Critical Infrastructure Impacted by Climate Change Safety and Resilience Indicators

Kołowrocki, K.; Soszyńska-Budny, J.; Torbicki, M.

doi:10.1109/ieem.2018.8607565

Cited by 4 publications

(3 citation statements)

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“…The data were obtained from the IMWM-NRI under a copyright provision such that they can be presented in a processed form, not the exact original. Following the uniformity testing, the data collected from the four points (as depicted in Figure 4) were combined and subjected to analysis using methods outlined in [40][41][42][57][58][59][60][61]. Based on this consolidated dataset, the unknown fundamental parameters of the semi-Markov model of the process at the selected water area were assessed and evaluated.…”

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confidence: 99%

Oil Discharge Trajectory Simulation at Selected Baltic Sea Waterway under Variability of Hydro-Meteorological Conditions

Dąbrowska

2023

Water

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The paper deals with an important issue related to the identification, modelling, and prediction of environmental pollution in aquatic ecosystems of the Baltic Sea caused by anthropopressure. Water ecosystems are in danger nowadays because of the negative influence of chemical releases in seas, oceans, or inland waters. The crucial issue is to prevent the oil spills and mitigate their consequences. Thus, there is a need for methods capable of reducing the water pollution and enhancing the effectiveness of port and marine environment preservation. The challenge in implementing actions to remove and prevent horizontal oil discharge lies in accurately determining its shape and direction of oil spreading. The author employed a self-designed software utilizing modified and developed mathematical probabilistic models to forecast the movement and dispersion of an oil spill in diverse hydrological and meteorological conditions. This involved determining the trajectory and movement of a spill domain, which consists of elliptical sub-domains undergoing temporal changes. The research results obtained are the initial results in the oil spill simulation problem. This approach represents an expanded and innovative method for determining the spill domain and tracking its movement, applicable to oceans and seas worldwide. It expands upon the methodologies firstly discussed, thereby broadening the range of available techniques in this field. A simple model of an oil spill trajectory simulation and a surface oil slick as an ellipse is illustrated using a time-series of selected hydro-meteorological factors that change at random times. The author proposes a Monte Carlo simulation method to determine the extent of an oil spill in an aquatic ecosystem, taking into account the influence of varying hydro-meteorological conditions. A semi-Markov model is defined to capture the dynamics of these conditions within the spill area and develop an enhanced algorithm for predicting changes in the shape and movement of the spill domain under changing these conditions. By applying the algorithm, a simulation is conducted to provide short-term prediction of the oil discharge trajectory in a selected Baltic Sea waterway. To enhance the accuracy of predicting the process of changing conditions, uniformly tested joint datasets from the open sea water area were incorporated. Finally, the potential future prospects and directions for further research in this field are discussed.

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confidence: 99%

Oil Discharge Trajectory Simulation at Selected Baltic Sea Waterway under Variability of Hydro-Meteorological Conditions

Dąbrowska

2023

Water

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“…Therefore, addressing the vulnerability of transport networks is the key to reliable operation of transport and logistics systems [6][7][8]. This is particularly important in the context of climate change [9][10][11][12][13] and the need to preserve the business continuity of these networks [9,12,14]. It was assumed that the best and most natural way to describe transport systems was a graph network representing the infrastructure of this system and allowing characterization of the traffic flows occurring in this network [15][16][17][18].…”

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confidence: 99%

“…It was assumed that the best and most natural way to describe transport systems was a graph network representing the infrastructure of this system and allowing characterization of the traffic flows occurring in this network [15][16][17][18]. One should agree with this because the structure and traffic flow in the transport network reflect the relationships between individual elements of the transport system in the best way, and thus, determine it [8,12]. According to the above, one of the most important things in transportation networks' analysis is the finding of the bottlenecks.…”

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Graph Theory Approach to the Vulnerability of Transportation Networks

Guze

2019

Algorithms

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Nowadays, transport is the basis for the functioning of national, continental, and global economies. Thus, many governments recognize it as a critical element in ensuring the daily existence of societies in their countries. Those responsible for the proper operation of the transport sector must have the right tools to model, analyze, and optimize its elements. One of the most critical problems is the need to prevent bottlenecks in transport networks. Thus, the main aim of the article was to define the parameters characterizing the transportation network vulnerability and select algorithms to support their search. The parameters proposed are based on characteristics related to domination in graph theory. The domination, edge-domination concepts, and related topics, such as bondage-connected and weighted bondage-connected numbers, were applied as the tools for searching and identifying the bottlenecks in transportation networks. Furthermore, the algorithms for finding the minimal dominating set and minimal (maximal) weighted dominating sets are proposed. This way, the exemplary academic transportation network was analyzed in two cases: stationary and dynamic. Some conclusions are presented. The main one is the fact that the methods given in this article are universal and applicable to both small and large-scale networks. Moreover, the approach can support the dynamic analysis of bottlenecks in transport networks.

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