Dependability of Engineering Systems

A Markov Minimal Cut Approach
 
 
Springer (Verlag)
  • erscheint ca. am 20. Juni 2020
 
  • Buch
  • |
  • Hardcover
  • |
  • XXVI, 162 Seiten
978-3-030-38326-8 (ISBN)
 
This book provides an in-depth understanding of precise and approximate MMC modeling and calculation techniques of engineering systems. The in-depth analysis demonstrates that it is only possible to precisely model and calculate the dependability of systems including s-dependent components with the knowledge of their (total) universe spaces, represented here by Markov spaces. They provide the basis for developing and verifying approximate MMC models. With the mathematical steps described and applied to several examples throughout this text, interested system developers and users can perform dependability analyses themselves. All examples are structured in precisely the same way.
1st ed. 2020
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • Für Beruf und Forschung
  • 2 s/w Abbildungen, 100 farbige Tabellen, 74 farbige Abbildungen
  • |
  • 100 Tables, color; 74 Illustrations, color; 2 Illustrations, black and white; XXVI, 162 p. 76 illus., 74 illus. in color.
  • Höhe: 23.5 cm
  • |
  • Breite: 15.5 cm
978-3-030-38326-8 (9783030383268)
10.1007/978-3-030-38327-5
weitere Ausgaben werden ermittelt
Hans-Dieter Kochs was head of the Chair of Computer Engineering and Information Logistics at the University Duisburg-Essen, Germany. He received a Diploma-Degree in Electrical Engineering (1972) and a Dr.-Ing. Degree (1976) from the Technical University (RWTH) Aachen, Germany. From 1972 to 1979 he was a member of the Institute of Power Systems and Power Economics (IAEW) at the RWTH Aachen (Prof. K.W. Edwin) as a research assistant. From 1979 to 1991 he held leading positions in industry (AEG/Daimler Frankfurt, FAG Kugelfischer Erlangen, and ESWE Wiesbaden, Germany). Since 1991 he has been a full Professor. From 1972 to the present day, he has been engaged in scientific and industrial dependability analyses and studies.
ContentPrefaceList of figuresList of tablesList of symbols and abbreviations1 Example 1: Reference example1.1 Mathematical foundation for the integration of Markov minimalcuts (MMC)1.2 Precise modeling of the MMC and the system up and downstate1.3 Precise calculation of the Markov models1.4 Approximate modeling of the MMC1.5 Approximate calculation of the MMC models with the pMpapproach1.6 Equivalent DBD based on MC1.7 Results1.8 Extension1.9 Remark to deviations - Model accuracy1.10 Preliminary research and related terms and methods2 Example 2.1 and 2.2: Parallel-to-series structure2.1 Example 2.1: Multiple common cause failures (CCF)2.1.1 Precise modeling of the MMC and the system up anddown state2.1.2 Approximate modeling of the MMC2.1.3 Approximate calculation of the MMC models with thepMp approach2.1.4 Equivalent DBD based on MC2.1.5 Results2.2 Example 2.2: Mix of s-dependencies2.2.1 Precise modeling of the MMC and the system up anddown state2.2.2 Approximate modeling of the MMC2.2.3 Approximate calculation of the MMC models with thepMp approach2.2.4 Equivalent DBD based on MC2.2.5 ResultsChapter x 617.10.20193 Example 3.1 and 3.2: Series-to-parallel structure3.1 Example 3.1: Multiple common cause failures (CCF)3.1.1 Precise modeling of the MMC and the system up anddown state3.1.2 Approximate modeling of the MMC3.1.3 Approximate calculation of the MMC models with thepMp approach3.1.4 Equivalent DBD based on MC3.1.5 Results3.2 Example 3.2: Mix of s-dependencies3.2.1 Precise modeling of the MMC and the system up anddown state3.2.2 Approximate modeling of the MMC3.2.3 Approximate calculation of the MMC models with thepMp approach3.2.4 Equivalent DBD based on MC3.2.5 Results4 Example 4: 4-out-of-4 (4oo4)4.1 Precise modeling of the MMC and the system up and downstate4.2 Approximate modeling of the MMC4.3 Approximate calculation of the MMC models with the pMpapproach4.4 Equivalent DBD based on MC4.5 Results5 Example 5: 3-out-of-4 (3oo4)5.1 Precise modeling of the MMC and the system up and downstate5.2 Approximate modeling of the MMC5.3 Approximate calculation of the MMC models with the pMpapproach5.4 Equivalent DBD based on MC5.5 Results6 Example 6.1 and 6.2: 2-out-of-4 (2oo4)6.1 Example 6.1: Multiple common cause failures (CCF)6.1.1 Precise modeling of the MMC and the system up anddown state6.1.2 Approximate modeling of the MMCChapter x 717.10.20196.1.3 Approximate calculation of the MMC models with thepMp approach6.1.4 Equivalent DBD based on MC6.1.5 Results6.2 Example 6.2: Mix of s-dependencies6.2.1 Precise modeling of the MMC and the system up anddown state6.2.2 Approximate modeling of the MMC6.2.3 Approximate calculation of the MMC models with thepMp approach6.2.4 Equivalent DBD based on MC6.2.5 Results7 Example 7: 1-out-of-4 (1oo4)7.1 Precise modeling of the MMC and the system up and downstate7.2 Approximate calculation of the MMC models with the pMpapproach7.3 Equivalent DBD based on MC7.4 Results8 Conclusion and overall assessment9 AppendixAppendix 9.1Appendix 9.2Appendix 9.3Appendix 9.4Appendix 9.5Appendix 9.6Appendix 9.710 Reference
This book provides an in-depth understanding of precise and approximate MMC modeling and calculation techniques of engineering systems. The in-depth analysis demonstrates that it is only possible to precisely model and calculate the dependability of systems including s-dependent components with the knowledge of their (total) universe spaces, represented here by Markov spaces. They provide the basis for developing and verifying approximate MMC models. With the mathematical steps described and applied to several examples throughout this text, interested system developers and users can perform dependability analyses themselves. All examples are structured in precisely the same way.

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