Systems Dependability Assessment


Benefits of Petri Net Models


Volume 1 – Systems Dependability Assessment SET Coordinated by Jean-François Aubry

Systems Dependability Assessment

Jean-François Aubry and Nicolae Brinzei, University of Lorraine, France
Mohammed-Habib Mazouni, Alstom Transport


ISBN : 9781848219915

Publication Date : February 2016

Hardcover 282 pp

135.00 USD

Co-publisher

Description


In addition to highlighting the benefits of the use of Petri Nets (PN) in systems dependability studies, this book, which is divided into four parts, also shows the risk analysis step for probabilistic assessment of RAMS.

In the first part, the basic models of Petri Nets and some useful extensions are briefly recalled. In the second part, Petri Nets are used as a formal model for describing the evolution process of a critical system in the framework of an ontological approach. The third part focuses on Stochastic Petri Nets (SPN) and their use in dependability assessment. Different formal models of Stochastic Petri Nets are formally presented (semantics, evolution rules, etc.) in addition to their equivalence with the corresponding class of Markov processes in order to obtain an analytical assessment of dependability. Simplification methods are proposed so as to reduce the size of the analytical model and thus make it more calculable. The introduction of some concepts specific to high-level Petri Nets also allows the consideration of complex systems. In the fourth part, five examples of industrial systems modeling are presented, stemming from collaborations with large industrial companies in various application areas.

Contents


1. Autonomous Petri Nets.
2. Petri Nets and Event Languages.
3. Comparison Petri Nets – Finite State Automaton.
4. Some Extensions of Petri Nets.
5. Ontology-based Accidental Process.
6. Petri Net Modeling of the Accidental Process.
7. Illustrative Example.
8. Design and Safety Assessment Cycle.
9. Basic Concept.
10. Semantics, Properties and Evolution Rules of an SPN.
11. Simplification of Complex Models.
12. Extensions of SPN.
13. Application in Dynamic Reliability.
14. Classical Dependability Assessment.
15. Impact of Failures on System Performances.

About the authors/editors


Jean-François Aubry is Professor Emeritus at the University of Lorraine, France. His research interests include control systems and safety engineering, dynamic reliability and the dependability assessment of systems.

Nicolae Brinzei is Associate Professor at the University of Lorraine, France. His research interests include stochastic modeling of systems for dependability and dynamic reliability assessment.

Mohammed-Habib Mazouni is a System Architect at Alstom Transport, appointed as a system engineering senior expert. His research interests include complex systems engineering, advanced CBTC signaling, processing and tools, design, safety, verification and validation.