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The demand for efficient applications of solar energy and nanomaterials has grown significantly in recent years due to industrial needs and the desire to minimize energy consumption and costs. However, the efficiency of photovoltaic cells and solar-powered ships is highly dependent on solar radiation. In this study, a model for the installation of a parabolic trough surface collector (PTSC) was developed to achieve high temperatures on solar-powered ships. The current study analyzed the thermal characterization function in solar-powered ships under the effect of heat radiation, magnetic field, and viscous dissipation by employing hybrid magnetite particles (Fe3O4) and silver (Ag). The Cattaneo–Christov model has been used to assess heat flux in the thermal boundary layer. The Galerkin weighted residual method (GWRM) has been employed to solve the ordinary differential equations using MATHEMATICA 11.3 software. The findings showed that the thermal efficiency of the hybrid nanofluid was significantly enhanced by 56.3% relative percentage. The motto of the current investigation is developing a model for the installation of PTSC on solar-powered ships under various provided assumptions. [ABSTRACT FROM AUTHOR]

The direct optimization of ship hull designs using deep learning algorithms is increasingly expected, as it proposes optimization directions for designers almost instantaneously, without relying on complex, time-consuming, and expensive hydrodynamic simulations. In this study, we proposed a GAN-based 3D ship hull design optimization method. We eliminated the dependence on hydrodynamic simulations by training a separate model to predict ship performance indicators. Instead of a standard discriminator, we applied a relativistic average discriminator to obtain better feedback regarding the anomalous designs. We add two new loss functions for the generator: one restricts design variability, and the other sets improvement targets using feedback from the performance estimation model. In addition, we propose a new training strategy to improve learning effectiveness and avoid instability during training. The experimental results show that our model can optimize the form factor by 5.251% while limiting the deterioration of other indicators and the variability of the ship hull design. [ABSTRACT FROM AUTHOR]

The present study aimed to find the truth about the effect of ocean waves on the process of righting a capsized ship by employing common computational methods of marine salvage engineering. Mathematical models of ship stability and uprighting were developed to quantitatively evaluate the effects of wave encounter angle on the righting forces, bending moments and torques of the hull during the uprighting process. The results indicated that during the uprighting process, the maximum righting forces of the capsized ship were almost unchanged with a maximum difference of 1kN, when the ocean was calm or when the encounter angle of the waves varied. However, the righting force moment showed significant discrepancies under all conditions, with a maximum difference of 1177.5 kN m. When the wave encounter angle is at 0°, the shear force of some parts of the ship is 2–3 times that of the still water environment, and the shear force of some parts of the ship is 3–4 times that of the wave encounter angle at 300°. Remarkably, the bending moment varied by more than 200% at some particular locations under a particular wave encounter angle. Furthermore, the negative torque variation was relatively minor at a 300° wave encounter angle, and the uprighting process still needs relatively large righting forces. [ABSTRACT FROM AUTHOR]

Understanding the determination mechanism and dynamics of shipping freight rates has significant implications for practitioners, economists, and regulators of maritime transport. This paper systematically reviews the relevant papers on shipping freight rate published between 2000 and 2019. Specifically, it provides empirical insights including the major influencing factors of shipping freight rates and differences among the shipping sectors, and discusses the dominant methods and their applicability, strengths and weaknesses, and opportunities for new methods. Furthermore, the omissions and limitations in methods are explored to identify the research gaps and set a future research agenda. It is found that there is a strong focus on temporal dynamics with a wide range of modelling methods applied, while discussion on cross-sectional dynamics on how shipping freight rates are determined by vessel characteristics, contract terms, market competition, etc., is limited. Besides, the collaboration network analysis shows that more knowledge sharing and cross-discipline collaboration efforts can create potential for more inspired insights with advanced methods in this field. [ABSTRACT FROM AUTHOR]

This paper presents the results of an extensive model-scale experimental evaluation of autonomous ship landing guidance and control modes, with flight tests performed in the Maneuvering and Seakeeping (MASK) Basin at the U.S. Naval Surface Warfare Center Carderock Division. The experiments were performed using a commodities-based multirotor unmanned aerial vehicle (UAV) operating from a 20-ft-long model scale ship subject to scaled wave conditions. During testing, two separate guidance algorithms were evaluated: a quadratic programming (QP) based landing algorithm that plans the trajectory to a forecasted deck state and a simpler "baseline" method that tracks deck motions while closing the distance between the aircraft and deck at a constant rate. Both algorithms commanded a Froude-scaled explicit model following control law, and the control law parameters were modified to progressively degrade aircraft tracking bandwidths. The results showed that the predictive capabilities of the QP algorithm allowed more direct landing paths to be planned when compared to the baseline algorithm and also allowed the QP algorithm to land with lower tracking bandwidths. But while the QP algorithm performed well in the majority of cases, there were several landings where a combination of poor deck state predictions and how the QP algorithm utilizes predictions to choose a land time resulted in significant terminal velocity and attitude errors. The baseline guidance algorithm, on the other hand, proved to be both simple and reliable when the UAV was in high bandwidth configurations but required a high reference tracking bandwidth. [ABSTRACT FROM AUTHOR]

