Ice Class Research Articles

Investigating coincident L- and S-band ASAR imagery over Arctic sea ice

Our investigation into coincident L- and S-band ASAR (airborne synthetic aperture radar) imagery explored Arctic sea ice separability in the Beaufort Sea, particularly in light of the imminent launch of the NASA-ISRO Synthetic Aperture Radar (NISAR) mission. Our research has revealed an improved capability to separate i) multi-year and first-year sea ice at the S-band imagery, as well as ii) a higher separability within first-year sea ice classes at L-band imagery. We have also reported that wind-roughened melt ponds show a distinct signature in the S-band. Importantly, our machine learning algorithm has achieved higher accuracy in sea ice classification at the S-band than the L-band. These findings have significant implications for the future of sea ice research and operations using SAR imagery from the NISAR mission.

Assessing the representation of Arctic sea ice and the marginal ice zone in ocean–sea ice reanalyses

Abstract. The recent development of data-assimilating reanalyses of the global ocean and sea ice enables a better understanding of the polar region dynamics and provides gridded descriptions of sea ice variables without temporal and spatial gaps. Here, we study the spatiotemporal variability of the Arctic sea ice area and thickness using the Global ocean Reanalysis Ensemble Product (GREP) produced and disseminated by the Copernicus Marine Service (CMS). GREP is compared and validated against the state-of-the-art regional reanalyses PIOMAS and TOPAZ, as well as observational datasets of sea ice concentration and thickness for the period 1993–2020. Our analysis presents pan-Arctic metrics but also emphasizes the different responses of ice classes, the marginal ice zone (MIZ), and pack ice to climate changes. This aspect is of primary importance since the MIZ accounts for an increasing percentage of the summer sea ice as a consequence of the Arctic warming and sea ice extent retreat, among other processes. Our results show that GREP provides reliable estimates of present-day and recent-past Arctic sea ice states and that the seasonal to interannual variability and linear trends in the MIZ area are properly reproduced, with the ensemble spread often being as broad as the uncertainty of the observational dataset. The analysis is complemented by an assessment of the average MIZ latitude and its northward migration in recent years, a further indicator of the Arctic sea ice decline. There is substantial agreement between GREP and reference datasets in the summer. Overall, GREP is an adequate tool for gaining an improved understanding of the Arctic sea ice, also in light of the expected warming and the Arctic transition to ice-free summers.

Какой должна быть мощность крупнотоннажного судна для работы в восточном секторе Арк­тики?

The study presents estimates of the required power capacity of superships intended for year-round operation in the Eastern sector of the Arctic, using the example of bow-first operation following an icebreaker in a narrow ice channel. The authors pay particular attention to the contour shapes, the going mode along the ice channel, as well as the vessel ice class. The study results prove that the use of large-tonnage vessels with a moderate icebreaking bow will require a noticeable increase in the propulsion power to ensure regular navigation at a speed that is effective for the operation of the maritime transport system.

A research on the Turkish shipyards in the Arctic: Opportunities and challenges

The Arctic region has been experiencing an extensive transformation and several economic opportunities have emerged due to the shrinking sea ice. While the Arctic Ocean has become more convenient for navigation, both Arctic and non-Arctic states have updated their Arctic policies according to recent developments. There has been a substantial increase in the number of studies studying three main Arctic sea routes: Northwest Passage (NWP), Northeast Passage (NEP), and Trans-Polar Sea Route (TSR). Albeit the existence of contradictory results, the interest in Arctic shipping presents a growing trend. The Turkish shipyards increasingly participate in tenders as well. While Çelik Tekne Shipyard stands out as the first Turkish shipyard to win the shipbuilding tender in accordance with polar conditions, a significant increase has been observed in the number of shipyards within the Arctic shipping tenders since 2018. In addition to Atlas and Akdeniz Shipyards, producing ice-class vehicles in accordance with the requirements of the Polar Code, it is possible to multiply examples from Beşiktaş Shipyard, which built ice class fuel ships, Sanmar Shipyard, which won the icebreaker tugboat tender, and Sefine and Kuzey Star Shipyards, which participated in the icebreaker tenders. Besides, the participation of Turkish shipyards as sole contractors in the Russian Arctic as of 2021 indicates their determination to become active actors in the Arctic shipping industry. Accordingly, this paper discusses the opportunities and challenges of Arctic shipping based on the Turkish case.

