Search Results (36)

Collisions between ships and sea ice pose a significant threat to maritime safety, making it essential to detect sea ice and perform safety-oriented path planning for polar navigation. This paper utilizes an optimized You Only Look Once version 5 (YOLOv5) model, designated as YOLOv5-ICE, for the detection of sea ice in satellite imagery, with the resultant detection data being employed to input obstacle coordinates into a ship path planning system. The enhancements include the Squeeze-and-Excitation (SE) attention mechanism, improved spatial pyramid pooling, and the Flexible ReLU (FReLU) activation function. The improved YOLOv5-ICE shows enhanced performance, with its mAP increasing by 3.5% compared to the baseline YOLOv5 and also by 1.3% compared to YOLOv8. YOLOv5-ICE demonstrates robust performance in detecting small sea ice targets within large-scale satellite images and excels in high ice concentration regions. For path planning, the Any-Angle Path Planning on Grids algorithm is applied to simulate routes based on detected sea ice floes. The objective function incorporates the path length, number of ship turns, and sea ice risk value, enabling path planning under varying ice concentrations. By integrating detection and path planning, this work proposes a novel method to enhance navigational safety in polar regions. Full article

During polar navigation, icebreakers frequently encounter ice ridges, which can significantly reduce navigation efficiency and even pose threats to structural safety. Therefore, studying the ramming of ice ridges by the icebreaker is of great importance. In this study, the ice ridge is decoupled into the consolidated layer and the keel for modeling. The consolidated layer is simplified as layered ice, and an innovative hybrid empirical–numerical method is used to determine the icebreaking loads. For the keel, a failure model is developed using the Mohr–Coulomb criterion in combination with the effective stress principle, accounting for shear failure in porous media and incorporating both cohesion and internal friction angle. The ship is restricted to surge motion only. A comparative analysis with the model test results was conducted to assess the accuracy of the method, with the predicted ice resistance showing deviation of 9.85% in the consolidated ice area and 10.48% in the keel area. Ablation studies were conducted to investigate the effects of different ice ridge shapes, varying retreat distances, and different ship drafts on the performance of ramming the ice ridge. The proposed method can quickly and accurately calculate ice ridge loads and predict their motion responses, providing a suitable tool for on-site rapid navigability assessment and for the design of icebreakers. Full article

Structural safety is of utmost importance for polar icebreakers under both navigation and icebreaking conditions. In this research, the Palmgren–Miner linear cumulative damage theory is employed to evaluate the structural fatigue lifespan of polar icebreakers. A spectral analysis, incorporating the time distribution coefficients for three load conditions, is executed to assess the fatigue damage at typical hot spots during navigation. For icebreaking activities, the ship–ice interaction loads with time history are simulated using the discrete ice element method, taking into account five sub-operating conditions. This simulation is coupled with rainflow counting to evaluate the fatigue damage. The results show that the cumulative fatigue damage during navigation is much less than that during icebreaking. Additionally, shoulder areas suffer more serious fatigue damage during icebreaking as a result of the direct impact of broken ice. Consequently, both navigation and icebreaking conditions should be considered in the design of hull structures and the assessment of fatigue strength for polar icebreakers. Full article

A great ellipse route (GER), as one of the fundamental routes for ocean voyages, directly influences the actual voyage distance and the complexity of vessel maneuvering through the location and number of its waypoints. Against the backdrop of global warming, the melting of Arctic sea ice has accelerated the opening of the Arctic shipping route. This paper addresses the issue of how to reasonably segment and adopt rhumb line routes to approximate the GER in the special navigational environment of the Arctic. Using historical routes, recommended routes, and geospatial data that have passed through the Arctic shipping lane as constraints, this paper proposes a waypoint optimization model based on an adaptive hybrid particle swarm optimization-genetic algorithm (AHPSOGA). Additionally, by integrating Arctic remote sensing ice condition data and the Polar Operational Limit Assessment Risk Indexing System (POLARIS), a safety assessment model tailored for this route has been developed, enabling the quantification of sea ice risks and dynamic evaluation of segment safety. Experimental results indicate that the proposed waypoint optimization model reduces the number of waypoints and voyage distance compared to recommended routes and conventional shipping industry methods. Furthermore, the AHPSOGA algorithm achieves a 16.41% and 19.19% improvement in convergence speed compared to traditional GA and PSO algorithms, respectively. In terms of computational efficiency, the average runtime is improved by approximately 12.00% and 14.53%, respectively. The risk levels of each segment of the optimized route are comparable to those of the recommended Northeast Passage route. This study provides an effective theoretical foundation and technical support for intelligent planning and decision-making for Arctic shipping routes. Full article