Summary: This paper focuses on the problem of the event‐triggered disturbance rejection tracking control for marine surface ships with ocean stochastic disturbances under actuator saturation effects. The ocean stochastic disturbances are described by the first‐order Markov stochastic process. The event‐triggered disturbance rejection tracking control is built through incorporating a stochastic disturbance observer and an auxiliary dynamic filter with the event‐triggered vectorial backstepping framework. A stochastic disturbance observer is established to provide stochastic disturbance estimations on‐line. Then, an auxiliary dynamic filter employs the commanded control derivation vector to modify the feedback control errors on‐line so as to preserve the disturbance rejection tracking control performance under adverse saturation effects. The event‐triggered control protocol involving tracking errors and commanded control derivations is designed to reduce the excessive wear and tear of propellers and thrusters in the presence of ocean stochastic disturbances. Illustrative simulations on a 1:70 model ship demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Ship detection finds extensive applications in fisheries management, maritime rescue, and surveillance. However, detecting nearshore targets in SAR images is challenging due to land scattering interference and non-axisymmetric ship shapes. Existing SAR ship detection models struggle to adapt to oriented ship detection in complex nearshore environments. To address this, we propose an oriented-reppoints target detection scheme guided by scattering points in SAR images. Our method deeply integrates SAR image target scattering characteristics and designs an adaptive sample selection scheme guided by target scattering points. This incorporates scattering position features into the sample quality measurement scheme, providing the network with a higher-quality set of proposed reppoints. We also introduce a novel supervised guidance paradigm that uses target scattering points to guide the initialization of reppoints, mitigating the influence of land scattering interference on the initial reppoints quality. This achieves adaptive feature learning, enhancing the quality of the initial reppoints set and the performance of object detection. Our method has been extensively tested on the SSDD and HRSID datasets, where we achieved mAP scores of 89.8% and 80.8%, respectively. These scores represent significant improvements over the baseline methods, demonstrating the effectiveness and robustness of our approach. Additionally, our method exhibits strong anti-interference capabilities in nearshore detection and has achieved state-of-the-art performance. [ABSTRACT FROM AUTHOR]

This study focuses on potential gas leakage scenarios during the natural gas transportation process in ship engine room. A three-dimensional model of the ship engine room is constructed to investigate the diffusion patterns of leaked gas and the resulting explosion and disaster risks. The results reveal that natural gas exhibits the highest concentration along the jet direction, with the concentration remaining above 5% by 360 s after the leakage. When an explosion intensity of 5 is chosen, the calculated results from TNO multi-energy method show an average relative error of less than 10% compared to the numerical simulations beyond 20 m. In the rear of obstacles, the peak overpressure decreases by 60%, and the time to reach the peak overpressure extends to 1.8 times the original duration. The range of slight building damage caused by explosion overpressure is the largest, averaging about twice the range of minor injuries to personnel. • The CFD model of methane diffusion and explosion in ship engine room was established. • Obstacles have a significant influence on gas diffusion and explosion in engine room. • The explosive effect of methane was assessed using the TNO multi-energy method. • The impact of methane leakage duration on the explosion safety distance was analyzed. [ABSTRACT FROM AUTHOR]

Researchers have explored various methods to fully exploit the all-weather characteristics of Synthetic aperture radar (SAR) images to achieve high-precision, real-time, computationally efficient, and easily deployable ship target detection models. These methods include Constant False Alarm Rate (CFAR) algorithms and deep learning approaches such as RCNN, YOLO, and SSD, among others. While these methods outperform traditional algorithms in SAR ship detection, challenges still exist in handling the arbitrary ship distributions and small target features in SAR remote sensing images. Existing models are complex, with a large number of parameters, hindering effective deployment. This paper introduces a YOLOv7 oriented bounding box SAR ship detection model (YOLOv7oSAR). The model employs a rotation box detection mechanism, uses the KLD loss function to enhance accuracy, and introduces a Bi-former attention mechanism to improve small target detection. By redesigning the network's width and depth and incorporating a lightweight P-ELAN structure, the model effectively reduces its size and computational requirements. The proposed model achieves high-precision detection results on the public RSDD dataset (94.8% offshore, 66.6% nearshore), and its generalization ability is validated on a custom dataset (94.2% overall detection accuracy). [ABSTRACT FROM AUTHOR]

This paper presents a forward modeling method for the scattering center (SC) model of dynamic ships on time-varying sea surfaces, tailored for remote sensing and target-recognition applications. Grounded in ship hydrodynamics, the methodology delineates ship movements amidst fluctuating waves, harnessing computer graphics to integrate ship–sea geometries across diverse temporal instances. Utilizing the four-path model, the composite scattering effects are segregated into distinct ship and sea contributions, along with their mutual interactions. Augmented by high-frequency electromagnetic principles, the paper quantifies and deduces SC parameters, culminating in a 3-D parameterized SC model for complex maritime targets. Unlike conventional inverse methods, this approach employs a "cause-to-effect" forward strategy, establishing clear links between SCs and local geometries, enhancing the model's physical clarity. Using the fishing ship as a case, this research compared the normalized similarity index and position-matching rate between the reconstructed synthetic aperture radar (SAR) image and the simulated SAR image. The results indicate that all computed results exceeded 90%. Furthermore, a comparison was conducted between the reconstructed radar cross-sections (RCS) obtained by expanding the model within a large angular range and the simulated results. The root mean square error between the two was less than 3 dB, affirming the accuracy and effectiveness of the proposed model. Additionally, the research examines the variations in SCs during the six-degrees-of-freedom motions, providing a detailed quantitative analysis of their temporal trends in amplitude and position. In summary, this investigation furnishes an efficient and economical framework for rapid radar characterization in dynamic, variable marine environments, fostering advancements in remote sensing and maritime target identification. [ABSTRACT FROM AUTHOR]