Past and future of the Arctic sea ice in High-Resolution Model Intercomparison Project (HighResMIP) climate models

Abstract. We examine the past and projected changes in Arctic sea ice properties in six climate models participating in the High-Resolution Model Intercomparison Project (HighResMIP) in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Within HighResMIP, each of the experiments is run using a reference resolution configuration (consistent with typical CMIP6 runs) and using higher-resolution configurations. The role of horizontal grid resolution in both the atmosphere model component and the ocean model component in reproducing past and future changes in the Arctic sea ice cover is analysed. Model outputs from the coupled historical (hist-1950) and future (highres-future) runs are used to describe the multi-model, multi-resolution representation of the Arctic sea ice and to evaluate the systematic differences (if any) that resolution enhancement causes. Our results indicate that there is not a strong relationship between the representation of sea ice cover and the ocean/atmosphere grids; the impact of horizontal resolution depends rather on the sea ice characteristic examined and the model used. However, the refinement of the ocean grid has a more prominent effect compared to the refinement of the atmospheric one, with eddy-permitting ocean configurations generally providing more realistic representations of sea ice area and sea ice edges. All models project substantial sea ice shrinking: the Arctic loses nearly 95 % of sea ice volume from 1950 to 2050. The model selection based on historical performance potentially improves the accuracy of the model projections and predicts that the Arctic will turn ice-free as early as 2047. Along with the overall sea ice loss, changes in the spatial structure of the total sea ice and its partition in ice classes are noticed: the marginal ice zone (MIZ) will dominate the ice cover by 2050, suggesting a shift to a new sea ice regime much closer to the current Antarctic sea ice conditions. The MIZ-dominated Arctic might drive development and modification of model physics and parameterizations in the new generation of general circulation models (GCMs).

Arctic Thin Ice Detection Using AMSR2 and FY-3C MWRI Radiometer Data

Thin ice with a thickness of less than half a meter produces strong salt and heat fluxes which affect deep water circulation and weather in the polar oceans. The identification of thin ice areas is essential for ship navigation. We have developed thin ice detection algorithms for the AMSR2 and FY-3C MWRI radiometer data over the Arctic Ocean. Thin ice (<20 cm) is detected based on the classification of the H-polarization 89–36-GHz gradient ratio (GR8936H) and the 36-GHz polarization ratio (PR36) signatures with a linear discriminant analysis (LDA) and thick ice restoration with GR3610H. The brightness temperature (TB) data are corrected for the atmospheric effects following an EUMETSAT OSI SAF correction method in sea ice concentration retrieval algorithms. The thin ice detection algorithms were trained and validated using MODIS ice thickness charts covering the Barents and Kara Seas. Thin ice detection is applied to swath TB datasets and the swath charts are compiled into a daily thin ice chart using 10 km pixel size for AMSR2 and 20 km for MWRI. On average, the likelihood of misclassifying thick ice as thin in the ATIDA2 daily charts is 7.0% and 42% for reverse misclassification. For the MWRI chart, these accuracy figures are 4% and 53%. A comparison of the MWRI chart to the AMSR2 chart showed a very high match (98%) for the thick ice class with SIC > 90% but only a 53% match for the thin ice class. These accuracy disagreements are due to the much coarser resolution of MWRI, which gives larger spatial averaging of TB signatures, and thus, less detection of thin ice. The comparison of the AMSR2 and MWRI charts with the SMOS sea ice thickness chart showed a rough match in the thin ice versus thick ice classification. The AMSR2 and MWRI daily thin ice charts aim to complement SAR data for various sea ice classification tasks.

On the data-driven investigation of factors affecting the need for icebreaker assistance in ice-covered waters

Merchant vessels often require icebreaker (IB) assistance to create safe pathways and improve efficiency when navigating in the Baltic Sea. Since IB resources are limited, an accurate estimation on the need for IB assistance is important. Whether IB assistance is needed depends on multiple factors. While practical experience from captains is naturally a source of valuable information for the decision on the need for IB assistance, systematic analysis of the reasoning is limited. The primary aim of this paper is to holistically investigate the influencing factors and their effect on estimating the need for IB assistance through data-driven techniques. Based on a comprehensive list of potential factors, different of data such as traffic history, environmental conditions, and ship specifications are gathered to present complex navigational scenarios. Each scenario is labeled by different navigation modes (independent navigation or IB assistance), laying the foundation for influencing factor identification and effect quantification. Logistic regression is applied to evaluate the effect of the factors on the need for IB assistance. The results show that the impact of the factors is diverse, and ridged ice concentration has the most significant impact. The effectiveness of identified factors is measured by comparing it to that of the factors that have been implemented by the existing studies (e.g., the combination of ice concentration, thickness, and ship ice class, or only ship speed). By considering the factors in this study, the classification performance can be improved by at least 5.6%. The findings in this paper can provide insights for predicting IB workloads and optimizing IB resources and have the potential to support the development of an intelligent decision-support system for winter navigation.

