Safety distance modeling for ship escort operations in Arctic ice-covered waters

Zhang, Mingyang; Zhang, Di; Fu, Shanshan; Yan, Xinping; Goncharov, Vadim K.

doi:10.1016/j.oceaneng.2017.09.053

Cited by 67 publications

(14 citation statements)

References 21 publications

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“…In recent years, some researchers realized that the two research branches should not be isolated. On the contrary, both the actual operating conditions of the ship locks and the associated service quality should be considered together from a systematic perspective, taking into account the interests of different stakeholders such as shipping companies and transport management authorities [21][22][23].…”

Section: Safety and Carrying Capacity Of Ship Locksmentioning

confidence: 99%

A Fuzzy-Based Decision-Making Model for Improving the Carrying Capacity of Ship Locks: A Three Gorges Dam Case

Shi

Zhang

et al. 2019

JMSE

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This paper develops a decision-making model to assist the improvement of the carrying capacity of ship locks by combing fuzzy logic, the analytic hierarchy process (AHP) method, and the technique for order preference by similarity to an ideal solution (TOPSIS). A three-level hierarchical structure is constructed to identify the key factors influencing the carrying capacity of ship locks from the aspects of ship locks, vessels, environment, and administration. On this basis, a series of targeted strategies have been put forward to improve the carrying capacity of ship locks, and the TOPSIS method is applied to rank these strategies in terms of their performance. A case study of the five-stage dual-track ship lock of the Three Gorges Dam in China has been conducted to demonstrate the feasibility and rationality of the proposed model, and correlation analysis is conducted to verify the identified influencing factors in order to eliminate potential bias which may be generated from using AHP. The results obtained from the proposed methods are consistent with the real-life situation to a certain extent, indicating that the proposed method can provide a useful reference for improving the carrying capacity of ship locks.

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Section: Safety and Carrying Capacity Of Ship Locksmentioning

confidence: 99%

A Fuzzy-Based Decision-Making Model for Improving the Carrying Capacity of Ship Locks: A Three Gorges Dam Case

Shi

Zhang

et al. 2019

JMSE

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“…The latter however may exceed the safe speed for a ship in ice. 22,[40][41][42] On the other hand, the data-driven models provide information on ice performance for the range of ice and navigation conditions covered by the data, but fail to predict beyond that. Also, numerous variables affecting the performance remain hidden, [43][44][45] and only summarizing relationships between performance and ice conditions expressed in simplified manner can be established.…”

Section: The Idea Of Hybrid Modelingmentioning

confidence: 99%

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Montewka

Goerlandt

Lensu

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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Practical knowledge about the performance of a ship while navigating in ice is crucial for the selection of safe and efficient route for a ship. Existing route finding tools estimate ship performance in ice adopting numerous approaches, ranging from model tests and engineering models to experts-based guidelines. Therein ship performance is usually understood as attainable ship speed or the average speed in given ice conditions; rarely the probability of besetting in ice is taken into account. Those models despite being fairly accurate in the theory share the same shortcoming in practice. The latter encompasses three main issues: (1) inaccurate information about prevailing ice conditions, (2) presence of ice conditions that goes beyond the scope of the models, and (3) the effect of operational patterns and traffic organization on the performance of an individual ship. To approach those issues, we propose a hybrid model of ship performance in ice-covered waters. The hybrid model combines two other sub-models: engineering and data-driven. The former determines ship speed and besetting probability in ridged ice field with ice concentration close to 100%. The latter sub-model provides information on ship's speed in the actual ice conditions, where the speed is affected also by operational restrictions and icebreaker assistance. It is based on an extensive dataset combining ship data from automatic identification system and ice data from ice charts and ice forecast models. The presented hybrid model is valid for a specific ship type, which is ice going bulk carrier (IA Super ice class), operating within the Northern Baltic Sea winter navigation system. The obtained results reveal that the hybrid model in principle is capable of providing reliable information about the performance of a ship in a wide range of conditions accounting for environmental variability and existing operational conditions. The model is suitable for the purpose of safe route planning in ice for a single ship or group of similar ships, accounting for the economy and safety of a voyage.

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“…Preventing ship collision helps reduce environmental pollution, casualties, and economic losses. Extensive research has been conducted to achieve a safe maritime transport system [7][8][9][10]. One widely used way to achieve this goal is to analyze non-accident information, such as near miss, and then use these findings to develop preventive measures to enhance navigational safety [11,12].…”

Section: Introductionmentioning

confidence: 99%

Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

Banda

Goerlandt

et al. 2021

JMSE

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Ship collision is the most common type of accident in the Northern Baltic Sea, posing a risk to the safety of maritime transportation. Near miss detection from automatic identification system (AIS) data provides insight into maritime transportation safety. Collision risk always triggers a ship to maneuver for safe passing. Some frenetic rudder actions occur at the last moment before ship collision. However, the relationship between ship behavior and collision risk is not fully clarified. Therefore, this work proposes a novel method to improve near miss detection by analyzing ship behavior characteristic during the encounter process. The impact from the ship attributes (including ship size, type, and maneuverability), perceived risk of a navigator, traffic complexity, and traffic rule are considered to obtain insights into the ship behavior. The risk severity of the detected near miss is further quantified into four levels. This proposed method is then applied to traffic data from the Northern Baltic Sea. The promising results of near miss detection and the model validity test suggest that this work contributes to the development of preventive measures in maritime management to enhance to navigational safety, such as setting a precautionary area in the hotspot areas. Several advantages and limitations of the presented method for near miss detection are discussed.

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Safety distance modeling for ship escort operations in Arctic ice-covered waters

Cited by 67 publications

References 21 publications

A Fuzzy-Based Decision-Making Model for Improving the Carrying Capacity of Ship Locks: A Three Gorges Dam Case

A Fuzzy-Based Decision-Making Model for Improving the Carrying Capacity of Ship Locks: A Three Gorges Dam Case

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

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