Search

The presented work shows a methodology for the ultimate strength assessment of a ship hull, considering enhanced corrosion modelling. The approach is based on the classical Smith method. However, the recent findings regarding the impact of corrosion degradation on ultimate strength are incorporated. To this end, the stress–strain relationships for particular elements composing ship hull cross-section are modified using a specially developed correction factor. The proposed approach is validated with experimental results of the corroded box girders available in the literature, showing very good agreement. Further, a case study of a VLCC tanker ship is presented, and a comparison between contemporary and enhanced corrosion degradation modelling in terms of resulting ultimate strength is presented. The results indicate that the currently used method may significantly overestimate the hull's structure capacity, especially considering the long exploitation period. Thus, current approaches lead to a non-conservative assessment of the ship hull girder's ultimate strength, potentially increasing the risk of failure. It is therefore recommended to further investigate the proposed method, especially in the context of risk-based ship design approaches and holistic maritime transportation risk management. • Novel approach to consider corrosion in ultimate strength check of ship hull is given. • Proposed method is validated with available experimental results showing good agreement. • The case study of VLCC tanker is analysed considering a classical and novel approach. • Current method significantly overestimates ultimate strength increasing failure risk. [ABSTRACT FROM AUTHOR]

Designing maritime safety management systems commonly follows basic processes which focus on fulfilling the demands of the regulations in the industry. This provokes designing systems with limited application which are not capable to efficiently use the guidance contained in regulatory demands, and more importantly, creating systems which are not capable of representing, evaluating, and improving the dynamic management of safety-critical organizations. This article proposes a safety system engineering process for designing maritime safety management systems which is based on the Systems-Theoretic Accident Modelling and Processes (STAMP). This process is applied for sketching the safety management of the Vessel Traffic Services in Finland. The aim is to systematically represent the function of the utilized controls for ensuring the internal VTS safety management and the safety of navigation in Finnish sea areas. The outcome of this study provides a descriptive process of analysis for designing maritime safety management systems. In this process, two other concrete elements are included for supporting the functioning of the safety management system to be designed. First, the adaptation of an identification process for determining key performance indicators for planning, monitoring and evaluating the functioning of the safety management system. Second, the constitution of a performance monitoring tool capable of executing the monitoring, measuring, and updating of the determined key performance indicators and the general functioning of the designed safety management system. [ABSTRACT FROM AUTHOR]

Abstract In northern sea areas such as the Baltic Sea and the Arctic, especially in winter conditions, the presence of sea ice frequently necessitates icebreaker assistance operations for vessels navigating in these areas. Icebreaker escort operations are important for ensuring the safety of navigation in these harsh environments. While these operations reduce the overall system risk, studies have shown that specific navigational risks are associated also with escort operations, necessitating appropriate training and operational support for ship crew engaged in these. In this paper, the icebreaker escort operations are investigated, and a ship-following model is proposed, drawing on similarities with the car following phenomenon. This ship-following model accounts for the necessity of keeping an appropriate safety distance to avoid collision, as well as for the effects of sea ice on the operation. Its main intended use is for implementation in maritime simulators, providing a realistic environment of operational conditions for training ship crews. As a first approximation, the model accounts for the ice condition by the average ice thickness, while the safety speed constraint is relative to the vessel's ability of navigating in ice. The model parameters are calibrated using empirical data of icebreaker escort operations. Case studies are executed, showing good agreement between the simulation model and real-world operational conditions. Highlights • A ship-following model for icebreaker escort operations is proposed. • Safety distance and the effects of sea ice on the operation are accounted for. • Main intended use of the proposed model is for implementation in maritime simulators. • The model parameters are calibrated using empirical data of icebreaker escort operations. • Case studies show good agreement between the simulation model and real-world operations. [ABSTRACT FROM AUTHOR]

• A theoretical validation framework for the STPA technique based on the literature in closely related fields, namely risk science, social science, and operations research, system dynamics, and simulation modeling disciplines is proposed. • With this framework, it is aimed to propose a starting point in developing a formal validation framework for STPA. • The proposed framework consists of well-grounded set of tests that are elaborated as guide questions, with a focus on different steps, to assess their validity subjectively and formatively. • The framework limitations and several future research directions are elaborated in the discussion section. Validation is a prominent challenge in the domain of risk management in general, and hazard analysis in particular. Practitioners have highlighted a lack of clear guidance on how to perform validation of hazard analyses, who should be involved, and when to stop the validation process. Aiming to contribute to addressing this issue, this study proposes a validation framework for the System Theoretic Process Analysis (STPA) technique, based on foundational concepts in risk analysis and prior theoretical work on validation in related disciplines. STPA, which is a hazard analysis technique based on System-Theoretic Accident Model and Processes (STAMP) accident causality model, is selected due to its increasing popularity in different industries, and because no validation frameworks have yet been proposed for this technique. The proposed STPA validation framework aims to support a systematic assessment of the analysis's comprehensiveness, accuracy, and credibility. It consists of a set of theory-based concepts that are elaborated as guide questions, each focusing on different aspects of STPA. The framework employs a formative approach, i.e., it aims to help stakeholders systematically reason about the analysis and advise on improvements or further elaboration. To develop this framework, theoretical validation concepts in the pertinent literature in risk science, social science, and operations research, system dynamics, and simulation modeling disciplines have been used. It is recognized that the proposed framework should be further tested to confirm its practical usefulness, and it should be investigated whether it indeed improves the hazard analysis in terms of the envisioned functions. [ABSTRACT FROM AUTHOR]

