Critical Infrastructures (CIs) play a crucial role in the normal performance of economy and society. Over the last decades the amount and the variety of CIs grew rapidly, and the interdependency between them increased constantly. Consequently more and more essential services depend on the continuous performance of one, two or even more CIs such as power supply, communications, etc. It is thus of utmost importance to ensure reliable and robust performance of critical infrastructures on a continuous basis, particularly during and after the occurrence of extreme events. This paper presents a state-of-the-art review of the contemporary state of critical infrastructures’ preparedness, through a comprehensive literature review of significant extreme events that occurred in the past two decades. This paper examine the Oklahoma bombing (1995), the Izmit earthquake (1999), the World Trade Center attack (2001), the Indian Ocean tsunami (2004), hurricane Katrina (2005), the London July 7th attacks (2005), the Haiti earthquake (2010), and the Fukushima-Daiichi Nuclear disaster (2011). The review exposes insufficient preparedness of CIs in cases of extreme events and raises several root patterns which led to the severe consequences of the extreme events: a gap between the preparedness of the CIs to the actual risk; higher than expected consequences due to evolution of critical infrastructures; high and increasing interdependencies between the CIs, and high vulnerability of critical infrastructures despite the known risk. The consequences of those events reveal a mismatch between the actual risk to the CIs and between the investments that were made by decision makers for their preparedness

Modern economy and society are constantly highly dependent on a variety of critical infrastructures (CIs) over the last decades. However an observation and review of the extreme events that occurred during the last two decades reveal that while the interdependencies between the CIs are growing and getting more complex there is an increasing gap between the growing risk and the actual preparedness. Therefore, there is an utmost importance to ensure reliable and robust performance of critical infrastructures on a continuous basis, particularly during and after the occurrence of extreme events. A decision support tool for decision makers to appraise and mitigate the risk of CIs after the occurrence of seismic events is developed. The methodology analyzes the damage of critical infrastructure components by Fault-Tree-Analysis, Decision Trees and Fragility Curves. Though the methodology is suitable for a variety of critical infrastructures, this study will focus on critical Oil and Gas Network Systems, which are vital to the energy supply infrastructure of Israel. In order to assess the risk that Oil and Gas Critical Infrastructures are exposed to in case of seismic extreme events, fragility curves are derived and adjusted to different components of the Oil and Natural Gas systems. Subsequently, a variety of possible seismic scenarios are examined and analyzed in order to determine the damage of the components. The overall expected damage of the Oil or Gas system is assessed by considering the damage state of all components of the system. The expected damage states of the components disclose and emphasize the most vulnerable parts of the system. Also discussed are guiding principles for decision makers for risk informed mitigation on benefit-cost-ratio analysis

In observational method projects in geotechnical engineering, the final geotechnical design is decided upon during actual construction, depending on the observed behavior of the ground. Hence, engineers must be prepared to make crucial decisions promptly, with few available guidelines. In this paper, we propose coupling numerical analysis with machine learning (ML) algorithms for enhancing the decision process in observational method projects. The proposed methodology consists of two main computational steps: (1) data generation, where multiple numerical models are automatically generated according to the anticipated range of input parameters, and (2) data analysis, where input parameters and model results are analyzed with ML models. Using the case study of the Semel tunnel in Tel Aviv, Israel, we demonstrate how this computational process can contribute to the success of observational method projects through (1) the computation of feature importance, which can assist with better identifying the key features that drive failure prior to project execution, (2) providing insights regarding the monitoring plan, as correlative relationships between various results can be tested, and (3) instantaneous predictions during construction.

The role of critical infrastructures in maintaining the functioning of the economy and society and ensuring national security, particularly their durability in delivering essential services during crises, including natural disasters such as earthquakes, is critical. This work introduces an analytical methodology to quantify potential earthquake damage to power stations and evaluate the cost-effectiveness of measures to enhance their seismic resistance. By employing fragility curves and probabilistic risk analyses, this approach provides a structured framework for the comprehensive assessment of risks and the identification of economically practical mitigation strategies. A detailed examination of strategies to protect critical power station components against seismic activity is presented, revealing that a minor investment relative to the overall project budget for earthquake-proofing measures is economically effective. This investment, representing a marginal fraction of 0.5% of the total project expenditure significantly reduces the seismic risk of power station failure by 36%. Reinforcing essential elements, including switching stations, water treatment facilities, and water tanks, is emphasized to ensure their continued operation during and after an earthquake. This research highlights the critical significance of integrating risk assessment with benefit-to-cost analysis in strategic decision-making processes, supporting the prioritization of investments in infrastructure enhancements. These enhancements promise substantial reductions of risks at minimal costs, thus protecting essential services against the impacts of natural disasters. This research contributes to state-of-the-art research in critical infrastructures resilience.