The presence of sea ice threatens low ice-class vessels’ navigation safety in the Arctic, and traditional Navigation Risk Assessment Models based on sea ice parameters have been widely used to guide safe passages for ships operating in ice regions. However, these models mainly rely on empirical coefficients, and the accuracy of these models in identifying sea ice navigation risk remains insufficiently validated. Therefore, under the binary classification framework, this study used Automatic Identification System (AIS) data along the Northeast Passage (NEP) as positive samples, manual interpretation non-navigable data as negative samples, a total of 10 machine learning (ML) models were employed to capture the complex relationships between ice conditions and navigation risk for Polar Class (PC) 6 and Open Water (OW) vessels. The results showed that compared to traditional Navigation Risk Assessment Models, most of the 10 ML models exhibited significantly improved classification accuracy, which was especially pronounced when classifying samples of PC6 vessel. This study also revealed that the navigability of the East Siberian Sea (ESS) and the Vilkitsky Strait along the NEP is relatively poor, particularly during the month when sea ice melts and reforms, requiring special attention. The navigation risk output by ML models is strongly determined by sea ice thickness. These findings offer valuable insights for enhancing the safety and efficiency of Arctic maritime transport. Full article

In the context of global warming, polar tourism is developing rapidly, and the demand for polar cruise travel in the Northwest Passage continues to increase, while sea ice has long been a key factor limiting the development of polar cruise tourism. This study focuses on the operational risk of sea ice on cruise ships in the Northwest Passage (NWP), aiming to provide a scientific basis for ensuring the safety of cruise ship navigation and promoting the sustainable development of polar tourism. Based on ice data from 2015 to 2024, this study used the Polar Operational Limit Assessment Risk Indexing System (POLARIS) methodology recommended by the International Maritime Organization (IMO) to establish three scenarios for the route of ice class IC cruise ships: light ice, normal ice, and heavy ice. The navigable windows were systematically analyzed and critical waters along the route were identified. The results indicate that the navigable windows for IC ice-class cruise ships under light ice conditions are from mid-July to early December, while the navigable period under normal ice conditions is only from mid- to late September, and navigation is not possible under heavy ice conditions. The study identified Larsen Sound, Barrow Strait, Bellot Strait and Eastern Beaufort Sea as critical waters on the NWP cruise route. Among them, Larsen Sound and Eastern Beaufort Sea have a more prominent impact on voyage scheduling because their navigation weeks overlap less with other waters. This study provides a new idea for the risk assessment of polar cruise ships in ice regions. The research results can provide an important reference for the safe operation of polar cruise ships in the NWP and the decision-making of relevant parties. Full article

At present, sea ice remains a critical factor affecting the safety of vessel operations along the Northern Sea Route (NSR). However, inconsistencies between the navigability outcomes derived from the criteria for the admission of ships in the area of the Northern Sea Route (NSR criteria) and the polar operational limit assessment risk indexing system (POLARIS) methodology present challenges for navigational decision-making. This study aims to conduct a systematic comparison of the POLARIS methodology and the NSR criteria in evaluating the navigability of independently operating vessels classified as Arc4 to Arc9. Through comparative calculations of navigability and the navigability rates for six ice-class vessels across 27 districts using the two methods, this study reveals the consistencies and discrepancies in their navigability outcomes. Firstly, using the POLARIS methodology, the risk index outcome (RIO) is calculated for six ice-class vessels across 27 districts. For these districts, the navigability threshold is defined when 95% or more of the area exhibits an RIO greater than or equal to zero. Secondly, using the NSR criteria, navigability ratios for six ice-class vessels under varying ice conditions are evaluated. A navigability threshold is defined when 95% or more of the ice conditions in a district are classified as navigable. Finally, a quantitative comparison of the weekly navigability ratios obtained by the two methods is conducted to reveal the consistencies and discrepancies in the navigability outcomes of each ice-class vessel across different NSR districts. The results indicate that the consistency between the navigability outcomes of the two methods decreases with lower vessel ice classes, particularly in September and March. In general, the consistency of performance between the two methods in terms of navigability outcomes deteriorates as the vessel ice class decreases and ice conditions become more complex. This study provides a scientific foundation and data-based support for route planning and real-time decision-making in polar waters. Full article