• As reported by interviewed practitioners, most hazard analyses are performed using traditional methods, based upon linear accident causality models. • Expert reviews and benchmark exercise are the only hazard analysis validation methods reported by the interviewed practitioners. • A formalized process on how to validate hazard analysis is highlighted by practitioners as one of the important opportunities for improvements. • Several opportunities for organizations, regulatory bodies, and academic institutions are identified to improve the current state of the practice in both hazard analysis and hazard analysis validation. While many hazard analysis techniques exist, little empirical research has been dedicated to their use in industrial contexts, in particular concerning how practitioners validate hazard analyses. This raises questions about the accuracy, comprehensiveness, and credibility of safety analyses, and how practitioners consider this issue in relation to the overall system safety work. Acquiring qualitative evidence regarding the validation of hazard analysis among practitioners is important to support evidence-based safety practices. This paper qualitatively investigates the state of practice in hazard analysis and its validation for system safety among practitioners. Twenty semi-structured interviews were conducted with practitioners in safety–critical industries in North America. Feedback from practitioners indicates that only a limited number of hazard analysis methods are applied in industry, which are mainly based upon linear accident theory. It is also found that almost all practitioners perform some form of validation as they believe this type of safety work improves safety. Experts Reviews and benchmark exercises are the only methods reported for validating hazard analysis. In addition, practitioners highlighted several weaknesses of the current hazard analysis and hazard analysis validation practices, of which subjectivity is seen as the most important one. The authors discuss this in context of the emerging academic consensus that hazard analysis is inherently subjective, but that it can nevertheless be very useful especially when it relies on strong evidence. Also, several opportunities for organizations, regulatory bodies, and academic institutions are identified to improve the current state of the practice in both hazard analysis and hazard analysis validation. [ABSTRACT FROM AUTHOR]

For the design and transit simulation of ice-going ships, a number of methods have been proposed for the prediction of ship resistance and transit speed in various ice conditions. In this paper, selected methods for ship performance in level ice, ridged ice and channel ice are evaluated based on full-scale measurement data of two ships. Uncertainties are identified and evaluated for a better understanding of the deviations in the results. Ice thickness in full-scale data was measured using multiple methods to minimize the uncertainty. The thickness of level ice was measured by a stereo camera system. The ridge profile was identified through measurement with an electromagnetic device. Visual observation was conducted for the description of encountered ice conditions. For a better estimation of ship net thrust through propulsive data, the net thrust model is revised in this paper to take the effect of power and propeller pitch into consideration. The results show that for transit simulation, the selected methods for level ice give acceptable prediction of ship speed with certain underestimation. For ridged ice, the method seems to underestimate the speed, especially when a ship needs to conduct ramming operation. Data acquisition is the most problematic for the investigation of channel ice. The uncertainties due to the modelling of sub-processes and ice properties lead to certain scatter in applying these methods for speed prediction. Possible improvements are given as the conclusion of this work. [ABSTRACT FROM AUTHOR]

Recently, there have been several calls for increased attention to foundational issues in risk analysis, addressing issues like terminology, principles and theories. An important foundational issue is the appropriateness of different concepts and perspectives for analyzing risk in practical applications. Several authors have addressed this through arguments involving, inter alia, the definition of risk, the ontology of risk, and the reliability and validity of risk analysis. This paper aims to contribute to this discussion by focusing on the concept of prediction. While this term is quite frequently used in risk analysis contexts, no earlier work has specifically focused on the issue of whether risk analyses can be considered to be predictive, and if so, in what sense. Neither has this been linked to the feasibility of risk perspectives. First, two definitions of what prediction can mean are elaborated, and criteria corresponding to these definitions are outlined to facilitate the subsequent discussion. A brief discussion on system types is included, as one type of prediction is defined through the relation between the model and the modeled system. Then, the definitions of prediction and the corresponding criteria are used to consider the appropriateness of two commonly used risk perspectives, namely the probability of frequency and the uncertainty perspective. In the former, a risk analysis aims at estimating an underlying true risk with quantified uncertainty bounds. In the latter, a risk analysis is a descriptive account of judgments and uncertainties by an assessor. It is finally argued that the uncertainty perspective generally is more appropriate than the probability of frequency perspective for practical risk analysis applications. [ABSTRACT FROM AUTHOR]

Quantitative risk analysis (QRA) is widely applied in several industries as a tool to improve safety, as part of design, licensing or operational processes. Nevertheless, there is much less academic research on the validity and validation of QRA, despite their importance both for the science of risk analysis and with respect to its practical implication for decision-making and improving system safety. In light of this, this paper presents a review focusing on the validity and validation of QRA in a safety context. Theoretical, methodological and empirical contributions in the scientific literature are reviewed, focusing on three questions. Which theoretical views on validity and validation of QRA can be found? Which features of QRA are useful to validate a particular QRA, and which frameworks are proposed to this effect? What kinds of claims are made about QRA, and what evidence is available for QRA being valid for the stated purposes? A discussion follows the review, focusing on the available evidence for the validity of QRA and the effectiveness of validation methods. [ABSTRACT FROM AUTHOR]

Winter navigation is a complex but common operation in the Northern Baltic Sea areas. In Finnish waters, the safety of the wintertime maritime transportation system is managed through the Finnish–Swedish winter navigation system. This system results in different operational modes of ship navigation, with vessels either navigating independently or under icebreaker assistance. A recent risk analysis indicates that during icebreaker assistance, convoys operations are among the most hazardous, with convoy collisions the most important risk events. While the accident likelihood per exposure time is rather low, accidents occur almost every winter. Even though these typically lead to less serious consequences, accidents leading to ship loss and oil pollution have occurred and may occur in the future. One aspect of ship convoy navigation in ice conditions is the distance kept between the icebreaker and the ships in the convoy, a form of the well-known ship domain concept. While operational experience naturally is a valuable source of information for decision making about the distance of navigation in convoys, systematic analyses are lacking. The aim of this paper is to investigate selected operational aspects of convoy navigation in ice conditions in the Finnish waters of the Gulf of Finland, based on data of the Automatic Identification System and sea ice hindcast data. Focus is on obtaining qualitative and quantitative knowledge concerning distances between vessels in escort and convoy operations and the respective transit speeds, conditional to ice conditions. Such empirical knowledge can support operational decision making, contributing to wintertime maritime safety. [ABSTRACT FROM AUTHOR]

