Ship Route Design for Avoiding Heavy Weather and Sea Conditions

Cai, Yezhao; Wen, Yuanqiao

doi:10.12716/1001.08.04.09

Cited by 11 publications

(12 citation statements)

References 10 publications

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“…Routing can be defined as a prediction of a vessel's next position based on its current position and a number of features, such as speed Tu et al (2018). Other scholars refer to it as route design (Cai et al 2014) or navigation planning (Tan et al 2018). The term can be narrowed down to some specific meaning, for instance weather routing adds an additional layer of complexity by considering conditions such as wind or sea currents.…”

Section: Related Workmentioning

confidence: 99%

Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

et al. 2020

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The presented method reconstructs a network (a graph) from AIS data, which reflects vessel traffic and can be used for route planning. The approach consists of three main steps: maneuvering points detection, waypoints discovery, and edge construction. The maneuvering points detection uses the CUSUM method and reduces the amount of data for further processing. The genetic algorithm with spatial partitioning is used for waypoints discovery. Finally, edges connecting these waypoints form the final maritime traffic network. The approach aims at advancing the practice of maritime voyage planning, which is typically done manually by a ship’s navigation officer. The authors demonstrate the results of the implementation using Apache Spark, a popular distributed and parallel computing framework. The method is evaluated by comparing the results with an on-line voyage planning application. The evaluation shows that the approach has the capacity to generate a graph which resembles the real-world maritime traffic network.

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Section: Related Workmentioning

confidence: 99%

Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

et al. 2020

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“…This believe is based on the fact that weather and sea conditions forecasts were included in many research studies and experiments related to maritime industry. By studying specialized literature, we identified the following scenarios where weather forecasts are mostly used: -determining how ship navigation is affected by extreme weather conditions (Xia et al 2006); -identifying algorithms and models for the prediction of ship speed and power for different weather states (Chen et al 2013;Soda et al 2012); -determining fuel savings algorithms (Hellström 2003); -researching new architectural ship designs, for example flettner rotors design (Traut et al 2014); -determining different ship routes based on weather and sea currents forecasts (Padhy et al 2008;Tsujimoto, Tanizawa 2006;Panigrahi et al 2012;Zhang, Huang 2007;Cai et al 2014); -analysing characteristics of propulsion performance under various weather and sea conditions (Sasaki et al 2010;Yokoi et al 2010;Tsujimoto, Tanizawa 2006;Kayano et al 2013). Hellström (2003) emphasized that fuel costs are the second largest item (after salaries) on a big vessel's budget.…”

Section: External Weather Providersmentioning

confidence: 99%

“…According to Cai et al (2014), we should consider as important environmental factors for ship routing those elements such as the atmosphere and ocean which may produce a change in the status of a ship transit. Therefore, for ship routing, we can consider as important factors: waves, wind, ice, fogs and ocean currents (both speed and direction).…”

Section: External Weather Providersmentioning

confidence: 99%

“…If wind speed is high, the speed will be reduced in both cases due to the increased wave actions and steering corrections. Cai et al (2014) show that the major factor that will affect ship performance is the wave height. This situation is a consequence of the fact that the waves will reduce propeller thrust and increase drag from steering.…”

Section: External Weather Providersmentioning

confidence: 99%

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Operational Shipping Intelligence Through Distributed Cloud Computing

Cristea

Moga

Neculiță

et al. 2017

Journal of Business Economics and Management

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This paper provides a conceptual architecture for a cloud based platform design, that implements continuously data storage and analysis services for large maritime ships, with the purpose to provide valuable insights for maritime transportation business. We do this by first identifying the need on the shipping market for such kind of systems and also the significance and impact of different factors related to shipping business processes. The architecture presented throughout this paper will be defined around some of the most currently used ICT technologies, like Amazon Cloud Services, Sql Server Databases, .NET Platform, Matlab 2016 or javascript visualization libraries. The proposed system makes possible for a maritime company to gain more knowledge for optimizing the efficiency of its operations, to increase its financial benefits and its competitive advantage. The platform architecture was designed to make possible the storage and manipulation of very large datasets, also allowing the possibility of using different data mining techniques for inferring knowledge or to validate already existent models. Ultimately, the developed methodology and the presented outcomes demonstrate a vast potential of creating better technological management systems for the shipping industry, starting from the challenges but also from the huge opportunities this sector can offer.

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“…The water transportation activity at this port is highly depends on the wave condition. Wave height is one of the major factors which affects the ship performance and safety [1]. Wave condition is strongly influenced by wind variability which is the main generating force (dominant) of sea wave [2,3].…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling of wave-current interaction in Merak Port, Indonesia

Nurfitri

Ningsih

Sentanu

et al. 2018

IOP Conf. Ser.: Earth Environ. Sci.

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Abstract. This study aimed to investigate the effects of currents to wave height in the waters of Merak Port, Banten using wave spectrum model. The wave-current interaction simulation was performed by utilizing SWAN (Simulating Waves Nearshore) in stationary mode and using the unstructured triangular grid. Data of wind velocity and direction as model inputs were obtained from BMKG (Indonesian Agency for Meteorology, Climatology, and Geophysics), whereas tidal current velocity data was obtained from TMD (Tide Model Driver). The model was simulated in two different scenarios, i.e. without and with following (adverse) current which is same (opposite) with wave propagation. The model input of dominant west wind was used to represent the west monsoon, while the dominant wind from the north was used to represent the east monsoon. The simulation results show that the maximum wave height is 2.98 m in the west monsoon and 1.9 m in east monsoon. In the west (east) monsoon the following current decrease wave height to 9.26% (5.09%), while the adverse current increase wave height up to 9.07% (6.56%).

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Ship Route Design for Avoiding Heavy Weather and Sea Conditions

Abstract: This paper covers the current state

Cited by 11 publications

References 10 publications

Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

Operational Shipping Intelligence Through Distributed Cloud Computing

Numerical modeling of wave-current interaction in Merak Port, Indonesia

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