FULL-SCALE MOTIONS OF A LARGE HIGH-SPEED CATAMARAN: THE INFLUENCE OF WAVE ENVIRONMENT, SPEED AND RIDE CONTROL SYSTEM

To assess the behaviour of large high-speed catamarans in severe seas, extensive full-scale trials were conducted by the U.S. Navy on an INCAT Tasmania built vessel in the North Sea and North Atlantic region. Systematic testing was done for different speeds, sea states and ride control settings at different headings. Collected data has been used to characterise the ship’s motions and seakeeping performance with respect to wave environment, vessel speed and ride control system. Motion response amplitude operators were derived and compared with results from a two-dimensional Green function time-domain strip theory seakeeping prediction method. An increase of motion response with increasing vessel speed and a decrease with the vessel moving from head to beam seas was found. In higher sea states and headings ahead of beam seas an increasing influence of the centre bow on pitch motion damping was found. Significant motion RAO reduction was also found when the ride control system was active. Its effectiveness increased at higher speeds and contributed to heave and pitch motion RAO reduction. Predicted motion magnitudes with the time domain seakeeping code were consistent with the measured motion responses, but maximum heave was predicted at a rather higher frequency than was evident in the trials.

The Simulation of Sloped Bank Effect Influence on Container Ship Trajectory

The latest container vessel grounding in the Suez Canal, which occurred on 23 March 2021 (the Ever Given), raised many questions regarding the safety of navigation. The sudden concern about safety is due to fears that traffic flow through the Suez Canal could be blocked for longer periods of time. Besides external forces imposed by wind, in this case bank effect had a significant influence on the ship’s grounding. Bank effect occurs due to restricted water flow caused by narrow waterways. Many fairway design standards consider sloped banks such as those of the Suez Canal as unsubstantial in bank-effect forces. This paper analyses the impact of sloped banks on container ship trajectory and proposes minimal distances that may decrease bank-effect forces in order to reduce the risk of vessel grounding and increase the safety of navigation. However, this type of accident has happened before and may occur again due to a small sailing distance from the bank in cases where vessel speed is increased.

Underwater noise mitigation in the Santa Barbara Channel through incentive-based vessel speed reduction

Commercial shipping is the dominant source of low-frequency noise in the ocean. It has been shown that the noise radiated by an individual vessel depends upon the vessel’s speed. This study quantified the reduction in source levels (SLs) and sound exposure levels (SELs) for ships participating in two variations of a vessel speed reduction (VSR) program. SLs and SELs of individual ships participating in the program between 2014 and 2017 were statistically lower than non-participating ships (p < 0.001). In the 2018 fleet-based program, there were statistical differences between the SLs and SELs of fleets that participated with varying degrees of cooperation. Significant reductions in SL and SEL relied on cooperation of 25% or more in slowing vessel speed. This analysis highlights how slowing vessel speed to 10 knots or less is an effective method in reducing underwater noise emitted from commercial ships.

Multi-Camera Vessel-Speed Enforcement by Enhancing Detection and Re-Identification Techniques

This paper presents a camera-based vessel-speed enforcement system based on two cameras. The proposed system detects and tracks vessels per camera view and employs a re-identification (re-ID) function for linking vessels between the two cameras based on multiple bounding-box images per vessel. Newly detected vessels in one camera (query) are compared to the gallery set of all vessels detected by the other camera. To train and evaluate the proposed detection and re-ID system, a new Vessel-reID dataset is introduced. This extensive dataset has captured a total of 2474 different vessels covered in multiple images, resulting in a total of 136,888 vessel bounding-box images. Multiple CNN detector architectures are evaluated in-depth. The SSD512 detector performs best with respect to its speed (85.0% Recall@95Precision at 20.1 frames per second). For the re-ID of vessels, a large portion of the total trajectory can be covered by the successful detections of the SSD model. The re-ID experiments start with a baseline single-image evaluation obtaining a score of 55.9% Rank-1 (49.7% mAP) for the existing TriNet network, while the available MGN model obtains 68.9% Rank-1 (62.6% mAP). The performance significantly increases with 5.6% Rank-1 (5.7% mAP) for MGN by applying matching with multiple images from a single vessel. When emphasizing more fine details by selecting only the largest bounding-box images, another 2.0% Rank-1 (1.4% mAP) is added. Application-specific optimizations such as travel-time selection and applying a cross-camera matching constraint further enhance the results, leading to a final 88.9% Rank-1 and 83.5% mAP performance.