Risk ranking is a widely used technique for selecting and prioritizing multiple risks facing an organization or decision maker. In industrial practice and in academic work, risk ranking methods are commonly based an implicit risk conceptualization, adopting a particular foundational perspective and accounting for selected factors. Nevertheless, different stakeholders may adhere to various risk conceptualizations, applying different foundational perspectives and accounting for different factors in the ranking process. Identifying a gap in the literature to coherently consider these different foundations, this paper presents an approach for reconciling different foundational perspectives and stakeholder views, accounting for uncertainties about these. The approach is presented based on three foundational perspectives (the expected value, uncertainty and moral perspective), and developed as a Bayesian Network – Influence Diagram. The main use of the model is to make possible controversies in risk prioritization explicit, facilitating stakeholder deliberation. The model can easily be extended with new perspectives on risk ranking, or adapted based on additional knowledge about other aspects, e.g. relating to risk perception. The graphical representation allows insights into the contribution of various aspects, facilitating the selection of appropriate risk management actions. The developed model is applied to an example, suggesting that the envisaged benefits of the proposed approach are plausible. It is concluded that the novel approach has a clear potential for reconciling different foundational perspectives and stakeholder views on risk ranking. Nevertheless, it is stressed that the conceptual contribution made in this paper should be more elaborately tested in practical settings, substantiating the findings further. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Usually the improvements of human performance in the course of ship design process is carried out by modifying local ergonomics, like electronic visualisation and information display systems on the bridge or in the engine control room, stair or hatch covers design. However, the effect of global design factors (GDFs), such as ship motion, whole body vibration and noise, on human performance has not been given attention before. Such knowledge would allow the improvements of human performance by effective design modification on very early stage of ship design process. Therefore, in this paper we introduce probabilistic models linking the effect of GDFs with the human performance suitable for ship design process. As a theoretical basis for modelling human performance the concept of Attention Management is utilized, which combines the theories described by Dynamic Adaptability Model, Cognitive Control Model and Malleable Attentional Resources Theory. Since the analysed field is characterised by a high degree of uncertainty, we adopt a specific modelling technique along with a validation framework that allows uncertainty treatment and helps the potential end-users to gain confidence in the models and the results that they yield. The proposed models are developed with the use Bayesian Belief Networks, which allows systematic translation of the available background knowledge into a coherent network and the uncertainty assessment and treatment. The obtained results are promising as the models are responsive to changes in the GDF nodes as expected. The models may be used as intended by naval architects and vessel designers, to facilitate risk-based ship design. [ABSTRACT FROM AUTHOR]

Navigational accidents in wintertime conditions occur relatively frequently, yet there is little systematic knowledge available about the circumstances under which these occur. This paper presents an analysis of navigational shipping accidents in the Northern Baltic Sea area which occurred in the period 2007–2013. The analysis is based on an integration of various data sources, aiming to reconstruct the accident conditions based on the best available data sources. Apart from basic accident information from the original accident databases, data from the Automatic Identification System is used to obtain insight in the operation type during which the accident occurred, as well as into other dynamic aspects of the accident scenario. Finally, atmospheric and sea ice data is used to reconstruct the navigational conditions under which the accidents occurred. The analysis aims to provide qualitative insights in patterns and outlier cases in the accidental conditions. Correspondingly, visual data mining is selected as analysis approach, because of its utility in obtaining qualitative knowledge from data sources through a combination of visualization techniques and human interaction with the data. Special attention is given to the strength of evidence of the identified accident patterns. The results are primarily useful for improving risk analyses focusing on oil spill risks in winter conditions and for developing realistic training scenarios for oil spill response operations. [ABSTRACT FROM AUTHOR]

Ice management enables offshore and marine activities in Arctic waters in the presence of sea ice or icebergs. The presence of ice introduces additional risks to the activities. This paper discusses the risks in the light of novel risk perspectives, emphasizing uncertainties arising from potentially weak background knowledge in ice management operations. An ice management system is defined and a generic risk picture of an ice management operation is created. Risk theory is connected to the results using discussion and a conceptual example. Ice management operations are complex socio-technical systems requiring expertise in various fields. Available data is scarce and uncertainties are high. Still, the main activities need to trust in the ice management system to operate safely. The risks in ice management operations culminate in decision making and physical ice management. These need to be better understood to manage the operational risks. [ABSTRACT FROM AUTHOR]

Maritime accidents have the potential to cause significant financial loss, injury, and damage to the environment. One approach to investigating maritime safety is to focus on near misses, that is, situations which did not lead to an accident but where an accident was narrowly avoided. Based on the principles of the traffic conflict technique, which ranks traffic encounters through a conflict severity hierarchy, this paper proposes a novel model for screening maritime traffic data for near miss ship-ship encounters, particularly for open sea and coastal restricted sea areas. Compared to previous methods, the proposed method has a greater specificity, leaving fewer possible near miss cases to be assessed by navigational experts in a contextualised traffic setting. This is achieved by including the effect of ship size through a ship domain, and by better accounting for the criticality of the encounter direction through the Minimum Distance To Collision concept compared to earlier proposed models. The factors included in the model and their relation are based on expert judgments and using knowledge from previous studies. Model parameters are derived from AIS data points from a reference encounter situation dataset. The developed model has been applied to traffic data from the Northern Baltic Sea. The model is subjected to a number of validity tests, the results of which suggest that the model is adequate for ranking and prioritizing encounters for further assessment in an expert judgment phase to identify near misses. Thus, it establishes a method to enable subsequent research into the validity of near miss information to make statements of maritime safety in relation to collision accidents. [ABSTRACT FROM AUTHOR]

Natural and man-made disasters can disrupt road networks. The post-disaster period is usually divided into short and long-term response phases. In the short-term phase, blocked roads can jeopardize emergency operations such as search-and-rescue, evacuation of victims, and the distribution of emergency supplies. The detritus may pose an environmental challenge in the long-term, as the rubble must be properly collected, disposed of, and recycled. Optimization models designed to schedule repair and restoration activities and determine the repair crews' routes are helpful to give insights to decision-makers on how to improve emergency response plans. This article presents a literature review on short and long-term network models designed for roads repair and restoration. This review identifies the trends in publications, solution approaches, frequency of locations and type of disaster in the case studies, and the size of the networks. In addition, a qualitative analysis of the models' characteristics, such as the type of network, uncertainties, and interdependencies, is presented. A discussion is provided to indicate future research directions. Among these, future research should focus on the combination of roads repair and restoration with other emergency activities such as relief distribution. • A review of road network restoration and recovery models in the context of natural disasters is presented. • Mixed Integer Programming and Genetic Algorithms are the most used solution methods. • The applications are mainly on earthquake scenarios in the United States, China, and Turkey. • Road network repair and restoration models combined with other emergency operations is an emerging research direction. • Based on the identified trends, several research directions are proposed to advance the field. [ABSTRACT FROM AUTHOR]

