Ships In Waters Research Articles

Two Outbreaks of Legionnaires Disease Associated with Outdoor Hot Tubs for Private Use - Two Cruise Ships, November 2022-July 2024.

Legionnaires disease is a serious pneumonia caused by Legionella bacteria. During November 2022-June 2024, CDC was notified of 12 cases of Legionnaires disease among travelers on two cruise ships; eight on cruise ship A and four on cruise ship B. CDC, in collaboration with the cruise lines, initiated investigations to ascertain the potential sources of on-board exposure after notification of the second potentially associated case for each ship. Epidemiologic data collected from patient interviews and environmental assessment and sampling results identified private hot tubs on selected cabin balconies as the most likely exposure source. To minimize Legionella growth, both cruise lines modified the operation and maintenance of these devices by removing the heating elements, draining water between uses, and increasing the frequency of hyperchlorination and cleaning. Hot tubs offer favorable conditions for Legionella growth and transmission when maintained and operated inadequately, regardless of location. Private hot tubs on cruise ships are not subject to the same maintenance requirements as are public hot tubs in common areas. Given the range of hot tub-type devices offered as amenities across the cruise industry, to reduce risk for Legionella growth and transmission, it is important for cruise ship water management program staff members to inventory and assess private balcony hot tubs and adapt public hot tub maintenance and operations protocols for use on private outdoor hot tubs.

A semi-analytical approach for dynamic responses of monopile-supported offshore wind turbines subjected to accidental loads

Offshore wind energy is leading the way in sustainable energy generation. Offshore wind turbines (OWTs) need to be designed to withstand extreme or accidental loads in Ultimate Limit States (ULS) and Accidental Limit States (ALS), whereby high order eigenmodes may become significant. This paper introduces a semi-analytical approach for efficient and reliable analysis of the dynamic responses of monopile-supported OWTs subjected to accidental loads. A Rayleigh-Ritz solution is initially adopted to determine the high-order natural frequencies and eigenmodes of monopile OWTs, explicitly considering tapered towers and soil-pile interactions. Dynamic responses of OWTs are then calculated depending on the interaction schemes between accidental loads and the structures, e.g. soft contact loads (e.g. slamming, wind) and hard contact loads (e.g. ship collisions, ice impact). For soft contact loading conditions, the loads are considered independent of turbine responses, and the transient dynamic response is computed using the classical modal superposition method. While for hard contact loading conditions, the load actions depend on the contact stiffnesses and responses of the interacting bodies. A numerical contact algorithm is thus developed, and numerical iterations are performed to ensure convergence. The proposed approach is applied to the DTU 10 MW monopile-supported OWT subjected to extreme water slamming and ship collisions, respectively as example applications of soft and hard contact scenarios. The results are verified against nonlinear finite element analysis using USFOS and discussed with respect to the turbine natural frequencies and eigenmodes, contact forces and dynamic responses. A parametric analysis is conducted for ship-OWT collisions, exploring different impact scenarios by varying ship sizes, contact stiffnesses, and initial impact velocities. The proposed approach can serve as a promising tool for accidental load response analysis and the design of monopile OWTs.

Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks

A set of planar motion mechanism experiments of the Duisburg Test Case Post-Panamax container model executed in a towing tank with shallow depth is applied to train a neural network to analyse the ability of the proposed model to learn the effects of different depth conditions on ship’s manoeuvring capabilities. The motivation of the work presented in this paper is to contribute an alternative and effective approach to model non-linear systems through artificial neural networks that address the manoeuvring simulation of ships in shallow water. The system is developed using the Levenberg–Marquardt backpropagation training algorithm and the resilient backpropagation scheme to demonstrate the correlation between the vessel forces and the respective trajectories and velocities. Sensitivity analyses were performed to identify the number of layers necessary for the proposed model to predict the vessel manoeuvring characteristics in two different depths. The outcomes achieved with the proposed system have shown excellent accuracy and ability in predicting ship manoeuvring with varying depths of shallow water.

