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Given the complexity of Search and Rescue (SAR) activities in the coastal regions of Eastern Canada and the Arctic, there is a need to objectively assess system capabilities at a high level to determine the expected rescue time for multiple scenarios and system configurations. This paper outlines a new macro-scale generalized SAR model to simulate the main activities within the SAR system in Eastern Canada and the Arctic. The model uses discrete event simulation to represent the SAR operations and a probabilistic Monte Carlo approach to incorporate uncertainties in performance data for the different components of the system. Algorithms are first developed to identify the major decision-relevant components of SAR response, including the time to interpret emergency notifications and mobilize helicopter resources, the operability of assets in given environmental conditions, and the proximity and capability of resources. Following this, the model is coded in MATLAB, using a time-stepping approach, enabling changes in the scenario, asset status, and system configuration at any time step. Case scenarios are used as initial verification, beginning with a simplistic approach, and building complexity in the model parameters. For this paper, we will discuss simple and complex scenarios which are based on common incident occurrences and SAR system operational details in eastern Canada's coastal regions and the Arctic. We assess the sensitivity of the overall SAR system to various input parameters to better understand how factors such as the Location of Incident (LOI) and number of People in Distress (PID) influence SAR response time in remote coastal areas, as well as the impact of refueling station locations for more distant and longer duration scenarios.

Resilience assessment and management of technical systems have been increasingly important as the current applications in the process industries are becoming more complex. Several review papers on resilience man-agement methods and applications have been published by researchers from different aspects. However, none of them put the focus on bibliometric analysis of the relevant research works especially those in the process in-dustries. This study pays attention to system resilience assessment and management, by reviewing sources of relevant publications, collaboration of institutions and authors, and development trends. In addition, the development of resilience engineering and management is further investigated through analyzing the most influential and relevant journals of process safety and environmental protection. This review provides valuable information regarding knowledge structure, evolution and influential publications, and high-level insights for future research.

Society is concerned about maritime accidents since pollution, such as oil spills from ship accidents, adversely affects the marine environment. Operational and strategic pollution preparedness and response risk management are essential activities to mitigate such adverse impacts. Quantitative risk models and decision support systems (DSS) have been proposed to support these risk management activities. However, there currently is a lack of computationally fast and accurate models to estimate oil spill consequences. While resource-intensive simulation models are available to make accurate predictions, these are slow and cannot easily be integrated into quantitative risk models or DSS. Hence, there is a need to develop solutions to accelerate the computational process. A fast and accurate metamodel is developed in this work to predict damage and oil outflow in tanker collision accidents. To achieve this, multiobjective optimization is applied to three metamodeling approaches: Deep Neural Network, Polynomial Regression, and Gradient Boosting Regression Tree. The data used in these learning algorithms are generated using state-of-the-art engineering models for accidental damage and oil outflow dynamics. The multiobjective optimization approach leads to a computationally efficient and accurate model chosen from a set of optimized models. The results demonstrate the metamodel’s robust capacity to provide accurate and computationally efficient estimates of damage extents and volume of oil outflow. This model can be used in maritime risk analysis contexts, particularly in strategic pollution preparedness and response management. The models can also be linked to operational response DSS when fast, and reasonably accurate estimates of spill sizes are critical.

PurposeThis study aims to improve understanding of how coastal maritime transport system of Vancouver Island would be disrupted in disaster events, and the strategies could be used to address such risks. Any transport disruption at the maritime leg of the supply chain can affect the needs of vulnerable residents and thus, the supply of many goods to coastal communities.Design/methodology/approachThis case study focuses on the disruption that can be expected to occur for ferries that serves coastal communities of Vancouver Island in Canada. A landslide scenario in the Fraser River (which connects coastal communities) is developed, and interviews and focus groups are used to gain understanding of the vulnerability and resilience of shipping.FindingsThe findings show that the maritime leg of the supply chain for the coastal communities of Vancouver Island is resilient to a landslide disruption of ferries. Besides, there would be no impact on the operability of tugs and barges. This study also offers suggestions for creating the conditions for increasing resilience of maritime supply chains to any such disruption.Research limitations/implicationsA research gap exists with respect to minimizing disruption in maritime supply chains, mainly in regard to lessening the impact on the vulnerable residents of coastal communities. This study contributes to filling this gap in the literature.Practical implicationsThe findings have significant implications for maritime service providers and for people working on disaster preparedness, emergency response and recovery.Originality/valueStudies which focus on alleviating the impact of disruptions in the maritime supply chains and the mitigation strategies for coastal communities are scarce in the literature.