Efficient response to maritime incidents and accidents requires good communication processes and situation awareness by all involved parties, in particular between the Search and Rescue (SAR) response operators and the crew of the distressed vessel. In this paper, a method is proposed for enhancing the communication between the involved parties, by focusing on the safety status of the vessel. Borrowing ideas from well-established working methods in especially emergency medicine, the Vessel TRIAGE method has been established through a broad stakeholder consultation process. Its intended application is to assess and communicate whether a vessel can provide a safe environment for the people onboard. Using a set of threat factors and a four-level ship safety categorization, the method aims to establish a shared understanding of the nature of the distress situation, which in turn has implications for the operational focus of the SAR operators and vessel crew. An evaluation of the proposed method indicates a positive reception among various maritime stakeholders, suggesting that implementing the Vessel TRIAGE method in maritime SAR procedures may act as a useful tool to assist in the management of maritime distress situations. [ABSTRACT FROM AUTHOR]

Risk matrices and risk diagrams are widely used tools for analyzing, assessing and visualizing risk in many industries, and are used extensively for risk management purposes. Despite their popularity and wide application, they have recently become the object of discussion and research in scientific environments, which can be seen as part of a wider focus on foundational issues in the risk analysis discipline. Identifying several serious limitations and problems with the risk matrix approach, various authors have proposed extensions, modifications and recommendations for their use. One issue which has been raised recently but has attracted relatively limited scientific attention is the consideration of uncertainty in risk diagrams, i.e. how to visually represent and communicate uncertainty. This paper first reviews the available proposals for this question. Subsequently, the strengths and weaknesses of these proposals are discussed. Finally, some new proposals are made on how to represent uncertainty in risk diagrams in practical applications. [ABSTRACT FROM AUTHOR]

Various methods have been proposed to analyse safety and risk of maritime transportation, through modelling techniques and empirical studies, focusing on ship–ship collision. However, an efficient method for screening traffic data for the near miss collisions is lacking. Therefore the contribution of this paper is two-fold. First, it proposes a novel method detecting possible near miss ship–ship collisions from AIS data. Second, it discusses how such near miss data can be used to gain further insight in safety of maritime transportation. The developed Vessel Conflict Ranking Operator (VCRO) considers the following factors affecting the complexity of an encounter between two ships: the distance between the two ships, the relative speed of the ships, and the difference between the headings of the ships. The model content and structure are based on expert judgment, whereas the parameterisation is based on AIS data points of a reference encounter situation dataset. The developed model has been applied to the traffic data from the Northern Baltic Sea. The obtained results and the model validity tests suggest the model being adequate for ranking encounters, and for prioritising the encounters to subject to further expert scrutiny. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In many sea areas there is significant recreational activity, with many sailing vessels and motor boats navigating, especially in coastal areas. Search and Rescue (SAR) organizations ensure the safety of people at sea, and are relatively frequently called to perform rescue or assistance missions to people in distress. Apart from the importance of adequate operational planning and training, rescue organizations benefit from establishing a robust, effective and cost-efficient response system. Risk-informed capacity planning can serve as a decision-support tool for determining the number and location of the required search and rescue units (SRUs). The purpose of this paper is to present such a risk-informed approach, which combines analysis of historic accident and incident data of recreational boating with information derived from Geographic Information System (GIS) methods. The method is applied to a case study focusing on the risk-informed capacity evaluation of the voluntary search and rescue services in the Finnish part of the Gulf of Finland. Results indicate that the response performance for recreational boating incidents is very good in most areas. [ABSTRACT FROM AUTHOR]

Ship collisions are rare occurrences with a potential to cause significant human, monetary and/or environmental loss. One element in preventing collision accidents is the presence of a collision alert system (CAS), providing warnings to ship crews and/or personnel in Vessel Traffic Services of the collision risk in a real-time operational environment. In risk research, there is a recent focus on foundational issues related to risk concepts, perspectives and methods for describing risk, with calls for work addressing these risk-theoretical issues in application areas. Despite several proposed applications for CAS, no frameworks covering these risk-theoretic issues have been presented. Hence, the purpose of this paper is twofold. First, a framework for maritime risk-informed CAS (RICAS) is presented, including a risk-conceptual basis, a systematic description of the risk perspective and a discussion on the intended use of the risk model. A theoretical framework for the operationalization of the construct “ship collision risk” is presented, and a method for measuring this construct is introduced. Second, the framework is applied to a case-study concerning open sea navigation. An evaluation of the proposed RICAS in comparison with earlier proposed CAS methods indicates an improved performance over these. [ABSTRACT FROM AUTHOR]

This paper proposes a framework for risk analysis of maritime transportation systems, where risk analysis is understood as a tool for argumentative decision support. Uncertainty is given a more prominent role than in the current state of art in the maritime transportation application area, and various tools are presented for analyzing uncertainty. A two-stage risk description is applied. In the first stage, Bayesian Network (BN) modeling is applied for probabilistic risk quantification. The model functions as a communication and argumentation tool, serving as an aid to thinking in a qualitative evidence and assumption effect assessment. The evidence assessment is used together with a sensitivity analysis to select alternative hypotheses for the risk quantification, while the assumption effect assessment is used to convey an argumentation beyond the model. Based on this, a deliberative uncertainty judgment is made in the second risk analysis stage, which is supplemented with a global strength of evidence assessment. The framework is applied to a case study of oil spill from tanker collisions, aimed at response capacity planning and ecological risk assessment. The BN-model is a proactive and transferable tool for assessing the occurrence of various spill sizes in a sea area. While the case study uses evidence specific to the Gulf of Finland, the model and risk analysis approach can be applied to other areas. Based on evaluation criteria and tests for the risk model and risk analysis, it is found that the model is a plausible representation of tanker collision oil spill risk. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 40 cm 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. [ABSTRACT FROM AUTHOR]

