4,663 research outputs found

    Development of a semi-empirical ship operational performance model for voyage optimization

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    Previously held under moratorium from 1st December 2016 until 1st December 2021.Voyage optimization is the endeavour to select the optimum route and optimum speed along the voyage in order to maximise the ship performance in energy efficiency and the reduction of the Green House Gas emission footprint within fixed voyage duration. For achieving these goals, it is essential to develop an easy-to-use and accurate enough ship operational performance prediction model, which is the main aim of this study. A detailed critical review of the literature regarding the prediction of ship’s added resistance in waves and its operational performance modelling has been carried out. The existing research gap has been identified and addressed herein. The empirical added resistance prediction formulae have been improved based on the actual ship operational performance data and developed as a semi-empirical added resistance prediction method, which estimates the speed loss due to added resistance. Together with the calm water resistance model, propulsion efficiency model, main engine Specific Fuel Oil Consumption (SFOC) diagram, correction factor indicating fouling effect on fuel consumption, and actual ship operational performance data, the novel semi-empirical ship operational performance prediction model for oil tanker and container ship have been developed and validated. The easy-to-use and practical semi-empirical model is able to accurately predict main engine fuel consumption rate at varying speeds and wave angle encountered. This has been tested successfully on an oil tanker and a container ship. A GRIDS system has been developed to indicate the combination of potential routes and the corresponding weather forecast along each route between departure port and destination. By integrating the GRIDS system with the proposed semi-empirical ship operational performance prediction model, a weather routing model and a speed optimization model have been developed for voyage optimization. In this study, weather routing is achieved by optimum route selection. Its objectives include minimum passage time and minimum fuel consumption under fixed main engine output. Speed optimization is achieved by evaluating the predicted main engine fuel consumption with different speed combinations along the voyage, while a fixed Estimated Time of Arrival(ETA) is set as the constraint. Finally, the main findings are discussed and conclusions are drawn with some recommendations for future research.Voyage optimization is the endeavour to select the optimum route and optimum speed along the voyage in order to maximise the ship performance in energy efficiency and the reduction of the Green House Gas emission footprint within fixed voyage duration. For achieving these goals, it is essential to develop an easy-to-use and accurate enough ship operational performance prediction model, which is the main aim of this study. A detailed critical review of the literature regarding the prediction of ship’s added resistance in waves and its operational performance modelling has been carried out. The existing research gap has been identified and addressed herein. The empirical added resistance prediction formulae have been improved based on the actual ship operational performance data and developed as a semi-empirical added resistance prediction method, which estimates the speed loss due to added resistance. Together with the calm water resistance model, propulsion efficiency model, main engine Specific Fuel Oil Consumption (SFOC) diagram, correction factor indicating fouling effect on fuel consumption, and actual ship operational performance data, the novel semi-empirical ship operational performance prediction model for oil tanker and container ship have been developed and validated. The easy-to-use and practical semi-empirical model is able to accurately predict main engine fuel consumption rate at varying speeds and wave angle encountered. This has been tested successfully on an oil tanker and a container ship. A GRIDS system has been developed to indicate the combination of potential routes and the corresponding weather forecast along each route between departure port and destination. By integrating the GRIDS system with the proposed semi-empirical ship operational performance prediction model, a weather routing model and a speed optimization model have been developed for voyage optimization. In this study, weather routing is achieved by optimum route selection. Its objectives include minimum passage time and minimum fuel consumption under fixed main engine output. Speed optimization is achieved by evaluating the predicted main engine fuel consumption with different speed combinations along the voyage, while a fixed Estimated Time of Arrival(ETA) is set as the constraint. Finally, the main findings are discussed and conclusions are drawn with some recommendations for future research

    A comprehensive ship weather routing system using CMEMS products and A* algorithm

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    We describe the implementation of a comprehensive software for Ship Weather Routing referred to as SIM- ROUTE. The A* pathfinding algorithm is used to optimize the sailing route as a function of the wave action. The aim of the software is to provide a comprehensive, open and easy tool including pre- and post-processing for ship weather routing simulations. The software is constructed considering the Copernicus Marine Environment Monitoring Service (CMEMS) wave predictions systems which are available for free use. The code provides the optimized route and the minimum distance route together with additional modules to compute ship emission and safety on navigation monitoring. SIMROUTE has been tested in several cases using different CMEMS products over short and long distances. The comprehensive structure of the code enables it to be easily modified to include additional ship wave resistance models and the effect of the water currents and winds on navigation. SIMROUTE is also used for academic purposes, providing skills for ship routing optimization in the framework of standards of training, certification and watchkeeping (STCW) for competence-based maritime education and training. Due to the simplicity of its use, SIMROUTE is a good candidate for benchmarking strategies and inter-comparison exercises with advanced methods for ship weather routing. This contribution highlights the technical aspects, code organization and structure behind SIMROUTE, demonstrating its capabilities through examples of route optimization.Postprint (published version

    A semi-empirical ship operational performance prediction model for voyage optimization towards energy efficient shipping