Построение безопасных коридоров судоходства в морях арктического шельфа на основе использования алгоритмов глубокого обучения

A comparative analysis of interannual changes in the ice coverage of the Pechora and the Kara Seas has been conducted based on the information of open sources (satellite observations) gathered by the Arctic and Antarctic Research Institute and the open dataset with mapped ice conditions ArcticDEM. The following problems of the study have been solved: the analysis of the most common approaches to building a forecast based on the analysis of ice conditions has been conducted; a deep learning algorithm to solve the problem of analysis of ice fields has been developed and tested; a medium-term forecast of the condition of ice fields in the area of the Pechora and the Kara Seas has been prepared based on the approbation model example; the obtained results have been analyzed and processed. In the course of study, an algorithm of automated mapping of ice conditions based on the satellite imagery data has been developed; the possibilities of its application to forecast ice conditions automatically, i.e., without using a manmade mapping, have been described. It has been demonstrated that the use of images based on multiple spectral bands and the combination of data from different satellites can minimize the influence of clouds and weather conditions. The model gave the real forecasting accuracy for a period of 10–14 weeks equal to 49–53 % for the Barents (Pechora) and the Kara Seas of 2018–2021. In case the model was fine-tuned and included data from the Barents (Pechora) and Kara Seas before 2018 in the training sample, the accuracy on the data after 2018 increased up to 52–56 %. The feature of the model is its ability to operate with different classes of ice and precisely determine its amount. The developed method increases the efficiency of operational control over the ice conditions in the Arctic seas. Safe navigation routes for shipping transport in the Pechora Sea have been modeled.

Risk assessment of ice-class-based navigation in Arctic: a case study in the Vilkitsky Strait

Over the past four decades, the decrease in Arctic sea ice has driven significant growth in vessel traffic through the Arctic passages. A precise and quantitative sea ice risk assessment would be the cornerstone of route planning for Arctic ships. Taking the chokepoint of Arctic Northeast Passage, the Vilkitsky Strait, as an example, the temporal and spatial characteristics of ice conditions in the strait were analyzed based on simulated ice thickness and observed sea ice concentration data from 2012 to 2021. Additionally, navigation risk in the strait was assessed based on the Polar Operational Limit Assessment Risk Indexing System (POLARIS). The results showed that the strait experienced 100% sea ice coverage from December to May, peaking in thickness of nearly 2 m in May, receding starting in June, and presenting ice-free passages by August and September. A significant interannual variability is evident in the timing of sea ice melting and freezing. Moreover, the average navigability of the strait was 365 days for vessels with an ice class of PC3, 72 days for PC6 and fewer than 64 days for those below B1. Remarkably, in 2013, 2014, and 2021, vessels below PC5 had less than 30 navigable days in the strait.

Methodology for zoning the Northern Sea Route water area during salvage and rescue operations and oil spill response

A methodology for assessing the possibility of ensuring salvage and rescue operations and oil and oil product spills response throughout the entire water area of the Northern Sea Route has been proposed. From 2024, it is planned to systematically develop year-round navigation along the Northern Sea Route, which will be associated with the need to ensure safety. At the moment, this possibility is severely limited due to the lack of multifunctional vessels of high ice class and technical means for spills response in ices. The methodological basis for determining the response time to marine oil spills in the Polar waters is laid down in the Polar Code, documents of the Maritime Safety Committee of the International Maritime Organization and documents of the Arctic Council, but their application is determined only by the hydrometeorological and geographical conditions at the place of the accident liquidation. Despite their broad and practical focus, the proposed approaches are only of a general methodological nature, which does not take into account the peculiarities of navigation in the waters of the Northern Sea Route, its length and zoning. The developed methodology largely overcomes these limitations and allows, at a qualitative level, to zone the waters of the Northern Sea Route according to three classification criteria. Two model examples are provided in the paper. The first example assumes that shipping occurs only in the western part of the Northern Sea Route, i. e. in the Kara Sea, the Ob Bay and the Yenisei Gulf, and in the eastern sector, shipping is completely absent; the second example assumes that navigation occurs throughout the entire water area. For each option under study, the entire water area is zoned according to the level of readiness, which is assessed as “high”, “medium” and “low” and depends on the presence of icebreakers and multifunctional vessels in the area. In the future, this methodology can be supplemented by an assessment of other factors, such as the influence of hydrometeorological conditions, ice conditions, navigation risks, forecasting the intensity of shipping and the selection of the necessary technical means for oil and petroleum product spills response.