Numerical Investigation of Oblique Currents’ Effects on the Hydrodynamic Characteristics of Ships in Restricted Waters

The influence of oblique currents in narrow and shallow channels causes the fluid flow around ships to become complex. To analyze the hydrodynamic characteristics of a ship in such channels, it is essential to examine the influence of oblique currents on the ship’s hydrodynamic characteristics. In this study, current direction, ship speed, current speed, and water depth were identified as determinants affecting the hydrodynamic characteristics of a ship. Numerical simulations were conducted on a large oil tanker to investigate the effects of these factors on the ship’s hydrodynamic characteristics. The viscous fluid flow was modeled using the unsteady Reynolds-averaged Navier–Stokes (URANS) equations in conjunction with the k-ε turbulence model. The URANS equations were discretized using the finite volume method. The numerical results indicate substantial differences in the hydrodynamic characteristics of ships under oblique current conditions compared to still-water conditions. At a current direction of β = −45°, the direction of the sway force is consistent with that of still water’s sway force, which is an attractive force. The yaw moment at β = −45° changes from a bow-out moment under still-water conditions to a bow-in moment. Conversely, at a current direction of β = 45°, the sway force shifts from an attractive force under still-water conditions to a repulsive force. The yaw moment acts as a bow-out moment, which is consistent with that observed in still-water conditions. Furthermore, the influence of hydrodynamic characteristics on a ship varies significantly with changes in ship speed, current speed, and water depth. To ensure the safe navigation of ships, it is essential to develop and apply comprehensive strategies and countermeasures that account for practical conditions.

Advanced Human Reliability Analysis Approach for Ship Convoy Operations via a Model of IDAC and DBN: A Case from Ice-Covered Waters

The melting of Arctic ice has facilitated the successful navigation of merchant ships through the Arctic route, often requiring icebreakers for assistance. To reduce the risk of accidents between merchant vessels and icebreakers stemming from human errors during operations, this paper introduces an enhanced human reliability assessment approach. This method utilizes the Dynamic Bayesian Network (DBN) model, integrated with the information, decision, and action in crew context (IDAC) framework. First, a qualitative analysis of crew maneuvering behavior in scenarios involving a collision with the preceding vessel during icebreaker assistance is conducted using the IDAC model. Second, the D–S evidence theory and cloud models are integrated to process multi-source subjective data. Finally, the human error probability of crew members is quantified using the DBN. The research results indicate that during convoy operations, the maximum probability that the officer on watch (OOW) chooses an incorrect deceleration strategy is 8.259×10−2 and the collision probability is 4.129×10−3. Furthermore, this study also found that the factors of Team Effectiveness and Knowledge/Abilities during convoy operations have the greatest impact on collision occurrence. This research provides important guidance and recommendations for the safe navigation of merchant ships in the Arctic waters. By reducing human errors and adopting appropriate preventive measures, the risk of collisions between merchant ships and icebreakers can be significantly decreased.

Numerical simulations of the ONRT ship maneuvering in calm water and head waves with the partially rotating grid method

This research delves into the maneuverability aspects of a model-scale ONRT surface combatant ship using Computational Fluid Dynamics (CFD) simulations. A key aspect of this study is the comparison of the actuator disc (AD) model and the partially rotating grid (P) method in calm water, complemented by an in-depth analysis of the P method for simulations in waves. Utilizing these methods, the study investigates the performance of the ship in propeller open water, self-propulsion, and complex maneuvers like turning circle and zig-zag. Key findings highlight the superiority of the P method in closely aligning with experimental data, particularly in capturing complex dynamics of ship maneuvers. This research underscores the critical role of propeller side force in maneuvering simulations, a factor often neglected in simpler models like the AD. Maneuvers in head waves are also examined, revealing the nuanced effects of wave orientation on the stability and maneuverability of the ship. This study highlights the effectiveness of CFD in simulating ship maneuvers and the need for ongoing refinement of these techniques to improve accuracy and reliability.