While the concept of smart shipping is expected to shape the future of the maritime industry, its safety is still a major concern. New risks might emerge when shifting from human controllers onboard, to autonomous software controllers and remote human controllers. The uncertainties associated with the emerging risks require an efficient decision-making methodology to ensure ship safety. This paper proposes a framework for selecting Risk Control Options (RCOs) of ships with higher degrees of autonomy in the context of marine risk assessment and Formal Safety Assessment (FSA). The framework uses the System Theoretic Process Analysis (STPA) for the hazard analysis and the identification of RCOs, while Bayesian Network is employed in the framework for estimating the system risk. Integrating STPA and BN offers the possibility to cover most of the steps of both risk assessment and FSA and permits the prioritization of the identified RCOs. The proposed method is applied to a concept of an autonomous seawater coolingsystem (SWC) as an illustrative case study. The results indicate that the RCOs including sensors health monitoring and software testing should be prioritized to reduce the risk. This is unveiled by the STPA analysis which shows the risk contribution of the associated causal scenarios.

Escort and convoy are typical operations when a merchant ship navigates in ice beyond its own ice-going capability. In such scenarios, a safety distance between the front ship and the following ship is maintained. The leading vessel may suddenly decelerate or even come to a halt if it encounters a heavy ridge or thick ice floe. When this happens, the following ship needs to take actions to avoid collision with the leading vessel. An evasive operation for such collision avoidance is to break out of the channel. The safety distance can be defined as the minimum distance which is needed for successful collision avoidance. This depends on various parameters such as ice thickness, ship speed, channel width, the ship’s icebreaking capability and its manoeuvrability in ice. This paper investigates safety distance during escort and convoy by model-scale experiments and numerical simulation of a ship breaking out of ice channel. The experiments are carried out at Aalto Ice Tank and the numerical simulations are conducted via the in-house simulation software package of Aalto University Marine Technology group. The dependencies of the safety distance on ice thickness, channel width and initial speed are identified via multiple experimental and simulation runs. The simulation proves to provide accurate estimation on breakout distance through comparison with model test results, and reveals the influence of ice thickness, channel width and initial speed on the breakout distance.

This article presents a bibliometric analysis and mapping of the Chinese process safety research, focusing on the contributions made in core process safety journals and on the influences of international collaborations and knowledge sources on the developments of this research domain. Collaboration networks, term co-occurrence networks, and co-citation network were analyzed to identify trends, patterns, and the knowledge distribution of the Chinese research on process safety. Work to data has been clustered mainly on safety of chemical processes, fire and explosion, and risk management and accidents. Chinese research contributions are concentrated in only few journals, while the corresponding intellectual base draws on the wider literature focused on understanding and modeling phenomena, and on the broader risk research literature, although to a lesser extent. While various foreign authors are highly cited by Chinese authors, only very few direct collaborations with international scholars are identified. The results are used as a basis for a discussion on future research directions and developments for the community. Increased focus on uncertainty treatment and handling of black swan events, risk evaluation and economic aspects of safety decisions, interorganizational risk management, road and maritime transport of hazardous substances, risk perception and communication, and integrated safety and security assessment, are highlighted as fruitful directions for future scholarship. It is hoped that the insights obtained from this work can facilitate new and consolidated collaborations, as well as further invigorate the Chinese process safety domain, ultimately contributing to improved safety performance of process industries in China and elsewhere.

Safety climate and safety culture are important research domains in risk and safety science, and various industry and service sectors show significant interest in, and commitment to, applying its concepts, theories, and methods to enhance organizational safety performance. Despite the large body of literature on these topics, there are disagreements about the scope and focus of these concepts, and there is a lack of systematic understanding of their development patterns and the knowledge domains on which these are built. This article presents a comparative analysis of the literature focusing on safety climate and safety culture, using various scientometric analysis approaches and tools. General development patterns are identified, including the publication trends, in terms of temporal and geographical activity, the science domains in which safety culture and safety climate research occurs, and the scientific domains and articles that have primarily influenced their respective development. It is found that the safety culture and safety climate domains show strong similarities, e.g., in dominant application domains and frequently occurring terms. However, safety culture research attracts comparatively more attention from other scientific domains, and the research domains rely on partially different knowledge bases. In particular, while measurement plays a role in both domains, the results suggest that safety climate research focuses comparatively more on the development and validation of questionnaires and surveys in particular organizational contexts, whereas safety culture research appears to relate these measurements to wider organizational features and management mechanisms. Finally, various directions for future research are identified based on the obtained results.