Antarctic navigation encounters substantial challenges due to the dynamic and perilous characteristics of sea ice, which pose threats to vessel safety and operational efficiency. Existing risk assessment methodologies frequently lack real-time adaptability, while strategies for icebreaker convoys remain insufficiently quantified. To address these deficiencies, this study introduces an integrated framework that combines satellite-based sea ice monitoring, operational risk prediction, and icebreaker escort optimization. First, polar research routes and hydrographic conditions are systematically analyzed to enhance navigation planning. Second, a risk assessment system is developed by leveraging satellite-derived sea ice density and thickness data, facilitating a near-real-time hazard assessment (subject to satellite data latency) evaluation with 96.3% accuracy in ice type classification and a 15% improvement in risk prediction precision compared to conventional methods. Finally, kinematic safety criteria for icebreaker-escorted convoys are established, specifying speed-dependent distance thresholds to minimize collision risks, achieving optimal speeds of 1.4–2.3 knots for PC3-class vessels and 10–20% speed improvements for escorted vessels in cleared channels. The findings offer actionable insights into polar route optimization, risk mitigation, and safe ice navigation protocols, thereby directly supporting operational decision making in Antarctic waters. Full article

Wave propagation is impacted by the presence of ice floes. The influence of waves, on the other hand, causes ice floes to overlap and accumulate. In this paper, the interaction of ice floes and regular waves was simulated using the Finite Element Method. Firstly, natural ice floe fields were generated using the Python 3.10 programing language, with floe size distribution and randomness taken into consideration. Then, using the velocity inlet boundary wave generation method, regular simple harmonic waves were produced. The process where ice floes couple with waves was simulated with the Coupled Eulerian–Lagrangian (CEL) approach. Variations in wave height after passing through the ice floe field were investigated, and further research was conducted on the movement and fragmentation characteristics of ice floes. Simulations employing the Coupled Eulerian–Lagrangian (CEL) approach reveal that (1) ice floe motion exhibits periodic characteristics synchronized with incident wave periods; (2) wave height attenuation increases by 62–80% with rising ice concentration (70–90%); and (3) fragmentation predominantly occurs at wave trough phases due to flexural stress concentration. These findings quantitatively characterize wave–ice energy transfer mechanisms critical for polar navigation safety assessments. Full article

Aquatic floating debris detection is a key technological foundation for ecological monitoring and integrated water environment management. It holds substantial scientific and practical value in applications such as pollution source tracing, floating debris control, and maritime navigation safety. However, this field faces ongoing challenges due to water surface polarization. Reflections of polarized light produce intense glare, resulting in localized overexposure, detail loss, and geometric distortion in captured images. These optical artifacts severely impair the performance of conventional detection algorithms, increasing both false positives and missed detections. To overcome these imaging challenges in complex aquatic environments, we propose a novel YOLOv8-based detection framework with integrated polarized light suppression mechanisms. The framework consists of four key components: a fisheye distortion correction module, a polarization feature processing layer, a customized residual network with Squeeze-and-Excitation (SE) attention, and a cascaded pipeline for super-resolution reconstruction and deblurring. Additionally, we developed the PSF-IMG dataset (Polarized Surface Floats), which includes common floating debris types such as plastic bottles, bags, and foam boards. Extensive experiments demonstrate the network’s robustness in suppressing polarization artifacts and enhancing feature stability under dynamic optical conditions. Full article

The ballast tank is a critical system for LNG carriers, ensuring structural safety and stability during navigation. When LNG carriers navigate in polar regions, the ballast tank is prone to freezing, which will reduce the efficiency of ballast water circulation. Furthermore, the freezing process generates frost heaving forces that may damage the walls of the ballast tank, shorten the structure’s service life, and disrupt the ship’s normal operations. Therefore, analyzing the freezing process of ballast tanks is essential. This paper focuses on the ballast tank of a polar LNG carrier as the research subject. It assumes that the ballast water is fresh water with unchanging physical properties and takes into account the environmental conditions in polar regions. A numerical simulation model of the freezing process within the ballast tank is established. This study investigates the influence of various environmental parameters on the freezing process and determines the evolution of ice shape in relation to temperature field changes under different environmental conditions. The results indicate that as the ambient temperature decreases, the rate of temperature reduction at the ballast water level accelerates, resulting in a thicker ice layer formed by freezing. Additionally, as the seawater temperature decreases, the rate of temperature decline in the ballast water at the bulkhead is significantly accelerated, leading to an increased rate of ice shape evolution. Furthermore, a reduction in the height of the ballast water level enhances the heat transfer rate of the ballast water, which markedly increases the degree of freezing in the ballast water. Full article

