Securing harbor by combining probabilistic approach with event-based approach

International audienceAs a part of SECuring MARitime (SECMAR) project that aimed to improve security at Marseilles harbor, we developed a decision support system that helps port staff to better monitor ship behavior. It consists of two complementary sub-systems. The first system is based on the probabilistic Hidden Markov Model (HMM) approach and deals with nominal (regular and recurrent) behavior of large to medium size of commercial ships. The second system is based on the reactive synchronous language Esterel and concerns aggressive and transgressive behavior of small ships that may navigate freely in the harbor. Real-time evaluations showed that the proposed decision support system efficiently captured and evaluated ship behavior

ALGORITHM DESIGN FOR SHIP’S STEERING WITH SPECIFIED LIMITATIONS UNDER VARIOUS WEATHER CONDITIONS

The problems of developing the risk assessment methods to estimate the level of safety of the vessel under the current conditions on a planned route before staring the pilotage as well as to make the decision on the beginning or suspension of pilotage in order to increase the level of navigational safety are discussed in the paper. Moreover, the application of the research results will reduce the affect of the human factor in decision-making in tasks related to the sea-going vessel’s operation. The developed method for the quantitative assessment of navigational risks will improve the safety of ship’s pilotage. It can also be applied in the decision-making support systems for the navigator in case of collision avoidance actions. The research results presented in this paper can be used to create automatic control systems

Static maritime enviroment representation of electronic navigational charts in global path planning

In past years, numerous global path planning methods have been researched and applied in maritime surface navigation. Regardless of intended usage for either decision-support in manned, or autonomous vessel navigation, path planning should generate a safe and efficient route. However, prior to route generation, static maritime environment representation must be created first. Whether it is transformed in to discrete or continuous form, common approach is to use Electronic Navigational Charts (ENCs) as a basis for maritime environment representation. Nevertheless its origins, ENCs still adhere to inherited data generalisations and simplifications to be comprehensible for human navigators. This leads to limitations when considering path planning and spatial resolution at different chart scales. Furthermore, when generating the representation and path, uncertainty must be considered since the quality and accuracy of chart data varies. Although these topics have been addressed separately in their respective domains, their relations have not been researched in detail. The aim of the proposed paper is the review of electronic navigational charts, environment representation and common global path planning approaches’ relations. Forthcoming standards and technologies, such as usage of high-density charts, are presented and discussed as well.Peer Reviewe

MULTI-VESSELS COLLISION AVOIDANCE STRATEGY FOR AUTONOMOUS SURFACE VEHICLES BASED ON GENETIC ALGORITHM IN CONGESTED PORT ENVIRONMENT

An improved genetic collision avoidance algorithm is proposed in this study to address the problem that Autonomous Surface Vehicles (ASV) need to comply with the collision avoidance rules at sea in congested sea areas. Firstly, a collision risk index model for ASV safe encounters is established taking into account the international rules for collision avoidance. The ASV collision risk index and the distance of safe encounters are taken as boundary values of the correlation membership function of the collision risk index model to calculate the optimal heading of ASV in real-time. Secondly, the genetic coding, fitness function, and basic parameters of the genetic algorithm are designed to construct the collision avoidance decision system. Finally, the simulation of collision avoidance between ASV and several obstacle vessels is performed, including the simulation of three collision avoidance states head-on situation, crossing situation, and overtaking situation. The results show that the proposed intelligent genetic algorithm considering the rules of collision avoidance at sea can effectively avoid multiple other vessels in different situations

Development of voyage optimization algorithms for sustainable shipping and their impact to ship design

The environmental impacts from shipping and the societal challenges of human and property losses caused by ship accidents are pressuring the shipping industry to improve its energy efficiency and enhance ship safety. Voyage optimization is such an effective measure that has been widely adopted in today’s shipping market. The voyage optimization algorithm is the dominant part of any voyage optimization methods. The main objective of this thesis is to develop sophisticated voyage optimization algorithms, explore their applications to sustainable ship operations, and study its impact on ship fatigue design.In this thesis, five commonly used voyage optimization algorithms are first implemented and compared to provide a foundation for understanding optimization algorithms. A three-dimensional Dijkstra’s algorithm is then developed with further improvement based on the comparison. It can provide globally optimal solutions and conducting multi-objective voyage optimization. An engine-power based multi-objective optimization algorithm is proposed for the aid of ship operations with power-setting in their navigation system. Furthermore, the influence of the uncertainties from voyage optimization inputs, e.g., metocean forecast, implemented ship performance models and voyage optimization algorithms, on the optimization results is investigated. Moreover, the capabilities of the proposed voyage optimization algorithms to handle other optimization objectives, i.e., less fatigue damage accumulation and lower fatigue crack propagation rate, is also investigated. Meanwhile, two statistical wave models are compared to study the variation of a ship’s encountered wave environment for ship fatigue design. The impact of voyage optimization aided operations on a ship’s encountered wave environments and fatigue life assessment is also researched in this thesis. The three-dimensional Dijkstra’s algorithm addresses the limitations of conventional voyage optimization algorithms and allows for voluntary speed variation. It has a great potential of saving fuel up to about 12% in comparison with the case study ship’s actual sailing routes. The ship engine setting-based optimization algorithm provides a scheme based on a genetic algorithm and dynamic programming concept. It has the potential to save fuel up to approximately 14.5% compared to the actual sailing routes. This study also shows that metocean uncertainties in the voyage optimization process have great influence on the optimization results, i.e., 3-10% difference in fuel consumption for the same voyage optimization method. In addition, statistical wave models have been proven to capture ship-encountered wave statistics. It is also shown that the actual wave environments encountered by ships differ significantly from the wave scatter diagram provided by class guidelines. A good voyage optimization method can help to extend a ship’s fatigue life by at least 50%.Keywords: Dijkstra’s algorithm; Energy efficiency; Expected time of arrival (ETA); Genetic algorithm; Metocean forecast; Ship safety; Sustainable shipping; Voyage optimization algorithms