Risk Analysis was first published in 1981, established with a vision to provide a platform for inquiry into fundamental risk-related concepts and theories, and to disseminate new knowledge about methods and approaches for identifying, analyzing, evaluating, managing, and communicating risk. The journal has also contributed significantly to a scientific understanding of specific risks related to human health and safety, engineering, ecological, and social systems. Published on behalf of the Society for Risk Analysis, the journal has become a leading platform over its 40-year history. Complementing recent celebratory overviews and perspectives on the evolution, achievements, and future challenges for Risk Analysis, this article presents a scientometric overview of the journal between 1981 and 2020. The study presents high-level insights in the journal publication trends and structure and trends in the leading countries/regions, institutions, and authors, in relation to their respective collaboration networks. Furthermore, the structure and evolution of research focus issues is analyzed, and highly cited publications are identified. The findings are primarily intended to provide high-level insights, which may be useful for early career academics and risk practitioners to understand the structure and development of the research domain, and its main contributors and topics, and for experienced researchers to reflect on the achievements and future developments.

Marine oil spills have a detrimental effect on aquatic systems. Yet, it is challenging to select appropriate technologies in the Arctic because of limited logistics support, inclement weather conditions, and remoteness, and limited research has been conducted in this direction. This article suggests a method to rank the oil response technologies, including mechanical recovery, chemical dispersant, and in-situ burning, for use in Arctic oil spill risk assessment and preparedness planning. The proposed Preference Learning based Bayesian Inference Modeling offers data-driven ranking of systems by learning a label function and considers factors such as ice covered sea areas, cold weather, and spill volume. A data generation system is developed to produce numerous oil spill scenarios, using a state-of-the-art engineering tool. Results demonstrate that the model, while simple, can efficiently and accurately select the best available technique, making it suitable primarily for marine pollution preparedness and response planning in strategic risk assessments.

Towing operations are highly reliant on the experience of the towing operators. Safety concerns arise when towing operations are subjected to environmental disturbances and dynamic traffic conditions. However, a systematic framework and approaches to enhance the safety and automation of towing operations remain lacking. This work proposes a framework of collision prevention of ship towing operations under environmental disturbance in near port waters. The focus is to prevent internal collisions between tug and assisted ship and provide early warning of possible collisions with other surrounding ships. A cooperative multi-agent control strategy is employed to specify the direction and magnitude of the towing force of the two tugs in real-time. Therefore, in the presence of environmental disturbance, the assisted ship can sail along the planned trajectory, and the acceptable safe geometric distance between each ship pair in the towing system is guaranteed. Further, a COLREGs-compliant collision alert system is designed to promptly remind the towing operators of a collision hazard with nearby ships, and different alert levels indicate different action obligations of towing operators. This proposed framework and developed methods are applied to a tandem towing system consisting of two tugs and one assisted ship to test its feasibility.

Funding Information: The first author of this work is supported by the China Scholarship Council (Grant Number: 201606950009) and Marine Technology research group in Aalto University (9170094). This work is also supported by the National Science Foundation of China (NSFC) through Grant No. 52001237 and 52001241. The work has further received financial support from the Canada First Research Excellence Fund, through the Ocean Frontier Institute. This financial support is gratefully acknowledged. Besides, we thank the two anonymous reviewers for their very insightful comments, which have been very instrumental to improve an earlier version of this work. Publisher Copyright: © 2021 This paper introduced a new ship domain concept and an analytical framework. The ship domain takes the point of the ship’s first evasive maneuver as a basis and correlates it with the navigator-perceived collision risk level. The first evasive maneuver of a ship is detected based on the ship turning point identification and ship intention estimation. The available maneuvering margin (AMM) is utilized as a proxy to measure the perceived collision risk by the navigator. Interpreting the first evasive maneuver in terms of this AMM over a large sample of vessel encounters taken from automatic identification system (AIS) data finally enables an empirical estimation of the size of this ship domain. The method is applied to AIS data in the Northern Baltic Sea, and separate ship domains are constructed for the give-way and stand-on vessels with different maneuverability characteristics. Compared to the existing proximity-based ship domain, this ship domain explicitly incorporates the dynamic nature of the encounter process and the navigator’s evasive maneuvers. Several advantages of this proposed ship domain concept and limitations of the presented modeling approach are discussed. Finally, possible future applications are explained, including waterway safety assessment and navigational decision support systems to reduce ship-ship collision risk.

