. Progress, 1974. 70: p. 45-56.
9. Papadopoulos, Y., et al., Engineering failure analysis and design optimisation with HiP-HOPS. Engineering Failure Analysis, 2011. 18: p. 590-608.
10. Papadopoulos, Y. and U. Petersen, Combining ship machinery system design and first principle safety analysis, in 8th Int. Marine Design Conference (IMDC03)2003: Athens, Greece.
11. Soares CG, et al., Risk-Based Ship Design: Methods, Tools and Applications. Papanikolaou A.D., Ed. Berlin, Germany: Springer-Verlag, 2009.
12. Papadopoulos, Y. and C. Grante, Evolving car designs using model-based automated safety analysis and optimisation techniques. The Journal of Systems and Software, 2005. 76(1): p. 77-89.
13. Joshi, A. et al., Automatic Generation of Static Fault Trees from AADL Models. In Proceedings of the IEEE/IFIP Conference on Dependable Systems and Networks' Workshop on Dependable Systems, DSN07-WADS, Edinburgh Scotland-UK, June 2007.
14. Prosvirnova, T. et al., The Altarica 3.0 project for Model-Based Safety Assessment. Safety, reliability and Risk Analysis: Beyond the Horizon 2013. Proceedings of ESREL conference, Amsterdam, The Netherlands, 2013.
15. Pai, G.J. and Dugan, J.B., Automatic Synthesis of Dynamic Fault Trees from UML System Models. In Proceedings of the 13th International Symposium on Software Reliability Engineering, Annapolis, MD, pp. 243-256, 2002.
16. Poucet, A., STARTS: Knowledge Based Tools for safety and reliability Analysis. Reliability Engineering and System Safety 30 (1990) 379-97.
17. Xie, G, Xue, D., and Xi, S., TREE-EXPERT: A tree-based expert system for Fault Tree construction. Reliability Engineering and System Safety 40 (1993) 295-309.
18. Bozzano, M., and Villafiorita, A., Improvong System reliability via Model Checking: The FSAP/NuSMV-SA Safety Analysis Platform. Lecture notes in Computer Science 2788 (2003) 49-62.
19. Baier, C. and Katoen, J.P., Principles of Model Checking. MIT Press, 2008.
20. Alur, R., et al., Hybrid Automata: An algorithmic approach to the specification and verification of hybrid systems. Lecture Notes in Computer Science 736 (1993) 209-29.
21. Davis, M., Markov models and optimization. London: Chapman and Hall, 1993.
22. Sahner, R., Trivedi, K.S., and Pulifiato, A., Performance and reliability analysis of computer systems. Kluwer Academic Publishers, Boston, MA, 1996.
23. C.C. Pantelides, Z.E. Urban. Process Modelling Technology: A critical review of recent developments. 6th International Conference on Foundations of Computer-Aided Process Design (FOCAPD), Princeton, New Jersey, USA, 2004.
24. K.-U. Klatt, W. Marquardt. Perspectives for process systems engineering-Personal views from academia and industry. Computers & Chemical Engineering. 33 (2009) 536-50.
25. G Stephanopoulos, GV. Reklaitis. Process systems engineering: From Solvay to modern bio- and nanotechnology.: A history of development, successes and prospects for the future. Chemical engineering science. 66 (2011) 4272-306.
26. Kartson, D., Balbo, G, Donatelli, S., Franceschinis, G, and Conte, G, Modelling with Generealized Stochastic Petri Nets. John Willey & Sons, NY, USA, 1994.
27. Sanders W H. Construction and Solution of performability model based on stochastic activity networks. PhD Thesis, University of Michigan, 1988.
28. Walker, M.D., and Papadopoulos, Y.I., Pandora: The Time of Priority AND gates. In INCOM 2006, France, pp. 237-242, 2006.
29. Chiacchio, F., Compagno, L., D'Urso, D., Manno, G., and Trapani, N., Dynamic Fault Trees resolution: A conscious trade-off between analytical and simulative approaches. Reliability Engineering and System Safety 96 (11), 2011, 1515-26.
30. Manno, G., Chiacchio, F., Compagno, L., D'Urso, D., and Trapani, N., Conception of Reparaible Dynamic Fault Trees and resolution by the use of RAATSS, a Matlab toolbox based on the ATS formalism. Reliability Engineering and System Safety 121 (2014) 250-262.
31. Kakalis, N.M.P., G.G. Dimopoulos, and E. Ovrum, COSSMOS, model development and implementation I: Complex Ship Systems Modelling and Simulation, 2009, Det Norske Veritas.