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    Voyage optimization is a practice to select the optimum route for the ship operators to increase energy efficiency and reduce Green House Gas emission in the shipping industry. An accurate prediction of ship operational performance is the prerequisite to achieve these targets. In this paper, a modified Kwon's method was developed to predict the added resistance caused by wave and wind for a specific ship type, and an easy-to-use semi-empirical ship operational performance prediction model is proposed. It can accurately predict the ship's operational performance for a specific commercial ship under different drafts, at varying speeds and in varying encounter angles, and then enables the user to investigate the relation between fuel consumption and the various sea states and directions that the ship may encounter during her voyage. Based on the results from the operational performance prediction model and real time climatological information, different options for the ship's navigation course can be evaluated according to a number of objectives, including: maximising safety and minimising fuel consumption and voyage time. By incorporating this into a decision support tool, the ship's crew are able to make an informed decision about what is the best course to navigate. In this study the Energy Efficiency of Operation (EEO) is defined as an indicator to illustrate the ratio of main engine fuel consumption per unit of transport work. Two case studies are carried out to perform the prediction of ship operational performance for Suezmax and Aframax Oil Tankers, and the results indicate that the semiempirical ship operational performance prediction model provides an extremely quick calculation with very reasonable accuracy, particularly considering the uncertainties related to the parameters of interest for the case study data. Within the case studies, the additional fuel consumption caused by the combined hull and propeller fouling and engine degradation is included in the model as a time-dependent correction factor. The factor may assist the ship owner/operator to determine the hull coating selection, and/or the dry-docking and main engine maintenance strategy

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

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    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

    Voyage optimization combining genetic algorithm and dynamic programming for fuel/emissions reduction

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    Deterministic optimization algorithms generate optimal routes/paths and speeds along ship voyages. However, a ship can rarely follow pre-defined speeds because dynamic sea environments lead to continuous speed variation. In this paper, a voyage optimization method is proposed to optimize ship engine power to reduce fuel and air emissions. It is a combination of dynamic programming and genetic algorithm to solve voyage planning in three-dimensions. In this method, the engine power is discretized into several levels. The potential benefit of using this algorithm is investigated by a medium-size chemical tanker. A ship\u27s actual sailing is used to demonstrate benefits of the proposed method. On average 3.4% of fuel-saving and emission reduction can be achieved than state-of-the-art deterministic methods. If compared with the actual full-scale measurements, on average 5.6% reduction of fuel consumption and GHG emissions (about 275 tons) can be expected by the proposed method for the six case study voyages

    Smart Steaming: A New Flexible Paradigm for Synchromodal Logistics

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    Slow steaming, i.e., the possibility to ship vessels at a significantly slower speed than their nominal one, has been widely studied and implemented to improve the sustainability of long-haul supply chains. However, to create an efficient symbiosis with the paradigm of synchromodality, an evolution of slow steaming called smart steaming is introduced. Smart steaming is about defining a medium speed execution of shipping movements and the real-time adjustment (acceleration and deceleration) of traveling speeds to pursue the entire logistic system’s overall efficiency and sustainability. For instance, congestion in handling facilities (intermodal hubs, ports, and rail stations) is often caused by the common wish to arrive as soon as possible. Therefore, smart steaming would help avoid bottlenecks, allowing better synchronization and decreasing waiting time at ports or handling facilities. This work aims to discuss the strict relationships between smart steaming and synchromodality and show the potential impact of moving from slow steaming to smart steaming in terms of sustainability and efficiency. Moreover, we will propose an analysis considering the pros, cons, opportunities, and risks of managing operations under this new policy

    An application of fuzzy-AHP to ship operational energy efficiency measures

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    Lowering fuel consumption of ships has gained a great deal of attention in maritime industry with regards to both environmental and economic concerns. The potential for fuel economy in shipping ranging between 25% to 75% is possible by using existing technology and practices and technical improvements in the design of new ship. Despite the existence of many technology and design-based approaches, limitations of emerging these measures has led to discussions about the potential energy savings through operational changes. In this study, operational measures were examined within the scope of Ship Energy Efficiency Management Plan (SEEMP) adopted by International Maritime Organization (IMO). We applied the Analytic Hierarchy Process (Fuzzy-AHP) approach, one of multi-criteria decision making (MCDM) techniques, to prioritize the weight of each measure. Fuzzy AHP effectively reflects the vagueness of human thinking with interval values, and shows the relative importance of operational measures - which can be the fundamental decision making data for decision makers (ships' masters, operating companies and ship owners) - by providing a strategic approach to identify energy efficient solutions

    Impact of ship operations aided by voyage optimization on a ship’s fatigue assessment

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    In this study, different operation factors affecting a ship’s wave statistics are studied, such as the slow steaming and voyage optimizations. Especially, the impact of various voyage optimization methods on the long-term wave statistics and corresponding fatigue damage during ship operations is investigated by comparing the encountered waves with the design wave scatter diagram. Three years of full-scale measurements from a container ship sailing in the North Atlantic are employed to study the impact, in addition to noon reports from two fleets of container ships and VLCCs. Furthermore, the benefits of using voyage optimizations for minimum fatigue damage accumulation during operation are discussed. The large difference of wave statistics is found when the ship follows routes generated by various optimization methods and the design diagram. For some westbound voyages, the voyage optimization methods can significantly decrease the ship’s fatigue damage accumulations, leading to longer fatigue life
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