Huang, W.; Li, S.; Lu, Y., and Zhang, R., 2024. Hydrodynamic characteristics of an ecological revetment cavity structure under the propagation of ship-generated waves in a restricted channel. Journal of Coastal Research, 40(2), 382–394. Charlotte (North Carolina), ISSN 0749-0208. With the rapid development of inland waterway transportation and the rapid increase of ship traffic in restricted channels, the role of ship-generated waves on the restricted channel shore slope becomes increasingly significant. Some river bank protection projects use cavity structures to prevent bank slopes from being scoured and have achieved remarkable results. However, the hydrodynamic characteristics under the action of ship traveling waves inside and outside the cavity are not yet clear. Thus, this paper studies the time and frequency domain characteristics of ship-generated wave fluctuations, flow velocity distribution characteristics, and turbulence distribution characteristics in the cavity, under the action of ship-generated waves, by conducting self-propelled ship model flume tests using a new type of cavity shore protection structure applied to a restricted channel. This study investigates the application of such a structure to shallow water coastal areas with frequent ship traffic. The corresponding results demonstrate that during the ship traveling wave transfer to the cavity, the fluctuation frequency did not change significantly, and fluctuation energy concentrated in the frequency range of 0–1.5 Hz. The high-frequency (0.40–1.5 Hz) energy is concentrated in the secondary wave process, and the low-frequency (0–0.40 Hz) energy is observed throughout the fluctuation process. The cavity structure changes the flow velocity from low-frequency periodic flow to high-frequency oscillatory flow, and the frequency of flow velocity change tends to be uniformly distributed with significantly enhanced turbulence. The cavity's maximum wave height, flow velocity, and turbulence energy positively correlate with the self-propelled velocity of the vessel Vc. Moreover, the characteristic values increase slowly for Vc in the subcritical velocity region (Frh < 0.84), and the characteristic values increase sharply for Vc in the transcritical velocity region (0.84 < Frh < 1.12). [ABSTRACT FROM AUTHOR]

This paper presents the development of a displacement measurement system for small-scale physical models of moored ships, aimed at providing data to evaluate displacement amplitudes and determine whether they surpass predetermined operational limits. The system, which combines cameras and inertial sensors, captures six degrees of freedom, allowing measurements of surge, sway, heave, yaw, roll, and pitch. The developed system was initially tested isolating each degree of freedom for analysis, and subsequently applied to a scale model of a port terminal berth, with a bulk carrier vessel docked, subject to wave action. Scale models of port terminals have been extensively validated over numerous years of research and development. To evaluate the system's response, displacement measurements obtained through the developed system were compared with a commercial system widely recognized for measuring rigid body movements, the Qualisys® system. This comparison shows both systems obtained similar results, indicating that the developed system meets its intended purpose. Overall, the system provides a reliable tool for studying the complex behavior of moored vessels and evaluating operational and safety conditions in port terminals. [ABSTRACT FROM AUTHOR]

In recent decades, maritime transport, hand in hand with the International Maritime Organization (OMI), has promoted a change in the energetic model in ships and harbors. The main goal of this paper is to show the most useful advances in technologies with respect to reducing gas and particle emissions, and the implementation of technologies based on renewable energies for the propulsion of ships and the energy supply in harbors. Furthermore, new hybrid renewable energy-desalination water technologies which could change the shape of water supply to the ships from near shore zones will be shown. To carry out this study, exhaustive bibliographic research was conducted, including scientific and technical papers. [ABSTRACT FROM AUTHOR]

Ship detection is a crucial task for waterway surveillance and channel optimization, especially in close proximity to the shore. However, detecting ship in visible image‐based detection remains a challenge due to the limited nature of visible image datasets. To address this issue, the Inland Ships Data Set (ISDS) is constructed to facilitate research on ship identification. On the other hand, most detection methods struggle to accurately identify ships that are small in size. Therefore, a visible image‐based ship detection model is proposed that employs a multi‐scale weighted feature fusion structure with the YOLOv4 detection model to improve the efficacy of small ship detection. Specifically, the YOLOv4 model is improved through fusing multi‐scale feature, redesigning priori frame, and enhancing loss function. The model, named YOLOv4‐MSW (i.e. YOLOv4 based on Multi‐Scale Weighted feature fusion), exhibits improved performance on ship detection in experiments conducted on the ISDS dataset, outperforming the original YOLOv4 model by improving the average precision (AP) by 4.87% and the recall rate by 10.03%. Meanwhile, the model achieve better detection accuracy and improve the average precision rate by at least 0.86% compared to existing learned object detection methods. The code related to this work are released at https://github.com/Sunhuashan/YOLOv4‐MSW. The whole dataset is available at https://drive.google.com/drive/folders/1fzJ2fcqiko6lFwqIEGghMceoQgv‐8jBy. [ABSTRACT FROM AUTHOR]

This paper presents numerical simulations of propeller–hull interaction of a ship model for the dynamic condition, demonstrating the ability of the developed self-propulsion module in OpenFOAM. A dynamic motion class has been developed based on the sliding mesh method to simulate a rotating propeller with ship motions. A body-force method is also implemented to simulate propeller–hull interaction to reduce the computational cost of propeller modeling. Validation studies were carried out for the Japan Bulk Carrier (JBC) ship model. The bare-hull resistance, sinkage, and trim are verified against the experimental data. The propeller open-water hydrodynamic characteristics are then computed and validated using sliding mesh and body-force methods. Finally, the self-propulsion simulations are carried out for the JBC model in calm water with sinkage and trim at the design speed. Numerical predictions of the self-propulsion parameters and axial flow velocity distributions at different transverse locations are presented. [ABSTRACT FROM AUTHOR]

Ship detection has been an area of focus for high-frequency surface wave radar (HFSWR). The detection and identification of ship formation have proven significant in early warning, while studies on the formation identification are limited due to the complex background and low resolution of HFSWR. In this paper, we first establish a spatial distribution model of ship formation in HFSWR. Then, we propose a cascade identification algorithm of ship formation in the clutter edge. The proposed algorithm includes a preprocessing stage and a two-stage formation identification stage. The Faster R-CNN is introduced in the preprocessing stage to locate the clutter regions. In the first stage, we propose an extremum detector based on connected regions to extract suspicious regions. The suspicious regions contain ship formations, single-ship targets, and false targets. In the second stage, we design a network connected by a convolutional neural network (CNN) and an extreme learning machine (ELM) to identify two densely distributed ship formations from inhomogeneous clutter and single-ship targets. The experimental results based on the factual HFSWR background demonstrate that the proposed cascade identification algorithm is superior to the extremum detector combined with the classical CNN algorithm for ship formation identification. Meanwhile, the proposed algorithm performs well in weak formation and deformed formation identification. [ABSTRACT FROM AUTHOR]