Real-time simulation of ship overtake maneuvering at different water depths with a ship motion controller

This study aimed to predict ship trajectories in deep and shallow waters in real-time by properly accounting for the effects of hydrodynamic interactions on ship maneuvering. Ship maneuverability and motion control were investigated under hydrodynamic interactions arising from the effects of water depth, ship speed, and lateral distance between interacting ships on parallel courses. The Maneuvering Modeling Group (MMG) model was used, and the hydrodynamic interaction effect was estimated using an efficient three-dimensional potential-flow code that can run in real time. The influence of water depth on ship maneuverability was analyzed. The ship velocity response to the hydrodynamic interactions and maneuvering motion was simulated during the overtaking process of two ships at a range of water depths, lateral distances, and speeds. The findings suggest that, in shallow waters, changing the heading of the ship becomes more difficult, and the course deviation associated with the overtaking maneuver of two ships also increases. A conventional proportional-integral-derivative (PID) controller was employed for course-keeping. When the ratio of the water depth to ship draft was less than 2.0, the PID controller continued to perform effectively for the overtaking ship. For the overtaken ship, the effectiveness of the controller was diminished owing to the relatively low rudder effect at slow speeds.

A data-driven Ship Risk Profile model for Turkish Straits (TS-SRP) using Machine Learning

Marine accidents exhibit a higher frequency within ports, internal waters, and narrow waterways as compared to open seas, emphasizing the paramount concern of maritime authorities regarding the safe navigation of ships in congested waters. In response to this issue, coastal states, in addition to flag state and port state measures, institute preventive measures by conducting risk analyses in narrow waterways with geographical restrictions and high traffic density. To meet this need, this study aims to develop a Ship Risk Profile (SRP) model to monitor ships by evaluating the potential risks of the ships passing through narrow waterways and taking the necessary precautions proactively by Vessel Traffic Service (VTS) for mitigating the potential accident and environmental pollution risk. The Turkish Straits is determined as the application area for this paper. The proposed model employs Machine Learning (ML) methods and analyzes targeting factors from Port State Control (PSC), ship particulars obtained from Sailing Plan (SP)-1 reports specific to the Turkish Straits, as well as relevant environmental factors. The results demonstrate that the developed model holds promise for improving safety in Turkish Straits and can be adapted by VTSs in other sea regions by customizing it to suit their specific characteristics and conditions.

Early warning system on harmful aquatic organisms at a regional sea scale: Components and mechanisms

The introduction of harmful aquatic organisms and pathogens (HAOP) via the ballast water of ships can endanger human health, the environment, economic resource-related systems, as well as impair biological diversity. Early warning systems (EWS) are highly effective instruments for mitigating risks and enhancing readiness in the face of potential disasters, including those resulting from HAOP. The establishment of a regional EWS for the identification and notification of harmful organisms is a complex marine policy process involving communication with stakeholders, technical development, engagement of regional knowledge, and, ultimately, harmonization between key authorities and Participating States. The purpose of EWS is to promptly communicate the findings of HAOP to the appropriate stakeholders, such as government agencies and commercial companies. The paper elucidates in detail the criteria and procedure for developing a regionally standardized EWS, including its mechanism, the technical information platform that is required, and the obligations of EWS data providers. It also discusses the decision-making process for issuing alerts and identifies the intended recipients of the warning signals. The system has been operational in the Baltic Sea region for over two years, and the knowledge and insights gathered during its development may prove beneficial in other areas as well.