Efficient Harbor Craft Monitoring System: Time-Series Data Analytics and Machine Learning Tools to Achieve Fuel Efficiency by Operational Scoring System

This paper presents the analysis to reduce carbon emission from tugboat operations by utilizing a proposed unsupervised machine learning operational scoring system. The time-series analysis is performed by transforming data into a common domain for clustering. The data are collected from a tugboat to investigate the correlation between environmental and location data with fuel consumption to achieve fuel efficiency. The relevant parameters that influence the fuel consumption of the tugboat, such as fuel consumption, vessel route, vessel speed and wind metrics are collected from sensors installed onboard the ship and data provider to monitor and to gauge the vessel’s performance. The raw readings are conditioned (data cleaning and data pre-processing) before transformation to Score Dataset: the Raw mass-flowrate readings are cleaned by using the Haar wavelet; the wind raw reading is converted to wind effect data; the Location data is converted to vessel speed data. Together, they form a Score Dataset by applying the time series K-means clustering. The subsequent unsupervised learning identifies the activity labels that describe qualitatively the operations of the vessels and are obtained by using the non-time series K-mean clustering. By using the Hidden Markov Model approach, this paper attempts to explain the stochastic correlation among parameters explained earlier. The correlation is the information of newly discovered knowledge in terms of likelihood matrices, also known as the knowledge base (KB). The KB may be consumed to perform predictions. Hence, it is possible to suggest the optimal ship operation, i.e., speed that produces the optimum fuel consumption. The Score Dataset and clustering that are produced in this paper could also be used in the Artificial Neural Network for future work.

Effects of a Vessel Speed Reduction Program on Air Quality in Port Areas: Focusing on the Big Three Ports in South Korea

As the seriousness of air pollution from ports and ships is recognized, the Korean Port Authority is implementing many policies and instruments to reduce air pollution in port areas. This study aims to verify the effects of the vessel speed reduction (VSR) program among the procedures related to air pollution in port areas. This study was conducted using panel data created by combining ship entry and departure data and air quality measurement data. We measured the changes in air quality according to the entry and departure of ships and examined whether it changes due to the VSR program. For estimation, the panel fixed-effect model and the ordinary least squares (OLS) model were used. The results suggest that the VSR program had a positive effect on improving air quality in port areas. However, the VSR program’s effects were different over ports. Busan Port showed the highest policy effect, and Incheon Port showed a relatively low policy effect. Based on the results of this study, to maximize the VSR program’s effectiveness at the port, it is necessary to implement other eco-friendly policies as well.

Reanalysis of the Sydney Harbor RiverCat Ferry

In this paper, we revisit the hydrodynamics supporting the design and development of the RiverCat class of catamaran ferries operating in Sydney Harbor since 1991. More advanced software is used here. This software accounts for the hydrodynamics of the transom demisterns that experience partial or full ventilation, depending on the vessel speed. This ventilation gives rise to the hydrostatic drag, which adds to the total drag of the vessel. The presence of the transom also creates a hollow in the water. This hollow causes an effective hydrodynamic lengthening of the vessel, which leads to a reduction in the wave resistance. Hence, a detailed analysis is required in order to optimize the size of the transom. It is demonstrated that the drag of the vessel and the wave generation can be predicted with good accuracy. Finally, the software is also used to optimize the vessel further by means of affine transformations of the hull geometry.