For safe and efficient exploitation of ice-covered waters, knowledge about ship performance in ice is crucial. The literature describes numerical and semi-empirical models that characterize ship speed in ice. These however often fail to account for the joint effect of the ice conditions on ship's speed. Moreover, they omit the effect of ice compression. The latter, when combined with the presence of ridges, can significantly limit the capabilities of an ice-strengthened ship, and potentially bring her to a halt, even if the actual ice conditions are within the design range for the given ship. This paper introduces two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is likely to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models, two full-scale datasets were utilized. First, the dataset about the performance of a selected ship in ice is acquired from the automatic identification system. Second, the dataset containing numerical description of the ice field is obtained from a numerical ice model HELMI, developed in the Finnish Meteorological Institute. The collected datasets describe a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The relations between ship performance and the ice conditions were established using Bayesian networks and selected learning algorithms. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. [ABSTRACT FROM AUTHOR]

• A fuzzy SoE (strength of evidence) index is developed based on fuzzy logic theory. • The ambiguity issue of SoE raised in the literature in risk analysis is tackled. • Full digitalization of all elements in risk R C , P , S o E BK) is enabled. • The integration of fuzzy SoE index to BNs (Bayesian networks) is demonstrated. • Their integrated features showcase an improved system risk management approach. Digitalization is becoming a trend in our modern society and systems. Meanwhile, risk analysis and management has rooted and been applied in various fields. Therefore, there is an increasing need to integrate risk analysis and management into the coming digital society. Risk has been represented digitally by the product of probability and consequence i.e. R = P × C traditionally. However, it has been increasingly discussed to include strength of evidence (SoE) in addition to the traditional consequence (C) and probability (P). Although much advance has been achieved along this direction, there still remains challenges, e.g. ambiguity in rating SoE and visual expression of risk diagrams. This paper focuses on addressing these issues and meanwhile aims to make the risk expression fully digital so that it is more efficient and flexible to be included in a system analysis and visualization. This is achieved firstly by reviewing state-of-the-art discussions on SoE assessment in risk management and identifying the remaining challenges. Then, the paper proposes an approach to address the challenges by forming a fuzzy logic SoE index based on fuzzy logic theory, which enables a transfer from linguistic variable to a digital one with the ambiguity avoided. After the SoE index is formed, it is applied into BNs as the node size index to demonstrate its practical application. Meanwhile, with the BNs forming the infrastructure to calculate and present consequences and probabilities, it showcases a new system risk management approach. All the variables in the system can be expressed in a risk diagram. This further enables an improved risk visualization, risk management and risk communication for system analysis, towards risk digitalization. [ABSTRACT FROM AUTHOR]

Abstract: 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. Therefore this article discusses methodological requirements for the risk perspective, which is appropriate for risk management in the maritime domain with special attention to maritime transportation systems. A perspective that is proposed here considers risk as a set encompassing the following: a set of plausible scenarios leading to an accident, the likelihoods of unwanted events within the scenarios, the consequences of the events and description of uncertainty. All these elements are conditional upon the available knowledge (K) about the analyzed system and understanding (N) of the system behavior. Therefore, the quality of K and the level of N of a risk model should be reflected in the uncertainty description. For this purpose we introduce a qualitative scoring system, and we show its applicability on an exemplary risk model for a RoPax ship. [Copyright &y& Elsevier]

Highlights: [•] Reliability and validity of ship–ship collision risk analysis methods investigated. [•] Focus on probability- and risk indicator perspectives. [•] Varying internal reliability and low cross-methodological reliability found. [•] Both accuracy of total system risk and rank order of subsystem risk questioned. [•] More valid definitions of the ship encounter process needed to reduce uncertainty. [ABSTRACT FROM AUTHOR]

Abstract: A number of authors have proposed probabilistic risk based ship design for ship–ship collision, conditional to the local trading area of a vessel. The probability of collision and consequences are determined based on the traffic conditions in which a vessel is expected to operate. This paper investigates the adequacy of currently available models for impact scenarios, i.e. models linking the traffic conditions to the conditions at the moment of collision. An exploratory statistical model is presented to establish such a link. A probabilistic risk based design case study is performed for a fleet of RoPax vessels trading on a specified route in the Gulf of Finland. The available impact scenario models from the literature are compared with the developed probabilistic evasive maneuvering model. The results show that the impact scenario models have a very significant influence to the calculated hull breach probabilities. No well-justified impact scenario models are presently available and also the presented probabilistic evasive maneuvering model is burdened with uncertainty. Hence, to move toward a probabilistic risk based ship design paradigm for ship–ship collision in a local trading area, more focus and research is needed to establish a credible link. [Copyright &y& Elsevier]

• Benefits, concerns, and safety perceptions of autonomous urban vessels are studied. • Survey and interview research methodology applied in a case study. • Results show that increased autonomy is supported, conditional to onboard operator presence. • Environmental sustainability is the most important benefit, safety the main concern. • Relations between selected demographics and safety perceptions of autonomy are explored. Autonomous vessels are envisioned to enhance safety, improve environmental sustainability, increase efficiency, and reduce costs. With much effort directed towards merchant shipping, technical designs for urban ferries are also under development to facilitate smart mobility. Safety perceptions of such autonomous ferries are likely important drivers of the adoption of such novel technologies. Understanding the public's perceived benefits and concerns can support policy makers and industry in implementing responsible risk governance and can have design and operational implications. This article explores this topic for a hypothetical autonomous urban ferry in Halifax, Nova Scotia. Through phone surveys and interviews, focus is on safety perceptions of different automation degrees, which are further explored in relation to selected population characteristics. Improved environmental performance is the most important perceived benefit, whereas safety is the most important concern. Overall, there is support for increased automation, but an on-board presence of qualified operators is considered important for safety and security related reasons. Remotely controlled ferries without onboard personnel or fully autonomous vessels are generally perceived as (very) unsafe. Men are slightly more favourable of increased automation than women, as are people with more digital knowledge and skills. Acknowledging several limitations of this exploratory study, of which the focus on older age groups in the studied population is the most significant, the findings suggest that understanding the public's safety perceptions is important to ensure the successful design, implementation, and operation of autonomous urban, so that the envisaged benefits of these new systems can be achieved. [ABSTRACT FROM AUTHOR]