Sea ice and the resulting loads are major safety concerns for vessels operating in ice-covered regions. This study presents a tailored sea ice and local ice load monitoring system specifically designed for polar cargo vessels. The system employs shipboard cameras coupled with a DeepLab v3+-based algorithm to achieve real-time ice concentration identification, demonstrating 90.68% accuracy when validated against historical Arctic Sea ice imagery. For structural load monitoring, we developed a hybrid methodology integrating numerical simulations, full-scale strain measurements, and classification society standards, enabling the precise evaluation of ice-induced structural responses. The system’s operational process is demonstrated through comprehensive case studies of characteristic ice collision scenarios. Furthermore, this system serves as an exemplary implementation of a navigation assistance framework for polar cargo vessels, offering both real-time operational guidance and long-term reference data for enhancing ice navigation safety. Full article

The unique challenges of polar ecosystems, coupled with the necessity for high-precision data, make Unmanned Aerial Vehicles (UAVs) an ideal tool for vegetation monitoring and conservation studies in Antarctica. This review draws on existing studies on Antarctic UAV vegetation mapping, focusing on their methodologies, including surveyed locations, flight guidelines, UAV specifications, sensor technologies, data processing techniques, and the use of vegetation indices. Despite the potential of established Machine-Learning (ML) classifiers such as Random Forest, K Nearest Neighbour, and Support Vector Machine, and gradient boosting in the semantic segmentation of UAV-captured images, there is a notable scarcity of research employing Deep Learning (DL) models in these extreme environments. While initial studies suggest that DL models could match or surpass the performance of established classifiers, even on small datasets, the integration of these advanced models into real-time navigation systems on UAVs remains underexplored. This paper evaluates the feasibility of deploying UAVs equipped with adaptive path-planning and real-time semantic segmentation capabilities, which could significantly enhance the efficiency and safety of mapping missions in Antarctica. This review discusses the technological and logistical constraints observed in previous studies and proposes directions for future research to optimise autonomous drone operations in harsh polar conditions. Full article

As Arctic sea ice continues to melt and global demand for clean energy rises, Russia’s Liquefied Natural Gas (LNG) exports via the Northern Sea Route (NSR) are rapidly increasing. To ensure the operational safety of LNG carriers and safeguard the economic interests of stakeholders, including shipowners, a thorough assessment of the navigability of various ice-class LNG carriers along this route is essential. This study collected Arctic ice condition data from 2014 to 2023 and applied the Polar Operational Limit Assessment Risk Indexing System (POLARIS) methodology to calculate the Risk Index Outcome (RIO) for LNG carriers with No Ice Class, Arc4, and Arc7 ice classifications in Arctic waters. A navigability threshold of 95% RIO ≥ 0 was established to define navigable windows, and critical waters were identified where sections of the route remain in hazardous or risky conditions year-round. The results indicate that for No Ice Class vessels, Arc4 vessels, and Arc7 vessels, the navigable windows for westbound Route 1 and Route 2 under light, normal, and heavy ice conditions range from 70 to 133 days, 70 to 365 days, and 70 to 365 days, respectively, while for eastbound Route 3, the navigable windows range from 0 to 84 days, 0 to 238 days, and 7 to 365 days, respectively. The critical waters affecting the navigability of No Ice Class vessels, Arc4 vessels, and Arc7 vessels are primarily located in the Kara Sea, Laptev Sea and East Siberian Sea. This study, using the POLARIS methodology, provides valuable insights into the navigability of LNG carriers with different ice classes along the NSR, supporting the development and utilization of Arctic energy and shipping routes while offering decision-making support for stakeholders involved in Arctic maritime operations. Full article

This paper addresses the challenges faced by icebreakers in polar environments, particularly the difficulty in sensing underwater ice formations when navigating through thick ice layers, which often results in suboptimal icebreaking effectiveness. To overcome these challenges, this paper introduces a novel underwater robot equipped with both sensing and icebreaking capabilities. We propose a path-planning method for icebreaking that leverages the synergistic capabilities of the genetic algorithm and safe particle swarm optimization (GA-SPSO). The GA-SPSO algorithm integrates the global search prowess of the particle swarm optimization with the local optimization strength of the genetic algorithm, enabling efficient and adaptive path planning in complex ice environments. The unmanned underwater vehicles (UUV)-assisted icebreaking approach developed here utilizes the UUV’s flexibility and high-precision environmental sensing to provide real-time optimization suggestions for icebreaker navigation paths. Simulation results demonstrate that the GA-SPSO algorithm not only effectively circumvents hazardous areas but also significantly reduces the energy consumption and operational time of icebreakers, thereby enhancing the safety and stability of navigation. When compared to the conventional safe particle swarm optimization (SPSO), our approach shows marked improvements in path length, convergence speed, and obstacle avoidance capabilities, significantly enhancing the success and efficiency of polar navigation missions. Full article