Ballast water transport of alien phytoplankton species to the brazilian amazon coast

The aim of this study was to investigate the presence of alien phytoplankton species transported through ballast water of ships that docked on the Amazon coast. Phytoplankton samples were collected from 25 ships between 2012 and 2014, revealing 215 identified species, mostly comprising oceanic planktonic marine species. However, several coastal and freshwater species not yet documented on the Maranhão coast were also observed. The identification of several coastal and freshwater species not yet recorded for Amazonian environments in the ballast water of the Ponta da Madeira Maritime Terminal (TMPM), as well as toxic microalgae genera such as the dinoflagellates Alexandrium and Gymnodinium and of some diatom species from the genus Pseudo-nitzchia, raises concerns regarding the possibility of introducing species. This indicates that ballast water can be responsible for the introduction of alien species in Amazonian aquatic environments, thereby highlighting the TMPM as a critical hotspot in the Amazonian region.

Numerically Investigating the Effect of Trim on the Resistance of a Container Ship in Confined and Shallow Water

One of the promising strategies for the improvement of the resistance characteristics and energy efficiency of a ship is trim optimization. Most of the studies conducted so far regarding trim optimization deal with unrestricted water. The effect of trim on the total resistance and its components for the KRISO Container Ship model in confined and shallow water is investigated using computational fluid dynamics. Numerical simulations of resistance tests with and without the free surface effects using two turbulence models are carried out for even keel and four trims in restricted water. A verification study is conducted for the total resistance, sinkage, and trim in terms of grid resolutions and time steps to assess the numerical uncertainty. The numerical results are validated against the experimental ones available in the literature. Performing the double body simulations enabled the analysis of the effect of trim on the resistance components. The numerical results pointed out that by adjusting the trim a reduction in the total resistance in confined and shallow water can be obtained.

A baseline assessment of contamination in the Sacramento deep water ship channel

The Sacramento Deep Water Ship Channel (SDWSC) in the San Francisco Estuary, which is an active commercial port, is critical habitat for pelagic fish species including delta smelt (Hypomesus transpacificus), longfin smelt (Spirinchus thaleichthys), and Sacramento perch (Archoplites interruptus). Pelagic organism decline has been attributed to covarying factors such as manipulation of habitat, introduction of invasive species, decrease in food production, and contaminant exposure. Quantification of bioavailable toxicant loads in the SDWSC is limited despite previous surveys that have detected elevated contaminant concentrations in the sediments. Therefore, the focus of the present study was to characterize the bioavailability of the contaminants in the SDWSC from six sites along the channel. At each site, organochlorine pesticides (OCPs), pyrethroid insecticides, polyaromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) were quantified in sediment, zooplankton, and suspended solids. In addition, Tenax extraction was used to measure the bioaccessible fraction of sediment-associated contaminants freely dissolved in the water. Bioaccessible contaminants in the sediment provided an uptake route for these stressors into invertebrates and fish with bioaccessible OCPs being found at all sites, particularly 4,4′-dichlorodiphenyldichloroethylene (DDE). Bifenthrin was the only pyrethroid detected in the chosen matrices and it was found at concentrations below levels of concern. Bioaccessible PAHs were found at all sites, with highest detections for phenanthrene and pyrene. No PCBs were detected in sediments, but were detected in both suspended solids and zooplankton. Contaminant concentrations overall were significantly higher in suspended solids, followed by zooplankton and sediments. The highest sediment concentrations of DDE, fluoranthene, pyrene, and dibenzo[a,h]anthracene exceeded sediment quality benchmarks indicating potential risk to sediment-dwelling species. Finally, elevated contaminant levels were found in both suspended solids and zooplankton, suggesting additional risk to pelagic species in the SDWSC.

Numerical Simulations of a Ship’s Maneuverability in Shallow Water

It is necessary to maintain maneuverability for ship navigation in shallow water, such as channels, ports and other confined waters. In this study, a turning circle maneuver with 35° rudder deflection and a 20/5 zigzag maneuver for KVLCC2 in shallow waters are tested numerically to directly predict the maneuverability of the ship in shallow water. A viscous in-house CFD solver is applied with the dynamic overset grid approach. The impacts of the water depth on the ship’s maneuverability in terms of turning and zigzag competence are evaluated, and the underlying mechanism is analyzed. The numerical method is validated by comparing it with experimental data on the turning indices, which shows good agreement. It is demonstrated that the turning capability become worse with a smaller depth–draft ratio, thus resulting in a lower yaw rate and a greater steady turning diameter. However, the drift angle and lateral speed are reduced with a smaller depth–draft ratio for zigzag maneuvers, but the overshoot angle and turn lag vary with the water depth non-monotonically.