Abstract: An important element in assessing the consequences in a tanker collision is the probability of breaching an oil cargo tank. It is well recognized that the dynamic parameters at the moment of impact significantly affect the deformation energy. Assumptions regarding dynamic parameters at the moment of impact are nevertheless little discussed in context of collision risk analysis. The available impact scenario models are analyzed using a system risk approach. Comparison of impact scenario models from literature is performed with a risk analysis algorithm emphasizing on oil tanker collisions. Monte Carlo simulation is applied in the risk analysis algorithm for each impact scenario model. Only the impact scenario module is changed while other modules of the algorithm (encounter scenario generation, determination of deformation energy and structural hull capacity) are kept the same. Analysis reveals important differences in results of risk analysis when performed with different assumptions for the impact scenario. Moreover, in the discussion inherent conceptual limitations of the impact scenario models in the system risk framework are revealed. It is concluded that using more accurate collision energy and/or structural capacity models for purposes of maritime traffic risk analysis is currently not worthwhile, as the uncertainty regarding impact scenario is overwhelming. [Copyright &y& Elsevier]

Abstract: In this paper, a study leading towards a new definition of a ship–ship collision criterion, allowing further estimation of the probability of maritime accidents is conducted. The criterion is called the minimum distance to collision (MDTC) and reflects the shortest distance between two ships at which they must take evasive actions to avoid a collision. The new criterion is evaluated by means of a series of simulations using a ship motion model for a range of ship types, courses and speeds and thus its dynamic nature is recognised. It addresses the crossing type of ship–ship encounter. Additionally, this study defines a causation factor, which quantifies the proportions of cases in which two ships meeting each other end up having a collision. The causation factor is obtained in the course of maritime traffic analysis and accidents statistics. A comparative method is applied and the causation factors are determined for three different meeting types (head-on, crossing and overtaking). The causation factors obtained are valid for the MDTC model, chosen location and prevailing traffic conditions. The major factors affecting the MDTC criterion and relevant steps in the evaluation of the causation factors are described and discussed in the paper. [Copyright &y& Elsevier]

Abstract: Maritime traffic poses various risks in terms of human, environmental and economic loss. In a risk analysis of ship collisions, it is important to get a reasonable estimate for the probability of such accidents and the consequences they lead to. In this paper, a method is proposed to assess the probability of vessels colliding with each other. The method is capable of determining the expected number of accidents, the locations where and the time when they are most likely to occur, while providing input for models concerned with the expected consequences. At the basis of the collision detection algorithm lays an extensive time domain micro-simulation of vessel traffic in the given area. The Monte Carlo simulation technique is applied to obtain a meaningful prediction of the relevant factors of the collision events. Data obtained through the Automatic Identification System is analyzed in detail to obtain realistic input data for the traffic simulation: traffic routes, the number of vessels on each route, the ship departure times, main dimensions and sailing speed. The results obtained by the proposed method for the studied case of the Gulf of Finland are presented, showing reasonable agreement with registered accident and near-miss data. [Copyright &y& Elsevier]

• Natural disasters can lead to maritime transport disruptions to coastal communities • A Bayesian Network model is developed to estimate maritime transport delays • The model is specific to the coastal areas of British Columbia in an earthquake context • The model can be used for multi-modal logistics in disaster preparedness risk management Coastal communities are vulnerable to the consequences of disasters such as hurricanes, earthquakes and tsunamis. Often, such communities are heavily dependent on maritime transportation for the ingress of essential goods such as food, fuel, and medicine. Major natural disasters can cause damage to critical infrastructures, causing disruptions to logistics chains and delays in the delivery of essential goods to vulnerable coastal communities. Estimating such delays is an important aspect of disaster preparedness planning, as it can support community-focused risk mitigating policies, improve emergency response operations, and help identify resilience strategies. In this article, a Bayesian Network risk model is developed for estimating the delays in maritime transportation to island communities in British Columbia, resulting from a major earthquake in the region. The model takes a regional scope and is primarily expert-driven. Correspondingly, it uses information about the earthquake intensity, infrastructure damages, impacts on shipping operations, and community needs to estimate delay times of the operability of different shipping services in the region under various scenarios. The model is illustrated through a series of hypothetical scenarios. Various validation tests furthermore indicate an adequate model performance for supporting regional disaster preparedness planning for the immediate response phase following an earthquake. [ABSTRACT FROM AUTHOR]

• Bibliographic analysis of literature on Arctic shipping risk management is presented. • Patterns in year and journal of publication, keywords, and country of origin are analyzed. • Systematic review of articles presenting quantitative risk analyses of navigational accidents is made. • Risk Influencing Factors are extracted and synthesized in a qualitative model. With the diminishing extents of Arctic sea ice, Arctic shipping becomes increasingly attractive for the shipping industry. Voyages along Arctic sea routes have seen a significant increase in recent years. Given the harsh environment, shipping operations in the Arctic constitute a hazardous activity for people onboard vessels, while vessels pose risks to vulnerable ecosystems and traditional socio-cultural environments. Given this emerging trend, this paper presents a bibliometric analysis of the broad academic literature related to risk management of Arctic shipping, published in the period from 2000 to 2019. Based on 221 articles, the bibliometric analyses provide insights in publication patterns concerning the year of publication, keywords, journals, and countries/regions from which the work originates. Furthermore, through a qualitative systematic review, this article presents a synthesis of risk influencing factors (RIFs) of navigational accidents in the Arctic, based on published quantitative risk models containing accident scenarios in Arctic shipping. To this effect, ten papers are investigated in detail, focusing on the scenario, methods, data sources, and RIFs. Identifying major thematic clusters in the RIFs, a model is proposed for synthesizing and illustrating the relationships among environmental and ship-related RIFs, and accident scenarios in Arctic shipping. A discussion is made concerning challenges in the research domain and future research directions, focusing on the strength of evidence in the risk models, the use of linear versus complex, systemic accident theories, and on the alignment of academic work with focus issues in regulatory contexts. [ABSTRACT FROM AUTHOR]