Although there is a growing field of research focusing on university laboratory safety, accidents in such contexts still occur relatively frequently. Therefore, it is significant to summarize current research status and gaps, and to propose future research directions in the field of university laboratory safety. In this paper, a bibliometric analysis method was applied to gain an overall view of the developments, focus areas, and trends in this field of safety research. A total of 219 scientific publications on university laboratory safety were identified and screened from the database of Web of Science, covering 44 countries or regions, 254 research institutions, 575 authors, 126 publication sources, and 70 subject categories. Bibliometric data such as annual growth trend and distribution of subject categories were analyzed by using descriptive statistics. The most productive and influential countries, institutions, authors, and their cooperation networks were identified from co-citation maps created by VOSviewer. Further analysis was carried out to find out the core publications and publication sources in this field. Insights in the focus areas and research topics over time were obtained through terms co-occurrence analysis. The results indicate that university laboratory safety is a highly multidisciplinary research field. However, it is still a young discipline and belongs to the minority research field when compared with other safety domains. Several avenues for future research are identified to advance and make progress in this field.

The automatic identification system (AIS) has become a key element in maritime domains of inquiry and the number of related articles has increased rapidly. The systematic integration of AIS data with other datatypes has received less attention and has mostly resulted in application-specific datasets that are small relative to the available AIS data. This work presents an accumulating multi-purpose database for the northern Baltic Sea that combines nine years of AIS data with marine environmental data. The main application is winter navigation research, for which purpose the environmental data is from ice charts and ice drift models. The AIS data is from terrestrial stations and amounts to 6 billion messages. It has a full update rate which is also required for the analysis of ice navigation as this involves close encounters, icebreaker assistance, convoy operations, and rapid speed changes. To identify and study such traffic features, distances between ships that are close to each other are included in the database. Application examples are given for spatial traffic statistics, reduction of ship speed with increasing ice thickness, and for icebreaker assistance.

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.

The growing interest for Arctic and Antarctic shipping activities due to the decreasing ice cover will also increase the risks of accidents on these waters. The design of ships for ice has traditionally been based on the practical experience without a clear link to the physics of the ship-ice interaction. The rules are, however, getting more towards the goal based approach, which require good knowledge of all the various element important for design. Risk based ship design (RBSD) is also widely applied e.g. for the passengers ships. Therefore, the scope of this paper is the review of the knowledge necessary for RBSD for Arctic conditions. The main focus is on ice loads and ship structures. Accident prevention and environmental consequences of oil spills are also discussed, but more briefly. In risk analysis, there is a recent focus on the treatment of uncertainty, or conversely, the strength of knowledge underlying the risk quantification. In light of this, the review is performed with specific focus on the strength of evidence of the different fields of knowledge needed to perform RBSD in ice conditions. The results indicate that the risk based design for Arctic operations is challenging as the ice environment, together with all the possible ship-ice contact scenarios, are complicated to define properly, especially on proper probabilistic terms, The main challenges are still related how to describe the ship-ice interaction parameters such as ship-ice contact characteristics, pressure distributions, and load levels in all the various ice conditions. In addition, the possible environmental consequences of the accidents need further research. Finally, human factors need to be incorporated in risk analysis techniques.

The Baltic Sea is a unique and sensitive brackish-water ecosystem vulnerable to damage from shipping activities. Despite high levels of maritime safety in the area, there is a continued risk of oil spills and associated harmful environmental impacts. Achieving common situational awareness between oil spill response decision makers and other actors, such as merchant vessel and Vessel Traffic Service center operators, is an important step to minimizing detrimental effects. This paper presents the Next-Generation Smart Response Web (NG-SRW), a web-based application to aid decision making concerning oil spill response. This tool aims to provide, dynamically and interactively, relevant information on oil spills. By integrating the analysis and visualization of dynamic spill features with the sensitivity of environmental elements and value of human uses, the benefits of potential response actions can be compared, helping to develop an appropriate response strategy. The oil spill process simulation enables the response authorities to judge better the complexity and dynamic behavior of the systems and processes behind the potential environmental impact assessment and thereby better control the oil combat action.