Sea Ice Examination for Ice Class Ships visiting Horseshoe Island, Antarctica, Using MODIS in 2000-2022

Sea ice has a significant impact on numerous areas, ranging from the reflection of the sun rays back on the albedo scale, to spurring intense phytoplankton blooms that help maintain the marine ecosystem and making the navigation of some maritime routes challenging. The formation of sea ice in the Southern Ocean affects maritime logistics and scientific operations on Antarctica, especially on the Antarctic Peninsula, which hosts half of the scientific stations. Ships needed to supply British and Turkish scientific bases on Horseshoe Island in the southernmost part of the Antarctic Peninsula are in high demand. Therefore, the analysis of the oldest trends of sea ice that affect maritime operations is crucial. The goal of the study was to examine the formation of sea ice, and especially ice-free days, by using images collected between 2000 and 2022 by over 8000 NASA’s Terra/MODIS Moderate Resolution Imaging Spectroradiometer instruments (MODIS). An analysis of maritime traffic gives a better understanding of maritime operation needs and usage of natural ports, including bays within the research area. Therefore, the study focused on four sites: western approach to Horseshoe Island, Sally Cove (hosting a British station), Lystad Bay (hosting a Turkish station) and Gaul Cove. The results indicate that there has been no multiyear sea ice around Horseshoe Island. The most suitable months for the safe navigation of any type of ship in the area, due to the greatest number of ice-free days, are March, February, April and January. The study reveals that, in accordance with the Polar Code, lower ice class ships are required for safe navigation during scientific expeditions to Horseshoe Island. Also, as the average number of days with clear skies was 38, and average cloudiness very high, the use of optical satellites for long-term monitoring studies on Horseshoe Island is not recommended.

Effect of ice class to vessel fuel consumption based on real-life MRV data

Ice classed ships have specially designed, reinforced hulls and large engines, which may influence open-water fuel efficiency. Ice classification typically requires minimum engine power limit, possibly leading to an over-sized engine for open water operation. Most of the existing studies of energy efficiency of ice classed ships assume that these vessels consume more fuel also in open water conditions than conventional ships. In this work we analysed the EU Monitoring, Reporting and Verification database to understand the differences of main engine size, light ship mass, payload capacity and real-life reported and verified annual mean fuel consumption between ice classed ships and those without ice class using statistical methods. Ice classed ships were found to have on average 11% more hull mass, 13% more main engine power and 13% less deadweight capacity than ships without ice class, but some vessel types had inversed results. Also, ice class does not predict increased fuel consumption for all vessel types. In addition, according to the Automatic Identification System data, about 47% of vessels with reported ice class did not sail in ice covered areas during 2018–2022. These findings should open the discussion for more precise relief mechanisms of emission trading systems granted for ice classed vessels.

Experimental and numerical investigation of the propeller thrust reduction in bollard pull condition

The polar ships are often in bollard pull condition, which is prone to induce propeller cavitation and cause thrust reduction, weakening the ship’s ice-breaking ability. Based on the model tests and numerical simulations, this paper aims to investigate the propeller thrust reduction in the bollard pull condition. Firstly, the test of a self-designed ice class propeller under different cavitation numbers is carried out. The thrust reduction phenomenon is successfully captured and the hydrodynamic characteristics are obtained. Subsequently, the simulation based on Star-CCM+ is performed. It is found that the propeller thrust decreases almost linearly after the cavitation number reaches a certain threshold. When the cavitation number is equal to 0.25, the thrust decreases to 38.1% of that in the open water condition. By analyzing the mechanism of thrust reduction, the main reason is recognized that the average pressure of the blade face decreases greatly due to the influence of the cavitation on the blade back.