• Scientometric analyses of safety-related topics are reviewed. • An overview of data sources, scientometric methods, and tools is given. • A generic framework for performing scientometric analyses is described. • Best practices for performing scientometric research are discussed. • The overview aims to advance meaningful application of scientometrics in safety research. Scientometrics analysis is increasingly applied across scientific domains to gain quantitative insights in the development of research on particular (sub-)domains of scientific inquiry. By visualizing metrics containing quantitative information about such a domain, scientometric mapping allows researchers to gain insights in aspects thereof. Methods have been developed to answer specific research questions, focusing e.g. on collaboration networks, thematic research clusters, historic evolution patterns, and trends in topics addressed. Several articles applying scientometric mapping to safety-related topics have been published. In context of the Special Issue ' Mapping Safety Science – Reviewing Safety Research ', this article first reviews these, and subsequently provides an overview of key concepts, methods, and tools for scientometric mapping. Data sources and freely available tools are introduced, focusing on which research questions these are suited to answer. A brief tutorial-style description of a scientometrics research process is provided, guiding researchers new to this method how to engage with it. Finally, a discussion on best practices in scientometric mapping research is made, focusing on how to obtain reliable and valid results, and how to use the scientometric maps to gain meaningful insights. It is hoped that this work can advance the application of scientometric research within the safety science community. [ABSTRACT FROM AUTHOR]

The risk of a large-scale oil spill remains significant in marine environments as international maritime transport continues to grow. The environmental as well as the socio-economic impacts of a large-scale oil spill could be substantial. Oil spill models and modeling tools for Pollution Preparedness and Response (PPR) can support effective risk management. However, there is a lack of integrated approaches that consider oil spill risks comprehensively, learn from all information sources, and treat the system uncertainties in an explicit manner. Recently, the use of the international ISO 31000:2018 risk management framework has been suggested as a suitable basis for supporting oil spill PPR risk management. Bayesian networks (BNs) are graphical models that express uncertainty in a probabilistic form and can thus support decision-making processes when risks are complex and data are scarce. While BNs have increasingly been used for oil spill risk assessment (OSRA) for PPR, no link between the BNs literature and the ISO 31000:2018 framework has previously been made. This study explores how Bayesian risk models can be aligned with the ISO 31000:2018 framework by offering a flexible approach to integrate various sources of probabilistic knowledge. In order to gain insight in the current utilization of BNs for oil spill risk assessment and management (OSRA-BNs) for maritime oil spill preparedness and response, a literature review was performed. The review focused on articles presenting BN models that analyze the occurrence of oil spills, consequence mitigation in terms of offshore and shoreline oil spill response, and impacts of spills on the variables of interest. Based on the results, the study discusses the benefits of applying BNs to the ISO 31000:2018 framework as well as the challenges and further research needs. • The ISO 31000:2018 standard provides a comprehensive framework for oil spill risk management. • Bayesian Networks support the implementation of ISO 31000:2018-based risk management. • Bayesian Networks aid robust decision-making when uncertainties matter. • Bayesian Networks support participatory risk management based on continuous learning. [ABSTRACT FROM AUTHOR]

• Maritime transportation risk management: identification, analysis, and evaluation. • Comprehensive review of 50 years: bibliometric analysis, in-depth classical review. • Assessing safety, risk, reliability of maritime transportation in waterway areas. • Patterns, focus areas, emerging trends in prevention oriented risk management. • Links between research in Baltic Sea area and the global community. Various national maritime authorities and international organizations show strong interest to implement risk management processes to decision making for shipping accident prevention in waterway areas. There is a recurring need for approaches, models, and tools for identifying, analysing, and evaluating risks of shipping accidents, and for strategies for preventively managing these in (inter-)organizational settings. This article presents a comprehensive review of academic work in this research area, aiming to identify patterns, trends, and gaps, serving as a guide for future research and development, with a particular focus on the Baltic Sea Region. To understand the links between research in the Baltic Sea area and the global community, a bibliometric analysis is performed, focusing on identifying dominant narratives and social networks in the research community. Articles from the Baltic Sea area are subsequently analysed more in-depth, addressing issues like the nature of the academic work done, the risk management processes involved, and the underlying accident theories. From the results, patterns in the historical evolution of the research domain are detected, and insights about current trends gained, which are used to identify future avenues for research. [ABSTRACT FROM AUTHOR]

Ship performance in level ice involves problems such as attainable speed and maneuverability under different ice thickness. As the alternative to analytical methods, numerical simulation models have been proposed in recent years to improve the accuracy and to analyze more complex operations. However, current numerical models use quite diverse approaches to model the icebreaking components, and focus on rather different aspects, while the choices need more justification. The primary aim of this paper is to propose a framework for the development of effective and efficient numerical models to simulate ship performance in level ice, based on state-of-the-art knowledge of ship-ice interaction. This covers a discussion of modelling purposes and a hierarchical decomposition of the problem, followed by a strategy and two methods which could be applied to improve accuracy and credibility, as well as methodology of validation. Following the proposed framework, a numerical model is proposed as a prototype model, which simulates ship performance in level ice, and can be developed further in future. The numerical simulation results are compared with full-scale measurement results of a ship on the Baltic Sea, indicating reasonable estimation of ship turning. This implies the validity of the model as a prototype of the proposed framework. [ABSTRACT FROM AUTHOR]

• The technique using non-accident critical events as surrogate indicators to assess waterway risk has attracted much attention. • A critical review of the academic literature on non-accident critical events detected from AIS data is presented. • The analysis focuses on the definition, accident theory, measurement, model use, and validation of non-accident critical events. • Results indicate variations in conceptual basis and implementation, and a lack of extensive validation. The safe navigation of ships is of high societal concern. A promising approach for analyzing waterway risks is using non-accident critical events as surrogate indicators of collision accidents. These are typically detected in data from the Automatic Identification System (AIS). Recognizing the significant interest in this approach, this article provides a review and analysis of methods based on the detection of non-accident critical events from AIS data, which aim to provide insight into maritime waterway risk. Considering also recent calls for increased focus on foundational issues in risk research and safety science, each method in the literature is critically reviewed based on five questions: How are non-accident critical events defined? What is the accident-theoretical basis of the method? How are non-accident critical events ranked? How is the method used? To what extent has the method been validated? Based on the results, it is concluded that focus is needed to build evidence of the validity of the models' results, if these are to be effectively used for waterway risk analysis. As a prerequisite, more focus is needed on how exactly non-accident critical events are defined, and what factors are involved in the relation between their occurrence and accident involvement. [ABSTRACT FROM AUTHOR]

