Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database.

Organized into a global network of critical infrastructures, the oil & gas industry remains to this day the main energy contributor to the world's economy. Severe accidents occasionally occur resulting in fatalities and disruption. We build an oil & gas accident graph based on more than a thousand severe accidents for the period 1970-2016 recorded for refineries, tankers, and gas networks in the authoritative ENergy-related Severe Accident Database (ENSAD). We explore the distribution of potential chains-of-events leading to severe accidents by combining graph theory, Markov analysis and catastrophe dynamics. Using centrality measures, we first verify that human error is consistently the main source of accidents and that explosion, fire, toxic release, and element rupture are the principal sinks, but also the main catalysts for accident amplification. Second, we quantify the space of possible chains-of-events using the concept of fundamental matrix and rank them by defining a likelihood-based importance measure γ. We find that chains of up to five events can play a significant role in severe accidents, consisting of feedback loops of the aforementioned events but also of secondary events not directly identifiable from graph topology and yet participating in the most likely chains-of-events.

MCDA Index Tool: an interactive software to develop indices and rankings.

A web-based software, called MCDA Index Tool (https://www.mcdaindex.net/), is presented in this paper. It allows developing indices and ranking alternatives, based on multiple combinations of normalization methods and aggregation functions. Given the steadily increasing importance of accounting for multiple preferences of the decision-makers and assessing the robustness of the decision recommendations, this tool is a timely instrument that can be used primarily by non-multiple criteria decision analysis (MCDA) experts to dynamically shape and evaluate their indices. The MCDA Index Tool allows the user to (i) input a dataset directly from spreadsheets with alternatives and indicators performance, (ii) build multiple indices by choosing several normalization methods and aggregation functions, and (iii) visualize and compare the indices' scores and rankings to assess the robustness of the results. A novel perspective on uncertainty and sensitivity analysis of preference models offers operational solutions to assess the influence of different strategies to develop indices and visualize their results. A case study for the assessment of the energy security and sustainability implications of different global energy scenarios is used to illustrate the application of the MCDA Index Tool. Analysts have now access to an index development tool that supports constructive and dynamic evaluation of the stability of rankings driven by a single score while including multiple decision-makers' and stakeholders' preferences.

Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non-OECD Countries with Focus on Time Trend Analysis.

This study presents probabilistic analysis of dam accidents worldwide in the period 1911-2016. The accidents are classified by the dam purpose and by the country cluster, where they occurred, distinguishing between the countries of the Organization for Economic Cooperation and Development (OECD) and nonmember countries (non-OECD without China). A Bayesian hierarchical approach is used to model distributions of frequency and severity for accidents. This approach treats accident data as a multilevel system with subsets sharing specific characteristics. To model accident probabilities for a particular dam characteristic, this approach samples data from the entire data set, borrowing the strength across data set and enabling to model distributions even for subsets with scarce data. The modelled frequencies and severities are combined in frequency-consequence curves, showing that accidents for all dam purposes are more frequent in non-OECD (without China) and their maximum consequences are larger than in OECD countries. Multipurpose dams also have higher frequencies and maximum consequences than single-purpose dams. In addition, the developed methodology explicitly models time dependence to identify trends in accident frequencies over the analyzed period. Downward trends are found for almost all dam purposes confirming that technological development and implementation of safety measures are likely to have a positive impact on dam safety. The results of the analysis provide insights for dam risk management and decision-making processes by identifying key risk factors related to country groups and dam purposes as well as changes over time.

An aftermath analysis of the 2014 coal mine accident in Soma, Turkey: Use of risk performance indicators based on historical experience.

On the 13th of May 2014 a fire related incident in the Soma coal mine in Turkey caused 301 fatalities and more than 80 injuries. This has been the largest coal mine accident in Turkey, and in the OECD country group, so far. This study investigated if such a disastrous event should be expected, in a statistical sense, based on historical observations. For this purpose, PSI's ENSAD database is used to extract accident data for the period 1970-2014. Four different cases are analyzed, i.e., OECD, OECD w/o Turkey, Turkey and USA. Analysis of temporal trends for annual numbers of accidents and fatalities indicated a non-significant decreasing tendency for OECD and OECD w/o Turkey and a significant one for USA, whereas for Turkey both measures showed an increase over time. The expectation analysis revealed clearly that an event with the consequences of the Soma accident is rather unlikely for OECD, OECD w/o Turkey and USA. In contrast, such a severe accident has a substantially higher expectation for Turkey, i.e. it cannot be considered an extremely rare event, based on historical experience. This indicates a need for improved safety measures and stricter regulations in the Turkish coal mining sector in order to get closer to the rest of OECD.