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Infrastructure Resilience Conference 2018

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Resilience Engineering – From Concept to Application

To meet the multi-faceted challenges our world faces, its critical infrastructure needs to be resilient. International terrorism and natural disasters but also vulnerabilities stemming from the growing interconnectedness and complexity of coupled infrastructure systems threaten the sustained and reliable functioning of our critical infrastructure. Traditional risk analysis, which relies on reductionism and uses well-specified scenarios, defined probabilities and rigid damage estimations, is not a suitable tool to analyze, manage and improve complex systems. Furthermore, modern infrastructure systems are strongly coupled with each other and therefore vulnerable to cascading effects. Those effects can trigger unforeseen outcomes in situations which seemed to be controllable before. Thus, new and holistic concepts are needed. Resilience is such a concept. Resilience can be understood as the ability to repel, prepare for, take into account, absorb, recover from and adapt ever more successfully to actual or potential adverse events. The tutorial session will show how resilience has found its way into the engineering sciences in the field of security research. In Freiburg, Fraunhofer EMI – together with the new Department of Sustainable Systems Engineering (INATECH) at the University of Freiburg – has been working on both the concept of Resilience Engineering as well as tangible solutions for real world applications for years. The Freiburg understanding of Resilience Engineering is based on the work of a community of researchers around Erik Hollnagel and David Woods. It advances their conceptual thinking, which focuses on human factors, and identifies six key aspects of Resilience Engineering. First, Resilience Engineering is about preserving critical functionality. When disaster strikes, a system needs to be able to maintain its most critical subfunctions. Second, if functionality cannot be preserved, Resilience Engineering ensures at least a graceful degradation of system functionalities averting a catastrophic and abrupt total system failure. Third, as soon as the disruption is over, the system will start to recover. Fast recovery does not only mean bouncing back to the original state, but also implementing lessons learned and adapting system functionalities to changed and evolving circumstances. Fourth, Resilience Engineering is the ability to create generic capabilities as heuristics that can be applied to a broad set of previously undefined disruptions. Such heuristics include redundancy, backups, predictability, complexity avoidance/reduction and others. Fifth, at the same time Resilience Engineering means including resilience thinking into the use of cutting-edge technologies for system design. These technologies need to be customized to fit the respective system. And sixth, Resilience Engineering is useful when the system witnesses known problems, serious unexpected disruptions or even unexampled events. Customized technological solutions allow for the handling of minor and well-known disruptions whereas generic capabilities are more useful for unexpected or unexampled events. This concept remains rather vague. Particularly, when it comes to developing new methods to model and simulate the behavior of complex, coupled infrastructure systems independent of precisely defined scenarios, there is still a huge need for advancement both in basic and applied research. The same accounts for thorough ways to measure and quantify resilience. The session will show some application examples where the characteristics of the Resilience Engineering concept were used to create software tools for infrastructure operators, e.g. to mitigate terrorist threats, to include expert knowledge and all relevant stakeholder interests in management processes or to better understand cascading effects in coupled infrastructure networks. As a result, the session will conclude with the remark that it is important to apply the concept more often to real world problems. This will enable analyzing strengths and weaknesses and improve both the concept as such as well as its applicability and, thus, usefulness for society.

Scharte Benjamin
Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI
Germany

Stefan Hiermaier
Fraunhofer Institute for High Speed Dynamics, Ernst-Mach-Institut, EMI
Germany

 

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