32. Kakalis, N.M.P., et al., COSSMOS, model development and implementation II. DNV, 2010.
33. Kakalis, N.M.P., et al., COSSMOS, model development and implementation III. DNV, 2011.
34. Dimopoulos, G.G. and N.M.P. Kakalis. An integrated modelling framework for the design, operation and control of marine energy systems in Proc. of 26th CIMAC, 2010, Bergen, Norway.
35. Dimopoulos, G.G., C.A. Georgopoulou, and N.M.P. Kakalis. Modelling and optimisation of an integrated marine combined cycle system. in Proc. of 24th Int. Conf. on Energy, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS). 2011. Novi-Sad, Serbia.
36. Kakalis, N.M.P. and G. Dimopoulos. Managing the complexity of marine energy systems. Position Paper 11/2012, Det Norske Veritas, Research & Innovation, (available at: www.dnv.com).
37. gPROMS. Available from: www.psenterprise.com/gproms.
38. OREDA: offshore reliability data, 4th edition. SINTEF Industrial management, 2002.
39. Siu, N., Risk assessment for dynamic systems: An overview. Reliability Eng. and System Safety, 1994. 43: p. 43-73.
40. Henzinger, T.A., The theory of hybrid automata. In Proc. of the 11th Annual IEEE Symposium on Logic in Computer Science, LICS '96, pp. 278-292, New Brunswick, New jersey, 1996.
41. Stochastic Hybrid Systems ed. C.G. Cassandras and J. Lygeros2007: Taylor & Francis.
42. Labeau, P.E., Probabilistic Dynamics: Estimation of generalized unreliability through efficient Monte-Carlo simulation. Ann. Nucl. Energy, 1996. 23(No. 17): p. 1355-1369.
43. Smidts, C., Probabilistic Dynamics: a comparison between continuous event trees and discrete event tree model. Reliability Eng. and System Safety, 1994. 44: p. 189-206.
44. Devooght, J., Dynamic reliability. Adv. in Nuclear Science and Technology, 1997. 25.
45. Marseguerra, M., et al., A concept paper on dynamic reliability via Monte Carlo simulation. Mathematics and Computers in Simulation, 1998. 47: p. 371-382.
46. Kopustinskas V., Augutis J. and Rimkevičius S., Dynamic reliability and risk assessment of the accident localization system of Ingalina NPP RBMK-1500 reactor. Reliability Eng. and System Safety, 2005. 87: p.77-87.
47. Labeau, P.E., A Monte-Carlo estimation of the marginal distributions in a problem of probabilistic dynamics. Reliability Eng. and System Safety, 1996. 52: p. 65-75.
48. Lewis, E.E. and F. Böhm, Monte carlo simulation of Markov unreliability models. Nuclear Eng. And Design, 1984. 77(49-62).
49. Podofillini, L., et al., Dynamic safety assessment: Scenario identification via a possibilistic clustering approach. Reliability Eng. And System Safety, 2010. 95: 534-549.
50. Mercurio, D., et al., Identification and classification of dynamic event tree scenarios via possibilistic clustering: Application to a steam generator tube rupture event. Accident Analysis and Prevention, 2009. 41: 1180-1191.
51. Horton, G., et al., Fluid Stochastic Petri Nets: Theory, Applications, and Solution, January 1996, NASA: Langley Research Center Hampton, Virginia 23681-0001.
52. Trivedi, K.S. and V.G. Kulkarni. FSPNs: Fluid Stochastic Petri Nets. in 14th Int. Conference on Application and Theory of Petri Nets June 1993. Chicago, Illinois, USA: Springer-Verlag.
53. Ciardo, G., D.M. Nicol, and K.S. Trivedi, Discrete-Event Simulation of Fluid Stochastic Petri Nets. Software Engineering, IEEE Transactions on, 1999. 25(2): p. 207-217.
54. Manno, G., Zymaris, A., Kakalis, N.M.P., Chiacchio, F., Cipollone, F.E., Compagno, L., D'Urso, D., and Trapani, N., Dynamic reliability analysis of three nonlinear aging components with different failure modes characteristics. Safety, reliability and Risk Analysis: Beyond the Horizon 2013. Proceedings of ESREL conference, Amsterdam, The Netherlands, 2013.
55. Yang, X. and M.S. Mannan, The development and application of dynamic operational risk assessment in oil/gas and chemical process industry. Reliability Eng. and System Safety, 2010. 95: p. 806-815.
56. Domínguez-García, A.D., et al., An integrated methodology for the dynamic performance and reliability evaluation of fault-tolerant systems. Reliability Eng. and System Safety, 2008. 93: p.1628-1649.