Probabilistic analysis of operational ice damage for Polar class vessels using full-scale data

To ensure the safety of maritime operations in polar waters, the IMO enforced the International Code for Ships Operating in Polar Waters (Polar Code) in 2017. To address ice navigation related risks, the Polar Code refers to a set of guidelines known as the Polar Operational Limit Assessment Risk Indexing System (POLARIS). Following POLARIS, operational limits for ice navigation are defined based on the Risk Index Outcome (RIO) value, which takes into account the prevailing ice conditions and the ice class of a ship.Recent studies indicate that the POLARIS guidelines are well-founded. However, no direct relationship between RIO values and the probability of an ice-induced hull structural damage has been established. To enable a more accurate analysis of ice navigation risks, this article addresses this issue by (i) relating measured ice-induced loads to RIO values corresponding to the ice conditions in which the loads were measured, (ii) calculating the load limits for plastic deformation and rupture of the ice belt of hull structures representing different ice classes, and (iii) defining the probability of structural damage for different load limits. The study utilizes long-term full-scale ice load measurements carried out onboard Polar Supply and Research Vessel (PSRV) S.A. Agulhas II in the Antarctic Ocean. The load limits were calculated for ice class standards, PC3, PC4, PC5, PC6, and PC7 in accordance with the Unified Requirements of the International Association of Classification Societies (IACS).On a general level, the results are consistent with earlier findings indicating that the POLARIS guidelines are well-founded. If a ship operates mainly at ‘normal operation’ level, the probability for fracture at hull are at probability levels of 10-3 and 10-4 for ice classes PC3 to PC5. The probability levels for PC6 and PC7 are higher that is possibly a result from conservative load probability distributions. When the portion of operations at ‘special consideration’ level becomes significant, the probability of fracture at the hull increases significantly. However, large ice thicknesses and the largest load magnitudes may be associated with positive RIO values. Some inconsistencies are recognized, and the uncertainty and limitations of the analysis are discussed.

Review of schemes for transport-geographical zoning of the Arctic water area

The retrospective and modern schemes for geographic and transport zoning of the Arctic and the Northern Sea Route are examined. The historical research method, which consists in identifying and analyzing documented facts, historical processes and their logic in terms of clarifying development, is used. There are several stages in the formation of zones and areas in the waters of the Arctic seas. The time period chosen for the review is from the beginning of the 19th century to the present in chronological order. International relations, national legal and natural conditions, and country characteristics are taken into account. The evolution of the organizational structure for managing the operation of the transport system of the Northern Sea Route, from the creation of the first administration to the present day, is considered. The countries of the Arctic Council have not yet developed a uniform approach to such tasks as the classification of ice (ice conditions) and requirements for the design of a vessel (ship ice class). Most countries use the definitions from the Polar Code. Individual countries apply their own rules and classification. The Russian Federation, for example, when choosing criteria for the admission of ships, uses both the national classification (Arc4-Arc9) and the Baltic one (Ice1-Ice3), while recognizing the ice classes of ships according to the International Association of Classification Societies. The results of a comparison of the Arctic Council countries on the presence of signs for development of transport-geographical zoning and navigation management in the Polar waters are presented. In conclusion, a list of tasks, the solution of which will contribute to the future transition from geographical to transport zoning of the Northern Sea Route and the Polar waters as a whole, is provided.

Route optimization for vessels in ice: Investigating operational implications of the carbon intensity indicator regulation

The International Maritime Organization has adopted the Carbon Intensity Indicator (CII) regulation to promote decarbonization of shipping operations. The CII regulation includes specific treatment for vessels sailing in ice, which allows the time spent in ice, the associated emissions and transport work, to be excluded from the reported annual CII. The current study investigates the implications and possible side effects of this exemption in all ice-covered waters. A proposed model integrates the CII regulation into a route optimization tool for vessels in ice. The research decomposes the regulation from evaluating an annual CII value to monitoring an instantaneous CII value over a unit distance. A ship performance model is used to estimate resistance, powering, and fuel consumption. A graph-based pathfinding method is applied to find optimal routes and speeds for the vessel. A hypothetical bulk carrier with ice class 1A Super operating in the Canadian Arctic is considered as a case study. The Polar Operational Limit Assessment Risk Indexing System is applied to promote safe operations in ice. The demonstrations explore route optimization with and without CII considerations, including the exemption for ships sailing ice. The results show that the CII regulation promotes reduced speeds to curb fuel consumption and carbon emissions. The findings also indicate that the exemption for sailing in ice conditions influences routing decisions with results that are contrary to the intent of the regulation. This research provides a tool to support ship operators with voyage planning and policy-makers in evaluating the impact of the CII regulation.