Ship detection is vital for maritime safety and vessel monitoring, but challenges like false and missed detections persist, particularly in complex backgrounds, multiple scales, and adverse weather conditions. This paper presents YOLO-Vessel, a ship detection model built upon YOLOv7, which incorporates several innovations to improve its performance. First, we devised a novel backbone network structure called Efficient Layer Aggregation Networks and Omni-Dimensional Dynamic Convolution (ELAN-ODConv). This architecture effectively addresses the complex background interference commonly encountered in maritime ship images, thereby improving the model's feature extraction capabilities. Additionally, we introduce the space-to-depth structure in the head network, which can solve the problem of small ship targets in images that are difficult to detect. Furthermore, we introduced ASFFPredict, a predictive network structure addressing scale variation among ship types, bolstering multiscale ship target detection. Experimental results demonstrate YOLO-Vessel's effectiveness, achieving a 78.3% mean average precision (mAP), surpassing YOLOv7 by 2.3% and Faster R-CNN by 11.6%. It maintains real-time detection at 8.0 ms/frame, meeting real-time ship detection needs. Evaluation in adverse weather conditions confirms YOLO-Vessel's superiority in ship detection, offering a robust solution to maritime challenges and enhancing marine safety and vessel monitoring. [ABSTRACT FROM AUTHOR]

The underwater electric field (UEF) signature of a ship is a key factor in its survivability in marine warfare. Moreover, the study of a ship's UEF using scale models of ships in pools can be useful for the design of electromagnetically stealthy ships. Aiming at the system requirement of measuring and analyzing the UEF of scale models of ships with low noise, many channels, and real-time responsivity, we developed a system consisting of electrode sensors, a measuring device, and a personal computer (PC). Small Ag/AgCl electrodes with low noise and high stability were used. The measuring device was capable of simultaneously amplifying, sampling, and storing 24 channels of UEF data in real-time, and it was connected to the PC via Ethernet to facilitate the transfer of UEF data at high speeds. The PC software could display 24 low-frequency UEF curves in real time and perform spectral analysis and filtering of the UEF signals. In system performance tests, we found that the system had a noise floor lower than 6.34 nV/rt(Hz)@1 Hz and could simultaneously sample 24 channels of UEF signals while storing, displaying, and analyzing the signals in real-time. The primary functions of the system were also validated in a pooled experiment. [ABSTRACT FROM AUTHOR]

The loss of Arctic sea ice is one of the most visible signs of global climate change. As Arctic sea ice has retreated, Arctic marine shipping has increased. The Pan-Arctic's unique underwater acoustic properties mean that even small increases in ship traffic can have a significant effect on the ambient soundscape. This study presents the first long-term, basin-scale model of shipping noise in the Pan-Arctic with a focus on a few select sub-regions. The Arctic Ship Traffic Database from the Protection of the Arctic Marine Environment is used in this study to model the locations and source levels from ships operating in the Pan-Arctic between 2013 and 2019. The acoustic footprint of these ships is explored temporally for the entire basin as well as for the select large maritime ecosystems of the Barents Sea, the Northern Bering-Chukchi Sea, and Baffin Bay. From 2013 to 2019, modeled shipping noise propagating underwater broadly increased between 5–20 dB across the Pan-Arctic, but more specific results in sub-regions are presented and discussed. [ABSTRACT FROM AUTHOR]

This manuscript presents a method for reproducing sound fields actively by using a vibrating submerged structure as the field reproduction source, with the target sound field to be reproduced defined in the frequency domain using the acoustic brightness approach. To balance the predetermination of a mono- or multi-zone target sound pressure field and the control effort required, singular value decomposition of the structural-acoustic system matrix is proposed. The dependency of the radiation efficiency into the target zone on the singular modes representing source and pressure modes is investigated using a wavenumber-domain approach. Furthermore, a feedforward control principle is adopted for adaptive sound-field reproduction with mode matching from the least squares perspective. Finally, an experiment is reported that involve synthesizing a tonal target underwater acoustic signature of a model of a fast attack craft (scale 1:8) at a measurement facility at Lake Plön in Germany. The results show that with the structural-acoustic brightness approach structural modes with radiation coupling into the target zone are excited and related pressure modes exhibit individual focus in the direction of hydrophones in use. Finally, a predetermined narrowband sound pressure field is actively reproduced at the hydrophone positions using inertial actuators and accelerometers on the ship model's hull. [ABSTRACT FROM AUTHOR]

Deep learning is the major technique used to identify objects in images captured by the synthetic aperture radar (SAR). While SAR images can be used to identify ships in general, detecting multiple ships or small vessels in these images in complex contexts remains an outstanding challenge. This study proposes a model of detection based on the improved PP-YOLO deep convolutional neural network that can identify multiple ships as well as small vessels in complex scenarios from SAR images. The histogram equalization algorithm is first used to preprocess the SAR images, and then the initial anchor box is optimized by using the shape similarity distance-based K-means clustering algorithm. Following this, the accuracy of the training network is improved based on the feature pyramid network and an attention mechanism. The experimental results show that the average accuracy (average precision) of the model was 94.25% at 41.63 frames per second on the GF-3 and the Sentinel-1 SAR datasets, superior to those of YOLOv3 (Darknet), YOLOv7, FPN (VGG), SSD, Faster R-CNN, and PP-YOLO (RestNet50-vd). The model also satisfies the demands of real-time detection. [ABSTRACT FROM AUTHOR]

