Jakub Montewka

Probability modelling of vessel collisions

Among engineers, risk is defined as a product of probability of the occurrence of an undesired event and the expected consequences in terms of human, economic, and environmental loss. These two components are equally important; therefore, the appropriate estimation of these values is a matter of great significance. This paper deals with one of these two components—the assessment of the probability of vessels colliding, presenting a new approach for the geometrical probability of collision estimation on the basis of maritime and aviation experience. The geometrical model that is being introduced in this paper takes into account registered vessel traffic data and generalised vessel dynamics and uses advanced statistical and optimisation methods (Monte Carlo and genetic algorithms). The results obtained from the model are compared with registered data for maritime traffic in the Gulf of Finland and a good agreement is found.

Maritime transportation risk analysis: Review and analysis in light of some foundational issues

Many methods and applications for maritime transportation risk analysis have been presented in the literature. In parallel, there is a recent focus on foundational issues in risk analysis, with calls for intensified research on fundamental concepts and principles underlying the scientific field. This paper presents a review and analysis of risk definitions, perspectives and scientific approaches to risk analysis found in the maritime transportation application area, focusing on applications addressing accidental risk of shipping in a sea area. For this purpose, a classification of risk definitions, an overview of elements in risk perspectives and a classification of approaches to risk analysis science are applied. Results reveal that in the application area, risk is strongly tied to probability, both in definitions and perspectives, while alternative views exist. A diffuse situation is also found concerning the scientific approach to risk analysis, with realist, proceduralist and constructivist foundations co-existing. Realist approaches dominate the application area. Very few applications systematically account for uncertainty, neither concerning the evidence base nor in relation to the limitations of the risk model in relation to the space of possible outcomes. Some suggestions are made to improve the current situation, aiming to strengthen the scientific basis for risk analysis.

A risk analysis of winter navigation in Finnish sea areas

Winter navigation is a complex but common operation in north-European sea areas. In Finnish waters, the smooth flow of maritime traffic and safety of vessel navigation during the winter period are managed through the Finnish-Swedish winter navigation system (FSWNS). This article focuses on accident risks in winter navigation operations, beginning with a brief outline of the FSWNS. The study analyses a hazard identification model of winter navigation and reviews accident data extracted from four winter periods. These are adopted as a basis for visualizing the risks in winter navigation operations. The results reveal that experts consider ship independent navigation in ice conditions the most complex navigational operation, which is confirmed by accident data analysis showing that the operation constitutes the type of navigation with the highest number of accidents reported. The severity of the accidents during winter navigation is mainly categorized as less serious. Collision is the most typical accident in ice navigation and general cargo the type of vessel most frequently involved in these accidents. Consolidated ice, ice ridges and ice thickness between 15 and 40cm represent the most common ice conditions in which accidents occur. Thus, the analysis presented in this article establishes the key elements for identifying the operation types which would benefit most from further safety engineering and safety or risk management development.

A probabilistic model estimating oil spill clean-up costs--a case study for the Gulf of Finland.

Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs. In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement. We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).

A probabilistic model for accidental cargo oil outflow from product tankers in a ship-ship collision

In risk assessment of maritime transportation, estimation of accidental oil outflow from tankers is important for assessing environmental impacts. However, there typically is limited data concerning the specific structural design and tank arrangement of ships operating in a given area. Moreover, there is uncertainty about the accident scenarios potentially emerging from ship encounters. This paper proposes a Bayesian network (BN) model for reasoning under uncertainty for the assessment of accidental cargo oil outflow in a ship-ship collision where a product tanker is struck. The BN combines a model linking impact scenarios to damage extent with a model for estimating the tank layouts based on limited information regarding the ship. The methodology for constructing the model is presented and output for two accident scenarios is shown. The discussion elaborates on the issue of model validation, both in terms of the BN and in light of the adopted uncertainty/bias-based risk perspective.