• Different MASS degrees of autonomy are interpreted in a risk governance perspective. • With higher degrees of autonomy, uncertainties and ambiguities become more significant. • Implications for societal risk governance strategies and processes are drawn. • The focus is on which stakeholders to involve, and what discourses to engage in. • Directions for future work by policy makers and researchers are identified. Recently, there has been a significant interest in industry, regulatory, and academic contexts in the prospects of Maritime Autonomous Surface Ships (MASS). Much work focuses on technical developments and discussions on legal, economic, and safety and security implications. There has been less focus and discussion on the role of different societal actors in the decision-making processes concerning the conceptualization, design, and operational implementation of these future vessels. This paper contributes to this discussion by framing the introduction of MASS in a risk governance context. After briefly introducing the International Risk Governance Council's Risk Governance Framework, the different degrees of autonomy of MASS are categorized according to their dominant risk characteristics. Subsequently, implications are drawn for the recommended risk governance strategies in approaching MASS development and implementation, and some future research areas are identified. It is argued that with higher degrees of autonomy, complexities and uncertainties become more important, necessitating an approach to MASS design and implementation where multiple affected stakeholders are included. A reflective discourse is recommended. For MASS degree of autonomy three and four, normative ambiguities may be present. In such cases, a participative discourse is recommended, where a wider societal debate is held regarding appropriate actions. [ABSTRACT FROM AUTHOR]

The lack of situational awareness is a major cause of ship collisions. Thus, enhancing the situational awareness of the stand-on ship is a key for navigational safety, where the intention estimation of the give-way ship is crucial. According to COLREGs, the stand-on ship is not allowed to take evasive actions until the give-way ship does not take proper actions timely. The stage that needs the stand-on ship to take actions plays as the second protective layer for the ship, which is named as 'Stand-on Ship as Second Line of Defense' (SLoD). A method to estimate the intention of the give-way ship and to trigger SLoD is proposed in this article. Four modules of the proposed method include: "data pre-processing" collects all traffic information and determines the ships' obligations; "action identification" pinpoints the turning points; "action uncertainty" generates a bounded reachable velocity considering the give-way ship's maneuverability; "conflict assessment" judges potential collision by using non-linear velocity obstacle algorithm. Several typical encounter scenarios are simulated to demonstrate the feasibility of the proposed method. The results show that intention estimation of the give-way ship improves the situational awareness of the stand-on ship, which can support the stand-on ship to make collision avoidance decisions. • Improving the situational awareness of the stand-on ship by intention estimation of the give-way ship. • Intention estimation considering dynamics of the give-way ship, action uncertainty and conflict. • A method identifying turning points of the give-way ship based on its trajectory. • Using reachable velocity set to bound the uncertainty of the ship action. [ABSTRACT FROM AUTHOR]

Most vessels cannot safely sail in areas with sea ice. In the Northern Baltic Sea area, the presence of sea ice often requires icebreaking ships to open up ice-covered areas so merchant vessels can proceed to their destinations. In this environment there is an increasing number of ships. With growing transport volumes in sea ice environments, icebreaker operations such as convoys have become increasingly important to ensure navigation safety. This paper proposes a model of multi-ship following for icebreaker convoy operations in continuous icebreaking conditions, using modelling principles from earlier proposed car following models combined with considerations of safe distance and safe speed in ship convoy operations in ice conditions. The model parameters are calibrated with empirical data from actual icebreaker convoy operations, using data from the Automatic Identification System (AIS) and sea ice model data. The model determines ice resistance according to ice thickness, type, and bending strength, and the main dimensions of the icebreaker leading the convoy. The maximum safe navigable speed is used to assess the following ships' ability to sail in sea ice. The multi-ship following simulation results were found to be in good agreement with empirical data. The new proposed model can provide a theoretical reference for icebreaker convoy operations, can have practical use in ship simulators to improve training, and could be useful for traffic modelling and planning purposes. • A multi-ship following model for icebreaker escort operations is proposed. • Safety distance, safety speed and the effects of sea ice on the operation are accounted for. • Main intended use of the proposed model is for implementation in maritime simulators. • The model parameters are calibrated using empirical data of icebreaker escort operations. • Case studies show good agreement between the simulation model and real-world operations. [ABSTRACT FROM AUTHOR]

Abstract The modelling of the ice failure including icebreaking pattern and ice bearing capacity is an important issue in numerical simulations of ships going through level ice, in order to predict ship performance and ice loads. Previous studies model the shape of ice cusps assuming a simplified geometry, e.g. circular or triangular. According to the observations during full-scale ship trials, the geometry of the ice cusps is more elliptical rather than circular, with larger breaking length at the edges than that at the center. In this paper, a new ice failure model is developed which results in more realistic cusp shapes compared to existing approaches. The model is based on an analytically-derived differential equation, which is solved numerically via the Finite Difference Method (FDM). The predictions of ice cusps geometry are validated against full-scale measurement of ice cusps, obtained with an on-board stereo camera system. Satisfying agreement is shown. The ice failure model is incorporated into a numerical model for the prediction of ship performance in level ice. The predictions are compared with ship speed record obtained from a full-scale trial. It is shown that the model gives reasonable results for ship speed. Highlights • An engineering ice failure model which gives more realistic icebreaking pattern compared to state-of-the-art is proposed. • This model takes various ship and ice related factors into consideration and therefore is physically sound. • The model is integrated into a numerical simulation model for ships performance in level ice. • Ice photos gathered from full-scale test are measured and analyzed to support and validate the model. [ABSTRACT FROM AUTHOR]