On the modelling chain for production loss assessment for wind turbines in cold climates

This paper presents results from a validation study of the EMD-WRF On Demand (OD) ICING modelling chain for production loss assessment for wind turbines in cold climates. The emphasis has been on validating the modelled seasonal instrumental icing using 29 meteorological masts and 49 seasons. The observed instrumental icing was extracted from wind data from meteorological masts using windPRO. The modelled results were compared to the observed instrumental icing and the sensitivity of the industry threshold limit of 10 g (for a 1-m-high standard cylinder) was evaluated. The study showed very good performance of the modelling chain and confirmed the industry threshold limit of 10 g (for a 1-m-high standard cylinder) to be the best match. Furthermore, the IEA Task 19 Ice Class system for translating modelling icing into a production loss was evaluated, and it was found that using meteorological icing is the desired and recommended solution.

Coupled Lattice Boltzmann and Discrete Element Simulations of Ship-Ice Interactions

Evaluating ice loads acting on ships is essential for the safety of ships navigating in ice-covered seas. In this study, we develop a CFD method to handle ship, ice, and fluid interaction. The lattice Boltzmann method, capable of large-scale calculations, is applied to the simulation of free-surface fluids. The ice motion is computed by solving the equations of motion of a rigid body, and the discrete element method models the ice-ice and ice-ship contact interactions. A momentum exchange scheme couples the lattice Boltzmann method and particle-based rigid body simulation. We introduce tree-based adaptive mesh refinement and multiple GPU computing to improve grid resolution and computational time. The proposed method is applied to model scale simulations of ship navigation in a brash ice channel. Simulations were performed for various conditions with different ice concentrations and ship velocities, and we observed that ice resistance increased with the ice concentration and the ship velocity increased. The ice motions and resistances obtained from our simulations are reasonable compared to model equations of Finnish-Swedish ice class rules (FSICR) and numerical analyses of a previous study.

Sea ice surface type classification of ICESat-2 ATL07 data by using data-driven machine learning model: Ross Sea, Antarctic as an example

The ICESat-2 (IS2) ATL07 sea ice height product provides precise and accurate measurements of sea ice height for the polar regions. Although the original ATL07 product classifies the sea ice surface into snow-covered ice and open water (dark leads and specular leads), it has two critical issues: (1) it does not distinguish thin ice (gray ice) from thick/snow-covered ice or open water and (2) it involves uncertainties in the dark lead determination. To address these issues and obtain more accurate lead fraction and freeboard estimation, in this study, we assess a data-driven machine learning approach for sea ice surface type classification from the ATL07 product. A total of 17 IS2 tracks covering the Ross Sea in February, March, September, October, and November 2019 are used in this study. For training and testing the neural network (NN) models, we label the ATL07 data into three surface types: thick/snow-covered sea ice, thin/gray sea ice, and open water based on the coincident Sentinel-2 optical images. We use six variables from the ATL07 data: background rate, photon rate, relative surface height, width of height distribution, number of laser pulses, and difference in mean and median height, with the first three variables found to be the most significant in determining surface types. Our spatiotemporal test shows that the NN models can be applied to the ATL07 dataset with ∼99% accuracy in the Ross Sea, and the beam test shows that the difference in the accuracy for three beams is negligible. While the current ATL07 product captures only ∼5% of thin ice and ∼ 81% of open water correctly, our NN models capture ∼90% of both open water and thin ice leads successfully. When we qualitatively assess the surface classification of the NN models by using the coincident optical and radar images, our NN models do not show significant misclassification issues both in the daytime and nighttime and both in the winter and summer seasons. Compared to the IS2 ATL10 sea ice freeboard product, the ability of our NN model to separate thin ice and open water from snow-covered/thick ice is significant in freeboard estimation, especially for winter and highly packed sea ice areas. Open water and thin ice classes also improve mapping lead fraction and floe size distribution.

A Numerical Prediction of the Resistance of Bulk Carriers in Brash Ice Channels

Ship resistance increases significantly when navigating a brash ice channel. In this study, the numerical method is applied to predict the full-scale ship resistance of bulk carriers in brash ice channels. The viscous flow computational fluid dynamics (CFD) solver was coupled with the discrete element method (DEM) to establish the brash ice model. The Euler multiphase flow’s volume of fluid (VOF) model was applied to simulate the interaction between the ship and water. The ship–brash ice interaction was simulated. Predictions of ships’ total resistance based on the numerical method and the Finnish Swedish ice class rules (FSICR) method were compared with the experimental results carried out in Hamburg Ship Model Basin (HSVA) ice tank. The numerical resistance shows a good agreement with the HSVA experiment reports and a better performance than the FSICR method. The present study shows that the numerical method could provide reasonable and practical ice resistance predictions for engineering applications.