Deep learning technology has greatly propelled the development of intelligent and information-driven research on ship infrared automatic target recognition (SIATR). In future scenarios, there will be various recognition models with different mechanisms to choose from. However, in complex and dynamic environments, ship infrared (IR) data exhibit rich feature space distribution, resulting in performance variations among SIATR models, thus preventing the existence of a universally superior model for all recognition scenarios. In light of this, this study proposes a model-matching method for SIATR tasks based on bipartite graph theory. This method establishes evaluation criteria based on recognition accuracy and feature learning credibility, uncovering the underlying connections between IR attributes of ships and candidate models. The objective is to selectively recommend the optimal candidate model for a given sample, enhancing the overall recognition performance and applicability of the model. We separately conducted tests for the optimization of accuracy and credibility on high-fidelity simulation data, achieving Accuracy and EDMS (our credibility metric) of 95.86% and 0.7781. Our method improves by 1.06% and 0.0274 for each metric compared to the best candidate models (six in total). Subsequently, we created a recommendation system that balances two tasks, resulting in improvements of 0.43% (accuracy) and 0.0071 (EDMS). Additionally, considering the relationship between model resources and performance, we achieved a 28.35% reduction in memory usage while realizing enhancements of 0.33% (accuracy) and 0.0045 (EDMS). [ABSTRACT FROM AUTHOR]

• Prediction method of steady wave forces acting on an obliquely moving ship in short waves is proposed. • The existing asymptotic formula is enhanced in terms of the wave amplitude and flow velocity near the ship. • Proposed method efficiently predicts course-keeping manoeuvres of a ship model in regular short waves. • Proposed method approximately predicts course-keeping manoeuvres even under rudder effectiveness for a full-scale ship. In this study, we propose a prediction method for steady wave forces acting on an obliquely moving ship in short waves. Particularly, we enhance an existing method that focuses on refraction of flow and waves in the vicinity of ship's waterline, in terms of the wave amplitude in the near region of the ship and the flow velocity. The former is theoretically modified by deriving an advection equation for wave energy on a ship-fixed frame, and the latter is improved by reflecting the results of computational fluid dynamics that automatically includes viscous effects. A comparison between the prediction and published captive model test results shows that the present method can more adequately capture the variation of the steady wave forces owing to the ship advancing speed and lateral drift than the original method, although the prediction accuracy is not necessarily improved under all conditions. To confirm the applicability of the present method for steady wave forces to ship manoeuvring problems, we predict course-keeping manoeuvres of a ship in regular short waves through a numerical simulation that considers only the steady wave forces in the equation of motion in calm water. The manoeuvring simulation results are validated using previously published free-running model test results, involving various rudder effectiveness conditions for the ship model and full-scale ships, both with and without engine limits. The comparison shows that the present method for steady wave forces is effective in predicting the course-keeping manoeuvres under rudder effectiveness conditions for a ship model in regular short waves. Nonetheless, the present method is insufficiently practical in terms of the manoeuvring simulation under rudder effectiveness conditions for a full-scale ship that is relatively more susceptible to waves. We confirm that an empirical correction for the computed steady wave surge forces based on the discrepancy between the measured and computed values under the ship resting enables the approximate prediction of the course-keeping manoeuvres even under the rudder effectiveness conditions for the full-scale ship. [ABSTRACT FROM AUTHOR]

The interaction between aerosols and clouds is one of the major uncertainties in past climate change, affecting the accuracy of future climate projections. Ship tracks, trails left in clouds through the addition of aerosol in the ship exhaust plume, have become a key observational tool for constraining aerosol‐cloud interactions. However, many expected tracks remain undetected, presenting a significant gap in current knowledge of aerosol forcing. Here we leverage a plume‐parcel model to simulate the impact of aerosol dispersion for 2,957 cases off California's coast on cloud droplet number concentration (CDNC) enhancements. Plume‐parcel models show a large sensitivity to updraft uncertainties, which are found to be a primary control on track formation. Using these plume‐parcel models, updraft values consistent with observed CDNC enhancements are recovered, suggesting that relying solely on cloud‐top radiative cooling may overestimate in‐cloud updrafts by around 50%, hence overstating the cloud sensitivity to aerosols. Plain Language Summary: Here we investigate the interactions between aerosols and clouds and their impact on climate change. Ship tracks were used to study these interactions, and aerosol emissions from ships were modeled. It was shown that the increase in cloud droplets from ship aerosol was highly sensitive to the speed of the updraft in the clouds. A method was developed to fit the updraft to the observed cloud enhancements; the resultant updrafts were smaller than current estimates, suggesting that the clouds may be less sensitive to aerosols than previously thought. Key Points: Using ship emission data, a plume‐parcel model was implemented to study aerosol availability and cloud sensitivity in ship track formationCloud droplet number enhancements are very sensitive to uncertainties in the in‐cloud updraftThe retrieved plume‐parcel‐based updrafts suggest that clouds may be less sensitive to aerosols than implied by other estimates [ABSTRACT FROM AUTHOR]

Modern ships are complex energy systems containing a large number of different elements. Each of these elements is simulated separately. Since all these models form a single system (ship), they are interdependent. The operating modes of some systems influence others, but at the same time, the work of all the systems should be aimed at fulfilling the basic functions of the ship. The work proposes a methodological approach to combining various systems of ships into a single complex model. This model allows combining models of ship systems of various levels (microlevel, macrolevel, metalevel, megalevel). The work provides examples of models of such multi-level energy systems. These are energy systems composed of an electric generator, a diesel engine, a propeller shaft, and algorithms used for operating the common parts of the ship's electric power system and a piston wear process. Analytical, structural, numerical, and object-oriented models were made for these objects. Each of these particular models describes a limited class of problems, has characteristic properties, and a mathematical structure. The work shows how particular models can be interconnected using a set-theoretic description. Particular models are combined into macrolevel models, whose output parameters are quantities that are by no means related. The macrolevel models are interrelated using control models. Control models belong to the metalevel and allow for assigning settings and response thresholds to algorithms used in automation systems. Such a model (megalevel model) allows, ultimately, investigating the dynamics of the entire system as a whole and managing it. [ABSTRACT FROM AUTHOR]