Autonomous navigation decision-making for ships in complex estuarine waters: Methodology and validation

This study focused on key scientific issues in the autonomous navigation for ships, including constraints on environmental and navigation rules, limitations on ship maneuverability, and collision avoidance mechanisms, to address the challenges of autonomous navigation decision-making for ships in complex estuarine waters and validate the feasibility and accuracy of the proposed methodology. A novel autonomous navigation decision-making method that can dynamically adapt to residual errors in a system and the random movements of target ships was proposed. The predictive model used to calculate decision plans and the simulation model used to execute and validate decision plans were separated. Environmental constituent elements were classified and modeled to digitize the environment. A navigation scenario was constructed based on the fusion of virtual and real information. The control and process prediction methods were proposed based on the nonlinear ship maneuvering characteristics. Navigation rules were summarized, analyzed, and integrated into the decision-making and execution process. The collision avoidance mechanism and calculation method for feasible course and speed range were studied. Simulation experiments were conducted using the North Channel of the Yangtze River Estuary as an example. The results demonstrated that the proposed method can accurately make autonomous navigation decisions, safely avoid collisions, and timely track routes in nearly realistic scenarios.

Research of Methods of Collision Warning and Avoidance Assistant Decision Making for the Ship in Typical Inland TSS Waters

Research of Methods of Collision Warning and Avoidance Assistant Decision Making for the Ship in Typical Inland TSS Waters

Research on A Ship Trajectory Classification Method Based on Deep Learning

The unrestricted development and utilization of marine resources have resulted in a series of practical problems, such as the destruction of marine ecology. The wide application of radar, satellites and other detection equipment has gradually led to a large variety of large-capacity marine spatiotemporal trajectory data from a vast number of sources. In the field of marine domain awareness, there is an urgent need to use relevant information technology means to control and monitor ships and accurately classify and identify ship behavior patterns through multisource data fusion analysis. In addition, the increase in the type and quantity of trajectory data has produced a corresponding increase in the complexity and difficulty of data processing that cannot be adequately addressed by traditional data mining algorithms. Therefore, this paper provides a deep learning-based algorithm for the recognition of four main motion types of the ship from automatic identification system (AIS) data: anchoring, mooring, sailing and fishing. A new method for classifying patterns is presented that combines the computer vision and time series domains. Experiments are carried out on a dataset constructed from the open AIS data of ships in the coastal waters of the United States, which show that the method proposed in this paper achieves more than 95\% recognition accuracy. The experimental results confirm that the method proposed in this paper is effective in classifying ship trajectories using AIS data and that it can provide efficient technical support for marine supervision departments.

Optimal path planning for a ship in coastal waters with deep Q network

With the development of autonomous ships, complete automation of passage planning has become an imminent priority. However, existing A* algorithms have the disadvantage of generating paths close to land because they prioritize minimizing the navigation distance. Therefore, this study proposes a method based on a deep Q network to effectively implement reward-and-penalty strategies considering required navigation areas and non-navigable areas throughout the port-to-port distance. First, the Busan and Gwangyang Ports were selected as the target areas and a container ship was selected as the target ship. Initially, non-navigable and reward areas were designated based on the water depth and electronic navigational chart information. Thereafter, we conducted experiments using algorithms in three types of environments: normal conditions, turbulent weather, and obstacle-involved environments. Furthermore, we employed the Douglas–Peucker algorithm to eliminate excessive waypoints. Experimental results demonstrated that the path planning of a ship obtained using a deep Q network involved more efficient and safer decisions for ship navigation. Furthermore, the navigation distance was reduced by 1.77% compared to the passage plan used by actual ships. The proposed approach is advantageous for automatically deriving the optimal mid-range path of ships and can thus contribute toward improving maritime safety and efficiency.