Marine traffic risk modelling an innovative approach and a case study

This paper presents a model to analyse the risk of two common marine accidents: collision and grounding. Attention is focused on oil tankers since they pose the highest environmental risks. A case study in selected areas of the Gulf of Finland in ice-free conditions is presented. The model utilizes a formula for risk calculation that considers both the probability of an unwanted event and its consequences. The model can be decomposed into a block representation in which blocks for the probability of a collision, probability of a grounding event, and the consequences of an accident are linked. The probability of vessel colliding is assessed in terms of a minimum-distance-to-collision-based model. The model defines the collision zone using a mathematical ship motion model and considers the traffic flow to be a non-homogeneous process. Calculations are performed using data for traffic flows in the Gulf of Finland with particular attention being paid to the crossing of the channel used by scheduled ferries between Helsinki and Tallinn, and the main shipping channel. For the assessment of a grounding probability, a new approach is proposed, which utilizes a gravity-like model, where a ship and navigational obstructions are perceived as interacting objects and their repulsion is modelled by a formulation inspired by gravitational force. The considered situation in this case is the movement of oil tankers in the approach channel to an oil terminal at Sköldvik, near Helsinki. The consequences of an accident are expressed in monetary terms, and concern the costs of cleaning up an oil spill, based on the statistics of compensation levels claimed from the International Oil Pollution Compensation Fund.

Expert elicitation of a navigation service implementation effects on ship groundings and collisions in the Gulf of Finland

When considering the implementation of a novel risk-control option, the estimation of its possible effects often relies on expert elicitation. This article presents an expert-knowledge–based preliminary assessment of how the deployment of Enhanced Navigation Support Information navigation service would affect the ship collisions and groundings in the Gulf of Finland. Experts probabilistically assess the service’s direct effects on various factors, which are then utilized in collision and grounding probability Bayesian network models. The results indicate that implementing the Enhanced Navigation Support Information service could decrease the number of accidents. However, a comparison of the model outcomes to the experts’ qualitative opinions reveals some discrepancies, which suggest that the elicitation procedure or the applied models might require further improvement. Nevertheless, with the proposed Bayesian approach, the model can be updated and uncertainties in the estimates reduced after more evidences are available later from longer and wider use of the service.

Uncertainty in maritime risk analysis: Extended case study on chemical tanker collisions

Uncertainty is inherent to risk analysis. Therefore, it is extremely important to properly address the issue of uncertainty. In the field of risk analysis for maritime transportation systems, the effect of uncertainty is rarely discussed or quantified. For this reason, this article discusses a case study dealing with risk analysis for a chemical spill in the Gulf of Finland and analyses the related uncertainties by adopting a systematic framework. Risk is assessed in terms of the expected spill frequency and spill volumes caused by collisions between ships and chemical tankers in the Gulf of Finland. This is done by applying a collision consequence with a novel approach-to-collision-speed linkage model and Gulf of Finland–specific causation factors, which are based on reanalysing accident data. This article also presents a metamodel for assessing collision probability with initial vessel speeds for any given scenario where a chemical tanker is about to be struck by another vessel. Even when conducting a risk analysis using state-of-the-art methods, there is still a medium-high degree of uncertainty in the model presented in this article, which only becomes apparent when conducting a systematic uncertainty assessment analysis. However, an uncertainty assessment is an important part of quantitative maritime risk analysis. For this purpose, a qualitative framework for uncertainty assessment analysis is introduced for general use in the field of maritime risk analysis.

On a systematic perspective on risk for formal safety assessment (FSA)

In the maritime domain, risk is evaluated within the framework of the Formal Safety Assessment (FSA), introduced by the International Maritime Organization in 2002. Although the FSA has become an internationally recognized and recommended method, the definition, which is adopted there, to describe the risk, seems to be too narrow to reflect the actual content of the FSA.

Risk management model of winter navigation operations

The wintertime maritime traffic operations in the Gulf of Finland are managed through the Finnish-Swedish Winter Navigation System. This establishes the requirements and limitations for the vessels navigating when ice covers this area. During winter navigation in the Gulf of Finland, the largest risk stems from accidental ship collisions which may also trigger oil spills. In this article, a model for managing the risk of winter navigation operations is presented. The model analyses the probability of oil spills derived from collisions involving oil tanker vessels and other vessel types. The model structure is based on the steps provided in the Formal Safety Assessment (FSA) by the International Maritime Organization (IMO) and adapted into a Bayesian Network model. The results indicate that ship independent navigation and convoys are the operations with higher probability of oil spills. Minor spills are most probable, while major oil spills found very unlikely but possible.