This study focuses on the Wartsila 9L34DF engine and proposes an integrated system for low-temperature carbon capture using the coupling of cold and hot energy recovery with membrane separation in LNG-powered ships. By utilizing a series dual-pressure organic Rankine cycle (SDPORC) system to recover waste heat from the engine exhaust gases and generate electricity, the system provides power support for the low-temperature carbon capture compression process without consuming additional ship power. To validate the accuracy and reliability of the mathematical model, the simulation results are compared with the literature's data. Once the model's accuracy is ensured, the operational parameters of the integrated system are analyzed. Subsequently, working fluid optimization and genetic algorithm sensitive parameter optimization are conducted. Finally, under the optimal operating conditions, the thermodynamic performance and economic evaluation of the integrated system are assessed. The results demonstrate that the net power output of the integrated system is 100.95 kW, with an exergy efficiency of 45.19%. The unit carbon capture cost (UCC) is 14.24 $/ton, and for each unit of consumed LNG, 1.97 kg of liquid CO2 with a concentration of 99.5% can be captured. This integrated system significantly improves the energy utilization efficiency of ships and reduces CO2 emissions. [ABSTRACT FROM AUTHOR]

The extraction of ship behavior patterns from Automatic Identification System (AIS) data and the subsequent prediction of travel routes play crucial roles in mitigating the risk of ship accidents. This study focuses on the Wuhan section of the dendritic river system in the middle reaches of the Yangtze River and the partial reticulated river system in the northern part of the Zhejiang Province as its primary investigation areas. Considering the structure and attributes of AIS data, we introduce a novel algorithm known as the Combination of DBSCAN and DTW (CDDTW) to identify regional navigation characteristics of ships. Subsequently, we develop a real-time ship trajectory prediction model (RSTPM) to facilitate real-time ship trajectory predictions. Experimental tests on two distinct types of river sections are conducted to assess the model's reliability. The results indicate that the RSTPM exhibits superior prediction accuracy when compared to conventional trajectory prediction models, achieving an approximate 20 m prediction accuracy for ship trajectories on inland waterways. This showcases the advancements made by this model. [ABSTRACT FROM AUTHOR]

A good situation awareness (SA) of the navigator is essential for the safety of the ship, especially in coastal areas. In this study, the Unity 3D engine was used to simulate the navigation of a coastal trading vessel along predefined routes in the Baltic Sea. The SA of the helmsman, who was either Chinese or European, was assessed several times with the SAGAT test (Endsley, 1995b, 20-21) a nd c ompared b etween l ow a nd h igh workload conditions and between manual and autopilot navigation. High workload and automated navigation both reduced SA significantly and in an additive manner. No difference was found between Chinese and European participants. In contrast to previous accident analyses of SA, we found that SA level 3 (projection of future states) was most strongly affected by both factors, while SA levels 1 (perception of relevant information) and 2 (comprehension of the current situation) suffered to a lesser extent. Further research is needed to establish specific relationships between types of automation on ships, types of workload, and SA problems in order to design countermeasures. [ABSTRACT FROM AUTHOR]

With economic globalization, ships tend to be larger and faster, and the volume of maritime traffic is increasing. Ships sailing in waters with dense traffic flow are easy to fall into complicated multi-ship encounter situations and have a high risk of collision. Thus, it is crucial to conduct risk analysis in such situations. In this paper, a modified collision analysis method for detecting dangerous multi-ship encounters in ports and waterways is proposed. The velocity obstacle algorithm is utilized to detect encounters. The model of the elliptic ship domain was integrated into the algorithm as the criteria. The Boolean operation was also used in the multi-ship encounter. A case study is conducted to illustrate the efficacy of the improved model, and a comparison between the existing method and the formal model is also performed. The results indicate that with the integration of the ship domain, the proposed method can effectively detect the encounters of multiple ships which are dangerous to collide. [ABSTRACT FROM AUTHOR]

Ship maneuvering is a complex operation with inherent uncertainties. To express this complexity in system performance during the navigation process, an analysis model has been developed using Functional Resonance Analysis Method (FRAM) and Dynamic Bayesian Network (DBN). The functional level of dynamic work onboard is assessed and modeled using FRAM qualitatively, in which a key function and the function's potential coupling for specific instantiation are identified. Further analysis is done by integrating the FRAM analysis with DBN for quantification. The evolution of system performance over time is determined through changes in the probability of function's mode, namely strategic, tactical opportunistic, and scrambled. The model presented in this study concerns the fluctuation of ship officer performance to overcome the obstacles during the encounter event. As a result, the integration of FRAM-DBN shows promising usability to evaluate human performance. The essence of human adaptive capacity is also highlighted through system resilience potency, that is, the potency to learn, respond, monitor, and anticipate. We also discuss how this finding contributes to enhance safety analysis, in specific, to provide explicit representation of the dynamic in human performance in ship navigation based on Safety-II idea. [ABSTRACT FROM AUTHOR]

The forces arising on the ship's rudderat different angles of attack in an unbounded flow are investigated. The components of the resulting force on the rudder are represented in terms of the rudder lift and drag forces, as well as in terms of the normal and tangential forces on the rudder. The well-known mathematical models of hydrodynamic rudder coefficients are analyzed, and their disadvantages are found. New mathematical models of hydrodynamic coefficients have been obtained, in particular, the coefficients of rudder lift and drag, which take into account the aspect ratio of the rudder, its relative thickness and can be applied to any angle of attack of the flow on the rudder. On specific examples for rudders of the NACA series, the adequacy of the proposed models and their consistency with known experimental studies are illustrated. It is shown how the rudder lift and drag change, as well as the components of the resulting force for the maximum possible range of changes in the local drift angle and the rudder angle. [ABSTRACT FROM AUTHOR]