Legislation Issues on the Invasion of Alien Species Through Ballast Water in Ships

The issue of alien species invasion caused by ballast water from ships has been recognized by the Global Environmental Fund as one of the four major threats to the oceans. As a major maritime nation, China is also confronted with the same problem. This paper outlines the hazards of alien species invasion through ballast water and analyzes the current legislation status and shortcomings of ballast water in Chinese ships. It proposes legislative strategies, including clearly defining legislative purposes, enacting specialized laws, and establishing a coordinated regulatory system, aiming to provide assistance to legislation and practices in China regarding the invasion of alien species through ballast water.

TDA/rGO@WS with Joule heat and photothermal synergistic effect: A promising adsorption material for all–weather recovery of viscous oil spills at sea

Oil spills are a global environmental protection challenge, and traditional adsorption materials have poor effect on low temperature and high viscosity marine oil spills. This article reports composite adsorption materials TDA/rGO@WS for viscous oil spills: loaded with rGO/TDA coating on a commercial biomass wood pulp sponge (WS), achieving Joule heating, photothermal effect and hydrophobic modification. The results showed that the TDA/rGO@WS has good photothermal conversion ability and Joule heating ability, and the temperature increased to 83.7 °C and 148 °C, respectively, under simulated solar irradiation and additional voltage at room temperature. The efficiency of adsorption at a low temperature of 5 °C increased by 22.41% at 1 sun and by 51.53% at 10 V. Temperature effectively reduced the viscosity of the offshore oil spill and ensures the efficient adsorption of oil spills at low temperatures promoted. The TDA/rGO@WS also showed good hydrophobicity (WCA=129°), excellent efficiency of water–oil separation (99.53%) and good adsorption capacity (9.4–13.68 g/g) for marine fuel oils. TDA/rGO@WS effectively solves the problem of cleaning up high–viscosity oil spills from ships in winter and polar waters, and proposes a new strategy for all–weather efficient treatment of oil spills at sea.

Invasive Round goby Neogobius melanostomus distribution, relative abundance, and establishment in pools of the Illinois Waterway following 30 years of invasion

Round goby Neogobius melanostomus – a small, benthic fish native to Eurasia – was first introduced to North America in the 1980s through ballast water of cargo ships. In 1990, the Round goby was first discovered in the Laurentian Great Lakes Basin and rapidly spread through all Great Lakes from 1993 to 1998. The Round goby is an aggressive, prolific, and efficient egg predator that subsequently displaced native fishes from their preferred habitats and resources in the Great Lakes, where they are well established and abundant. From Lake Michigan, Round goby moved south into the Chicago Area Waterway System in 1993 and slowly progressed down the Illinois Waterway to the Mississippi River from 2004 to 2019, where less is known about their abundance, establishment, and impact. The goal of this study was to gain a comprehensive understanding of the first large river invasion by Round goby in the Mississippi River Basin by leveraging Round goby capture data from 2019 to 2022 on all pools of the Illinois Waterway. We describe their current distribution, relative abundance (i.e., catch-per-unit-effort), frequency of occurrence, and establishment (i.e., presence of young-of-year and adults) status throughout the Illinois Waterway. Results show that catch-per-unit-effort, frequency of occurrence, and the proportion of sites where multiple life stages are present are considerably higher in the upstream pools relative to more downstream pools of the Illinois Waterway. Our data support that the Round goby has established self-sustaining populations in the Chicago Area Waterway System, the upper Illinois River (i.e. Dresden Island Pool downstream through Starved Rock Pool), and a portion of the lower Illinois River (i.e. Peoria Pool downstream through Alton Pool) of the Illinois Waterway. In the lower Illinois River, Round gobies appear to only be established in Peoria Pool, with captures occurring infrequently in La Grange Pool, and no Round gobies being captured in Alton Pool.