Oil spills from maritime activities can lead to very extensive damage to the marine environment and disrupt maritime ecosystem services. Shipping is an important activity in the Northern Baltic Sea, and with the complex and dynamic ice conditions present in this sea area, navigational accidents occur rather frequently. Recent risk analysis results indicate those oil spills are particularly likely in the event of collisions. In Finnish sea areas, the current wintertime response preparedness is designed to a level of 5000 tonnes of oil, whereas a state-of-the-art risk analysis conservatively estimates that spills up to 15000 tonnes are possible. Hence, there is a need to more accurately estimate oil spill scenarios in the Northern Baltic Sea, to assist the relevant authorities in planning the response fleet organization and its operations. An issue that has not received prior consideration in maritime waterway oil spill analysis is the dynamics of the oil outflow, i.e. how the oil outflow extent depends on time. Hence, this paper focuses on time-dependent oil spill scenarios from collision accidents possibly occurring to tankers operating in the Northern Baltic Sea. To estimate these, a Bayesian Network model is developed, integrating information about designs of typical tankers operating in this area, information about possible damage scenarios in collision accidents, and a state-of-the-art time-domain oil outflow model. The resulting model efficiently provides information about the possible amounts of oil spilled in the sea in different periods of time, thus contributing to enhanced oil spill risk assessment and response preparedness planning.
The environmental conditions in the Gulf of Finland vary significantly in different locations. In addition, the gulf is a busy and important area for waterway traffic and international trade throughout the year. In summer, the area is ideal for recreational activities such as boating and other water-related activities. Water accidents occur due to different factors and under varying weather conditions. This paper introduces a visual data mining analysis applied to Search and Rescue (SAR) missions related to recreational boating. Starting from a SAR operations database, an integrated database was constructed by adding weather and wave data. The aim was to compare the different mission types as well as the activity of different SAR organisations during challenging wind and wave conditions. The investigation was performed using visual analysis techniques. The densest areas of challenging wind and wave conditions were found in the western and eastern parts of the gulf. Other investigated parameters were travelled distances and occurrence of the incidents during different times of day. A more detailed analysis was conducted for one dataset.
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AIS (Automatic Identification System) data analysis is used to define ship domain for ground-ing scenarios. The domain has been divided into two areas as inner and outer domains. Inner domain has clear border, which is based on ship dynamic characteristics. Violation of inner domain makes the grounding acci-dent unavoidable. Outer domain area is defined with AIS data analyzing. Outer domain shows the situation of own ship in compare with other similar ships that previously were in the same situation. The domain can be used as a decision support tool in VTS (Vessel Traffic Service) centers to detect grounding candidate vessels. In the case study presented in this paper, one type of ship, which is tanker, in a waterway to Sköldvik in the Gulf of Finland is taken into account.
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The collision dynamics model is a vital part in maritime risk analysis. Different models have been introduced since Minorsky first presented collision dynamics model. Lately, increased computing capac-ity has led to development of more sophisticated models. Although the dynamics of ship collisions have been studied and understanding on the affecting factors is increased, there are many assumptions required to com-plete the analysis. The uncertainty in the dynamic parameters due to assumptions is not often considered. In this paper a case study is conducted to show how input models for dynamic parameters affect the results of collision energy calculations and thus probability of an oil spill. The released deformation energy in collision is estimated by the means of the analytical collision dynamics model Zhang presented in his PhD thesis. The case study concerns the sea area between Helsinki and Tallinn where a crossing of two densely trafficked wa-terways is located. Actual traffic data is utilized to obtain realistic encounter scenarios by means of Monte Carlo simulation. Applicability of the compared assumptions is discussed based on the findings of the case study.
