229 publications from this institution
The Norwegian Atlantic salmon farming industry is exploring the possibility to run fish farms in more exposed locations. The severe wave and current conditions, irregular wind, sheer remoteness, and limited weather window challenge the operational planning to avoid accidents. The objective of this paper is to present results from applying a generic list of safety-critical parameters to a net cleaning operation to assess their usefulness and relevance in aquaculture. The list was proposed based on implications from major accident causation theories in safety research. The case study demonstrated that the list is a useful operational planning tool to identify activity failure mechanisms that have potential to cause accidents. The results also have implications to how to use barrier principles in aquaculture in general.
Decision-making in emergency situations is a risky and uncertain process due to the limited information and lack of time. Some key problem parameters, such as the time required to complete important response tasks, must be estimated and are therefore prone to errors. Other parameters, such as the probability of occurrence of a consequential event, will typically change as the response operation progresses. As a result, there should be a dynamic probabilistic risk assessment framework to assess the risk level of decision scenarios and facilitate the decision-making process. In this paper, a methodology for dynamic probabilistic risk assessment of decision making in emergencies for complex marine systems is proposed. In this method, a dynamic event sequence diagram is introduced that helps to quantify events probabilities as a function of time, as well as environmental and operational variables, considering events interdependencies and uncertainties. In addition, the effects of time required1 and time available2 for performing a decision in emergency are considered in the risk model. In this methodology, probabilistic models including Bayesian network and Monte Carlo simulation are utilized to quantify the uncertain behavior of the decision-making process in complex marine systems. A computational study is also conducted to evaluate the methodology performance, in terms of effectiveness and efficiency. Computational results show that the proposed approach can obtain optimal solutions for large and practical problem sizes.
Commercial fishing is the most dangerous of professional callings, widely recognized as a major source of fatalities and injuries per population size within participating nations. The majority of reported fisheries injury accident data from a state is based solely on self-completed reporting formats. These formats are currently significantly limiting in their ability to tease out the incident specifics, being insufficiently detail orientated to adequately capture the range of contributing factors in the events that unfolded onboard. The content of these report forms ultimately determines the depth to which accidents may be probed in the interest of preventative learning. The problem faced by researchers is that the paucity of information on the circumstances of accident occurrences in these records, makes it a matter of gleaning every possible detail from relatively blank canvases. This article aims to focus the diffuse literary knowledge of the deficiencies pertinent to accident reporting in fisheries and subsequent knowledge extraction capabilities. Critiquing current reporting mechanisms, with a view to illustrating the extent of the problems, promoting the necessity for change and provoking discussion on how accident reporting could be improved in the future.
The fishing industry is plagued by a long history of fatality and injury occurrence. Commercial fishing is hence recognized as the most dangerous and difficult of professional callings, in all jurisdictions. Fishing vessels have their own unique set of hazards, a myriad collection of complex occupational accident potentials, barely controlled, co-existing in a perilous work environment. The work in this article is directed by the Norwegian Systematic Health, Environmental and Safety Activities in Enterprises (1997) (Internal Control Regulations [1]), the ISM Code [2] for vessels and their recent applicability to the fishing fleet of Norway. Both safety management works place requirements on the vessel operators and crew to actively manage safety as an on-going concern. The application of these safety management system (SMS) control documents to fishing vessels is just the latest instalment in a continual drive to improve safety in this sector. The difficulty is that there has been no previous systematic approach to safety within the fishing fleet. This article uses the tenants of systems engineering to determine the requirements for such a SMS, detailing the limiting factors and restrictive issues of this complex operating environment.
The objective of this paper is to outline a framework for online risk modelling for autonomous ships. There is a clear trend towards increased autonomy and intelligence in ships because it enables new functionality, as well as safer and more cost-efficient operations. Nevertheless, emerging risks are involved, related to lack of knowledge and operational experience with the autonomous systems, the dependency on complex software-based control systems, as well as a limited ability to verify the safe performance of such systems. The framework presented in the paper is the first step towards supervisory risk control, i.e., developing control systems for autonomous systems with risk management capabilities to improve the decision-making and intelligence of such systems. The framework consists of two main phases, (i) hazard identification and analysis through the systems theoretic process analysis (STPA), and (ii) generating risk models represented by Bayesian Belief Networks (BBN) based on the outcomes of the STPA. The application in the paper is aimed at autonomous ships, but the results of the paper have a general relevance for both manned and unmanned systems with different levels of autonomy, complexity, and major hazard potential.
Norwegian fisheries play an important role nationally and internationally as a provider of healthy and protein-rich food to many people. Further, they not only contribute to the Norwegian economy but also the countries CO2 emissions and there is a need for decarbonization in this industry sector. In this paper the focus is on the Norwegian coastal fishing fleet and the objective is to provide an overview of the barriers preventing decarbonization in this fleet. An example is given on how a diesel-electric propulsion system can be implemented on board a small-scale fishing vessel. The concerns and perspectives of the fishers and other involved stakeholders are presented based on semi-structured interviews, literature search, and statistics. The main findings in the paper are that incomplete knowledge and experience about the safety, reliability, efficiency, and environmental performance of the new propulsion systems are important barriers for reducing CO2 emissions in this sector. Academic research in form of better analysis and evaluation of these factors is needed to overcome these barriers. Therefore, the paper also discusses how methods, such as the System Theoretic Process Analysis (STPA) and Life Cycle Analysis (LCA), can be used to provide additional knowledge and trust in the hybrid system. By pointing out the main barriers and giving indications about future research needed, this paper provides a solid background for further work on the topic of decarbonization in the Norwegian coastal fishing fleet.
The Norwegian University of Science and Technology (NTNU), is currently designing a small autonomous passenger ferry for up to 12 passengers. The ferry will bridge a harbor channel in Trondheim, Norway. This paper presents the results of the preliminary hazard analysis conducted in the early design phase of the ferry. The main hazards and envisioned risk reduction measures are associated with software failure, failure of communication system, both internal and external, traffic in the channel, especially kayaks, passenger handling, and monitoring, and weather conditions. In addition, this paper summarizes practical challenges encountered in the ferry project. These challenges are related to available hazard and risk analysis methods and data, determining and establishing an equivalent safety level, and some of the prescriptive regulations currently in use by the Norwegian Maritime Authority. The presented analysis and identified challenges may assist other, similar projects designing and developing autonomous vessels.
Overcapacity in the fishing fleets is considered as the most serious threat to sustainable fisheries. More effective fishing vessels and catching gear contribute to increased catch capacity. Increased catch capacity causes environmental problems such as overexploitation and calls for larger quotas. The problem of overcapacity indicates the need for a stronger integration of technological aspects into fisheries management. This article assesses the differences in sustainability between the Norwegian ocean and coastal fishing fleets in the cod fisheries, by using systems engineering methods. Attributes of sustainability in the Norwegian cod fishing fleets are investigated, as well as acceptance criteria and performance indicators. The results show that there are huge differences in the performance between the vessel groups, and that the results of an evaluation of sustainability in the fishing fleets are dependent on which attributes are explored. Thus, the discussion may contribute to a better decision basis and improved sustainability in fisheries management.
