Progressing digitalization and networking of systems and organizations representing Critical Infrastructures opens promising new potentials and opportunities, which on the downside, are accompanied by rising complexity and increasingly opaque interdependencies. The consequently increasing lack of knowledge leads to uncertainties affecting risk assessment and decision-making in case of adverse events. This trend motivated recent discussions and developments in risk science, emphasizing the need to handle such uncertainties. Complementarily, research in the resilience domain focuses on system capabilities to handle surprising hazardous situations. Several frameworks presented in the literature aim at combining both perspectives but either lack the focus on operational management, have a rather theoretical approach, or are designed for specific applications. Based on this observation, we propose an approach that integrates resilience management into the actual operation of Critical Infrastructure Systems and Organizations by providing an operational process that coordinates the fundamental resilience capabilities of responding, monitoring, anticipation, and learning. Furthermore, we tackle the challenge of uncertainties resulting from a lack of knowledge by aligning the concepts of digital twin and resilience management. The proposed framework is extensively discussed, and required processes are presented in detail. Eventually, its applicability and potential are reviewed by means of a complex hazardous situation at a Bavarian district heating power plant.

Offshore wind farms (OWFs) are important infrastructure which provide an alternative and clean means of energy production worldwide. The offshore wind industry has been continuously growing. Over the years, however, it has become evident that OWFs are facing a variety of safety and security challenges. If not addressed, these issues may hinder their progress. Based on these safety and security goals and on a Bayesian network model, this work presents a methodological approach for structuring and organizing expert knowledge and turning it into a probabilistic model to assess the safety and security of OWFs. This graphical probabilistic model allowed us to create a high-level representation of the safety and security state of a generic OWF. By studying the interrelations between the different functions of the model, and by proposing different scenarios, we determined the impacts that a failing function may have on other functions in this complex system. Finally, this model helped us define the performance requirements of such infrastructure, which should be beneficial for optimizing operation and maintenance.

This paper discusses the application of resilience engineering principles by shipborne navigation systems. As a technological system, the ship navigation system comprises all the communication and navigation equipment required to operate a ship. If examined as a socio-technological system, one has to additionally consider the use of the ship navigation system by the bridge teams in order to perform the nautical profession in terms of safe and efficient ship navigation, taking into account environmental information received by communication. The first part of this work discusses the theoretical background of resilience engineering and situation awareness. Case studies are used to illustrate under which conditions the application of resilience principles may result in an improvement of the operational reliability. With the help of simulations, it is shown that a sub-optimal implementation and utilization of resilience principles may decrease the robustness of the technical ship navigation system, as well as the reliability and adaptability of the ship navigation system in use. The examples illustrate once again that monitoring is one of the four cornerstones of resilience: anticipating, monitoring, learning, and responding. This is due to the effectiveness of most resilience principles depending on the availability and trustworthiness of situational information in relation to system status and environmental conditions, irrespective of whether the generation and use of the situational information is machine-made or human-made. Therefore, the establishment of situation awareness is an essential accompanying functionality to be considered in design, operation, and use of resilient systems.

The ability of an infrastructure to be resistant against hazards or to accommodate and recover from hazard-induced destructions and disturbances is characterized as resilience. Usually, infrastructures are engineered socio-technical systems or systems-of-systems. Jackson and Ferris consider the use of finite state machine (FSM) modelling as a suitable means to depict and investigate the resilience of such engineered systems. This paper discusses the capabilities and limitations of the FSM model proposed by Jackson and Ferris and if it should be used for the representation and evaluation of the resilience of an infrastructure. The discussion is conducted on a more general level. However, special attention is paid to monitoring because, on the one hand, monitoring is one of the cornerstones of resilience and, on the other hand, Scott and Ferris define a state that is emphasized by an increased level of situational awareness as a result of happened and perceived events. Consequently, the question has to be answered of how the models are able to reflect the need for routine monitoring of the resilience of infrastructures in order to initiate, if necessary, adjustment procedures as an appropriate response to changes in internal and external conditions. The results of this theoretical study are a fundamental step towards the practical application of the FSM approach for the design of resilient infrastructures.