This paper presents the development of a method for calculating the horizontal contact forces between two bodies in a real-time ship manoeuvring simulator. The method was implemented in the simulator of the University of São Paulo, whose computing core is named "Dyna". The model proposed calculates restoration and friction forces between bodies and has a Momentum-Impulse based criterion to reduce numerical issues when the simulation numerical integration has large time-steps. The model was empirically evaluated at the simulator by deck officers, in real-time simulations with pilots and tugmasters. We also ran simulations of that model to compare its performance under different integration time-steps lengths. [ABSTRACT FROM AUTHOR]

This paper describes the results obtained from an archaeometric study of a bronze Nuragic small boat model (Sardinia, Italy) dating from the Early Iron Age (presumably 9th–7th centuries BC). The artifact comes from an unknown location in Sardinia and is one of the objects that came to the Museum of Turin in the 19th century. This model is of particular interest as it is a unique Nuragic boat model containing a human figure among its decorations. The artifact is kept in the collection of the Royal Museum of Turin (Italy) and is a typical example of Sardinian manufacture from the Early Iron Age. This study was carried out using a combination of non-invasive techniques with energy dispersive X-ray fluorescence spectrometry (ED-XRF) integrated with Monte Carlo (MC) simulations and Raman spectroscopy, which allowed the characterization of the alloy of the artifact. [ABSTRACT FROM AUTHOR]

Molecular data storage is becoming a viable alternative to traditional information storage systems. Here, we propose a method where the presence or absence of a given molecule in a mixture of compounds represents a bit of information. As a novel approach, direct analysis in real time (DART) ionization mass spectrometry is used to recover and decode the information stored at the molecular level. Nicotinic acid derivatives were synthesized and used as the 'bit compounds'. Their volatility and ease of ionization make these molecules especially suitable for DART-MS detection. The application of DART-MS as a method with an ambient ionization technique, enables the re-reading of digital chemical codes embedded in the material of ordinary objects. Our method is designed to store and read back short pieces of digital information, up to several hundred bits. These codes can have the function of barcodes or QR codes, as shown in our proof-of-principle applications. First, modelling a QR code as a link to our university's website, three solutions were prepared, each representing 22 bits. Proceeding further, the bit compounds were incorporated into a polymer matrix that is suitable for 3D printing, and a toy ship was created with a hidden barcode. In addition, decoding software was developed to process the DART-MS spectra. The nicotinic acid components representing the bits dominated the DART-MS spectra and error-free decoding was achieved. [ABSTRACT FROM AUTHOR]

Molecular data storage is becoming a viable alternative to traditional information storage systems. Here, we propose a method where the presence or absence of a given molecule in a mixture of compounds represents a bit of information. As a novel approach, direct analysis in real time (DART) ionization mass spectrometry is used to recover and decode the information stored at the molecular level. Nicotinic acid derivatives were synthesized and used as the 'bit compounds'. Their volatility and ease of ionization make these molecules especially suitable for DART-MS detection. The application of DART-MS as a method with an ambient ionization technique, enables the re-reading of digital chemical codes embedded in the material of ordinary objects. Our method is designed to store and read back short pieces of digital information, up to several hundred bits. These codes can have the function of barcodes or QR codes, as shown in our proof-of-principle applications. First, modelling a QR code as a link to our university's website, three solutions were prepared, each representing 22 bits. Proceeding further, the bit compounds were incorporated into a polymer matrix that is suitable for 3D printing, and a toy ship was created with a hidden barcode. In addition, decoding software was developed to process the DART-MS spectra. The nicotinic acid components representing the bits dominated the DART-MS spectra and error-free decoding was achieved. [ABSTRACT FROM AUTHOR]

The reproduction of magnetic signatures is an important issue concerning the safety of ship traffic, as well as the identification and classification of vessels. Moreover, military applications of magnetic signatures and their reproduction refer to the activation or protection against activation of magnetic naval mines. Previous works on this subject focused on recording and replicating the signatures under the same conditions as those under which they were measured, e.g., on the same ship courses. In this article, much greater capabilities of the multi-dipole model are presented, including simultaneous identification of permanent and induced magnetism. Determining the dipole values using the data from cardinal directions gives the possibility of determining the magnetic field density at any trajectory (position), direction, or depth, with further reconstruction of the entire magnetic field on the basis of residual measurements. For the purpose of this article, a numerical test model of a corvette-type ship has been modelled in Opera simulation software for different geographical positions. The synthetic data from the simulator served as the data source for determining the parameters of the multi-dipole model and the reference data for the verification of the signatures reconstructed for other positions, directions, and depths than those used to determine the model parameters. To determine all permanent magnetization components, data sets were used for two different values of the external magnetic field vertical component. Finally, as a culmination of the demonstration of model universality, the entire magnetic field around the ship was reproduced for different control points on Earth, and for different courses and depths. Investigating the possibility of reconstructing the magnetic signature at a different geographic location than the place where the measurement was made for model synthesis is the main original issue considered in this paper. [ABSTRACT FROM AUTHOR]

In order to improve the detection accuracy of the collision detection system for unmanned ships at sea, this paper proposes a dynamic collision detection method based on improved ZigBee network wireless communication technology. The collision parameter detection model of unmanned ships at sea based on the ZigBee network and wireless communication network control is constructed. The communication network model is established by using wireless sensor network communication and radio frequency identification tag recognition technology. The experimental results show that the system can more accurately analyze and detect the collision of unmanned ships at sea and judge the route information of ships when there are obstacles. The collision dynamic detection accuracy of the system is 25% higher than that of traditional methods on average, and the performance is superior. [ABSTRACT FROM AUTHOR]