Occupational Cultures as a Challenge to Technological Innovation

This paper explains conflict over technological process innovation in cultural terms, drawing primarily on a case study of electric power distribution and strategies to automate its operation

Optimal weather routeing procedures for vessels on trans-oceanic voyages

Merged with duplicate record 10026.1/2726 on 06.20.2017 by CS (TIS)Three sets of algorithms are formulated for use in a variety of models :- * Ship performance algorithms. * Optimisation algorithms. * Environmental data. Optimisation models are constructed for deterministic minima, with time, fuel and cost objective functions. Models are constructed for an actual ship, (M. V. DART ATLANTIC), and realistic working solutions are obtained based on real-time weather information, simulating an actual on-board, computer based system, using dynamic programming. Several combinations of algorithm types are used in the the models, enabling comparisons of effectiveness. Thus, the ship performance algorithms incorporate severally; simple ship speed loss curves, ship resistance, ship motions and ship motion criteria databases devised from a linear seakeeping model. Limitations of the models are discussed from the routeing examples given. State space restrictions and originally devised methods to aid convergence in the models are discussed. Extension of the forecasted environmental data is achieved by a variety of methods and comparisons sought. In particular ECMWF surface pressure files are interrogated to produce sea wave fields over the extended period, establishing main disturbance centres. The variety of algorithms formulated in this work has facilitated real-time comparisons, this is particularly effective in route-updating. The development of these models and the methods used to extend the forecast period, and the comparisons and associated results stemming from these models are viewed as an original contribution to real-time weather routeing of ships.Oceanroutes (UK) Ltd and Oceanroutes Inc, US

Paths forward for sustainable maritime transport : A techno-economic optimization framework for next generation vessels

Climate change is omnipresent in our society. It is known that climate change is occurring, and that additional warming is unavoidable. Therefore, the decarbonization of industrial sectors has gained increased importance in the last years. The maritime transport sector is one of the most targeted industries as it contributes to approximately 3% of global GHG emissions. Nevertheless, maritime transport accounts for up to 80% of the global trade volume, underlying its importance for the world economy. A technical feasible and reliable solution is, thus, essential for the shipping industry to reach the ambitious climate goals established by the Paris Agreement. In the past, the maritim sector has been highly reliant on fossil fuels, using heavy fuel oil as the major energy input. Heavy fuel oil has been the most dominant fuel in the industry due to its cost advantage and high energy density. Recent developments in the maritime industry promote the emergence of dual fuel engines (e.g. LNG and HFO). Even though increased efficiencies and low carbon fuels can reduce maritime pollution, they cannot achieve carbon neutrality. In the long-term, it will be necessary to implement zero emission fuels including green hydrogen, ammonia, methanol, and LNG. The implementation of new sustainable technologies and fuels in the maritime sector will however depend on their economic competitiveness compared to alternative solutions. Therefore, the following research question arises: When can sustainable maritime transport achieve cost parity compared to conventional technologies? The master thesis investigates the break-even point of sustainable shipping technologies in order to achieve climate targets. Thereby, the focus is set on the life cycle costs of different maritime technologies. A techno-economic framework is necessary to decide on the most suitable options for the industry in prospective years. The framework should be able to analyze current as well as prospective technologies, and guide during the technological decision-making process. Therefore, the definition of key performance indicators (KPI) is essential to set a standard for further assessments. The KPIs will be the main value to compare technologies from an economic perspective. In order to answer the research question a case study is developed. The case study is formed by an extensive literature review on current and next-generation sustainable energy systems for vessels. A priority lies on potential carbon neutral technologies and engines such as fuel cells and battery systems based on a predetermined shipping route and shipping class. In a first step, a simulation model for the developed case is established. The output of the simulation model will then be used in the techno-economic framework, connecting components of the system through thermodynamic and physical properties. In a last step, cost functions translate the systems behavior into economic behavior. Once the case study is analyzed, a statistical model is applied on the results in order to evaluate the system under varying boundary conditions. This sensitivity approach is further necessary to underline the impact of the aforementioned KPIs. By that, the robustness of the framework is tested and secured. Finally, the results of the analysis are explained and interpreted with regard to the research question. A conclusion is drawn regarding the potential economic benefits of sustainable maritime transport technologies within the light of potential market access.The results of the thesis are to be documented in a scientifically appropriate manner and discussed within the context of existing literature and regulatory targets for the industry