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Maritime traffic poses various risks in terms of human casualties, environmental pollution or loss of property. In particular, tankers pose a high environmental risk as they carry very large amounts of oil or more modest amounts of possibly highly toxic chemicals. In this paper, a simplified risk assessment meth-odology for spills from tankers is proposed for the Gulf of Finland, for tankers involved in a ship-ship collision. The method is placed in a wider risk assessment methodology, inspired by the Formal Safety Assess-ment (FSA) and determines the risk as a combination of probability of occurrence and severity of the consequences. The collision probability model is based on a time-domain micro simulation of maritime traf-fic, for which the input is obtained through a detailed analysis of data from the Automatic Identification System (AIS). In addition, an accident causation model, coupled to the output of the traffic simulation model is proposed to evaluate the risk reduction effect of the risk control options. Further development of the model is needed, but the modular nature of the model allows for continuous improvement of the modules and the ex-tension of the model to include more hazards or consequences, such that the effect of risk control options can be studied and recommendations made. This paper shows some preliminary results of some risk analysis blocks for tanker collisions in the Gulf of Finland.
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For safe and efficient exploitation of ice-covered waters the knowledge about ship performance in ice is crucial. Although ice navigation has received substantial attention over recent decades, there is still no known modelling technique to predict ship’s speed in a dynamic ice field. In order to gain an insight into this process, we need to transform the available data into information first. Only then information can be used to develop new knowledge. This paper demonstrates how to transform still data into dynamic information about operation of maritime transportation system in ice-covered waters. For this purpose, the data from the Automatic Identification System about the performance of a selected ship is used along with a numerical ice forecast model describing the ice field in the analysed sea area.
PL
W celu bezpiecznej oraz wydajnej eksploatacji akwenów pokrytych lodem, wiedza o zachowaniu statku w tych warunkach jest niezbędna. Pomimo, iż żegluga w lodach pozostaje tematem wielu opracowań naukowych, tematyka modelowania zachowania statku w dynamicznym polu lodowym, zwłaszcza w obecności zjawiska kompresji pokrywy lodowej, pozostaje wciąż kwestią otwartą. W artykule omówiono dostępne źródła danych, które po odpowiednim przetworzeniu dostarczą informacji, umożliwiającej lepsze zrozumienie procesu nawigacji statku w dynamicznym polu lodowym co pozwoli na modelowanie tego procesu. W artykule podkreślono zasadność przeprowadzenia procesu przekształcenia danych w informację które następnie można wykorzystać w celu uzyskania nowej wiedzy. Na przykładzie pokazano, iż nawet najdokładniejsze dane, nie dostarczą pełnej informacji, jeżeli nie zostaną odpowiednio przetworzone oraz zinterpretowane, co może prowadzić do błędnych lub niepełnych wniosków.
Risks in the maritime domain have various sources, of which the transportation of oil and other noxious products is one of key concern to industry and public stakeholders. Operational or accidental releases of oil or other pollutants from ships or offshore facilities into the marine environment can have disastrous effects on the marine ecosystems, while also leading to very significant economical losses. Therefore, national states have implemented various mechanisms for preventing and responding to pollution in the maritime domain, with activities which are often embedded in regional cooperation frameworks clustered around certain sea areas. To support collaborative, harmonized, and risk-informed oil spill Pollution Preparedness and Response (PPR) planning for response authorities, the Baltic Marine Environment Protection Commission (HELCOM), together with its research partners, and with extensive end-user and stakeholder inputs, have developed the OpenRisk Toolbox. This toolbox includes several risk assessment tools and techniques, which can assist in providing answers to a range of PPR risk management questions in a range of organizational contexts. To better understand and ensure the applicability and usefulness of the OpenRisk Toolbox, a workshop was organized where some of these tools were tested. Selected end user and stakeholder views on the perceived usefulness of the tools were collected and analyzed. Another workshop focused on further development needs to implement the tools in organizational practices. This paper first presents the OpenRisk Toolbox, then describes the settings of the workshops. Finally, a summary of the end-user and stakeholder views on the tested tools, and on future development needs, is given.
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