The paper publishes a Greek graffito on a Zeest 80 amphora, found in Negrilești, in the settlement of Sântana de Mureș-Chernyakhov culture. The words ΝΑΥΚΛΕΡ(...) ΕΛΛΗΝΙΚΟΝ inscribed on the upper part of the amphora can be associated withprimary contentthetransport process -loading the container on the ship at the place of origin of the content. The characteristics of the amphora and the inscription are connected with the oil supply in the province of Scythia. The information highlights the trade connections of the settlements fromthe Lower Danube with the eastern provinces of Roman Empire at the end of the 3rd century, the beginning of the 4th century AD. [ABSTRACT FROM AUTHOR]

Based on data, there are more than 28 thousand residents in Karangasem, Bali, who live below the poverty line. This poverty occurs because residents who were previously involved in the tourism industry cannot meet their basic needs, with the average monthly per capita expenditure below the poverty line. Karangasem was chosen deliberately as a research location because it has the lowest human development index in Bali. The research sample was taken randomly from poor households who previously worked in the tourism sector and are now laid off as informants. Further data was collected through structured interviews and observations. The results of data analysis and discussion show that the entrepreneurial welfare project in East Bali identified two strategies for reducing poverty. First, cluster one is a strategy for poor households who are very poor and have a low level of education. In situations of economic and social limitations, it is necessary to channel employment opportunities through a job placement system for this type of household. They are given the opportunity to produce goods for certain companies, involving three parties: poor individuals, companies, and the government. Second, cluster two is a strategy for poor individuals who work independently to increase their income. For entrepreneurial households, are advised to develop their businesses into micro, small and medium businesses to increase sales. This strategy focuses on improving quality in the production, marketing and financing processes. The second cluster strategy is a model of rural community empowerment based on partner)ships. [ABSTRACT FROM AUTHOR]

In order to identify ship collision risk for the security of maritime transportation in a close-quarters situation, a novel real-time ship collision risk awareness approach is proposed by developing a novel non-linear velocity obstacle set, QSD-NLVO. More specifically, the Quaternion Ship Domain model was introduced into the non-linear velocity obstacle algorithm, and the conflict position was reasonably defined. By replacing the conflict position with ship domain, the proposed method can more reasonably assess the safety radius of the conflict in different ship encounter scenarios. The presented model enhanced the accuracy of collision risk identification by replacing the collision position in non-linear velocity obstacle algorithm with quaternion ship domain. Finally, case studies were implemented to illustrate the effectiveness of the QSD-NLVO approach. The developed model may be utilized as a guide for investigating port traffic safety as well as a tool for maritime surveillance operators to monitor port traffic collision risks and increase traffic safety. [ABSTRACT FROM AUTHOR]

And like in London, these national and subnational divisions are not without meaning, since D/E/G/N papers reference the distinctive institutions of Maghrebi governments - their Emperors, Deys, Pashas, Ambassadors, and individual relations with the Ottoman Empire and Europe - nearly as often as their London counterparts. The first consistent Irish newspapers (excluding several short-lived papers dedicated to new rulers or particular significant events) appeared in the 1680s and 1690s, yet by the early eighteenth century were "a permanent feature in the daily life of Dublin" (these early newspapers' impact on people outside major cities was much more tenuous; see below). Like the vast majority of London papers through the early eighteenth century, shaped by the I London Gazette i 's example, by the fear of reimposed censorship, and by an audience with interests in trade and global power, early D/E/G/N papers focused heavily on "factual" news with minimal political comment, often drawing on French, Dutch, and other European prints but primarily from London papers themselves. [Extracted from the article]

While Romney still spoke about "slaves", both Mosterman and Maskiell systematically used the term "enslaved." Unlike Romney, she does not limit herself to New Netherland, but also paid attention to the time period following the 1664 English takeover by analyzing spaces of enslavement among eighteenth-century New York families with Dutch roots. The steady increase in publications about New Netherland over the past years, triggered perhaps by Russell Shorto's bestseller I The Island at the Center of the World i (2004), the 2009 celebrations in Manhattan of the 400th anniversary of the arrival of Henry Hudson, or the diligence of the New Netherland Institute in supporting new scholarship, has fundamentally changed this. [Extracted from the article]

Early theories of status dynamics in small groups portrayed intragroup status as a limited resource—as the status of one group member rises, the status of another must fall. Recent theorizing presents an alternative view: that the amount of status available to group members can be variable rather than fixed. Building on this view, we theorize that the average level of intragroup status changes as a function of group performance, such that the intragroup status of an average group member is higher in groups with higher performance and lower in groups with lower performance. We further theorize that changes in group solidarity partly account for the link between group performance and intragroup status. Across three preregistered studies, we find support for these hypotheses, which we hope will kindle interest in identifying other factors that can account for changes in intragroup status equilibria. [ABSTRACT FROM AUTHOR]

Molecular data storage is becoming a viable alternative to traditional information storage systems. Here, we propose a method where the presence or absence of a given molecule in a mixture of compounds represents a bit of information. As a novel approach, direct analysis in real time (DART) ionization mass spectrometry is used to recover and decode the information stored at the molecular level. Nicotinic acid derivatives were synthesized and used as the 'bit compounds'. Their volatility and ease of ionization make these molecules especially suitable for DART-MS detection. The application of DART-MS as a method with an ambient ionization technique, enables the re-reading of digital chemical codes embedded in the material of ordinary objects. Our method is designed to store and read back short pieces of digital information, up to several hundred bits. These codes can have the function of barcodes or QR codes, as shown in our proof-of-principle applications. First, modelling a QR code as a link to our university's website, three solutions were prepared, each representing 22 bits. Proceeding further, the bit compounds were incorporated into a polymer matrix that is suitable for 3D printing, and a toy ship was created with a hidden barcode. In addition, decoding software was developed to process the DART-MS spectra. The nicotinic acid components representing the bits dominated the DART-MS spectra and error-free decoding was achieved. [ABSTRACT FROM AUTHOR]