Chapter
Aug 14, 2018
Chapter 4
Efficient Reliability and Risk Analysis of Complex Interconnected Systems
Authors: J. Behrensdorf, M.Sc. {behrensdorf, broggi, beer}@irz.uni-hannover.de, M. Broggi, Ph.D. {behrensdorf, broggi, beer}@irz.uni-hannover.de, and M. Beer {behrensdorf, broggi, beer}@irz.uni-hannover.deAuthor Affiliations
Publication: Resilience Engineering for Urban Tunnels
Abstract
This chapter introduces a quantitative approach to evaluating failure consequences by estimating the reliability of systems with cascading failures. The survival signature is highly advantageous in traditional analysis techniques, as it can be calculated once, ahead of the analysis, and used to perform reliability analysis for several scenarios on the same network without reevaluating the network structure. The chapter also introduces a novel methodology to assess cascading failures between systems. This method provides a structured approach to a quantitative analysis of failure consequences, up to an economic loss for a rigorous risk analysis of complex interconnected systems and networks. The chapter overviews the survival signature and the Monte Carlo approximation of network reliability and deals with the probabilistic characteristics of failures with dependencies. The chapter also presents some numerical examples.
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© 2018 American Society of Civil Engineers.
History
Published online: Aug 14, 2018
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ASCE Technical Topics:
- Analysis (by type)
- Design (by type)
- Disaster risk management
- Engineering fundamentals
- Failure analysis
- Forensic engineering
- Network analysis
- Quantitative analysis
- Risk management
- Structural analysis
- Structural design
- Structural engineering
- Structural failures
- Structural reliability
- System reliability
- Systems engineering
- Systems management
Authors
Affiliations
Institute for Risk and Reliability, Leibniz Universität Hannover, Callinstr. 34, 30167 Hannover, Germany; email: {behrensdorf, broggi, beer}@irz.uni-hannover.de
Institute for Risk and Reliability, Leibniz Universität Hannover, Callinstr. 34, 30167 Hannover, Germany; email: {behrensdorf, broggi, beer}@irz.uni-hannover.de
Prof.
Institute for Risk and Reliability, Leibniz Universität Hannover, Callinstr. 34, 30167 Hannover, Germany; email: {behrensdorf, broggi, beer}@irz.uni-hannover.de
Institute for Risk and Uncertainty, University of Liverpool, Liverpool, UK
International Joint Research Center for Engineering Reliability and Stochastic Mechanics (ERSM), Tongji University, Shanghai, China
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