Non-parallel side-by-side ship interaction can generate strongly asymmetric and nonlinear hydrodynamic responses. This study investigates the effects of berthing angle, water depth, and lateral spacing on the surge force, sway force, and yaw moment of a KVLCC2 and an Aframax, and evaluates response-specific Kriging models within three conditional parameter groups: an angle group (CaseA), an angle–depth group (CaseH), and an angle–spacing group (CaseY). An available unsteady RANS–VOF response database with overset meshes was organized into 40 training samples and 10 held-out evaluation samples. Six single-output Kriging models were constructed for each group, giving 18 models in total, and were assessed using leave-one-out cross-validation and held-out prediction metrics. The three legacy CFD campaigns use different response-extraction targets: signed peak responses in CaseA, instantaneous responses at t=10 s in CaseH, and instantaneous responses at t=7 s in CaseY. Therefore, the groups are evaluated independently and cross-group accuracy comparisons are treated as descriptive rather than strictly like-for-like. CaseA shows the most consistent predictive performance (held-out R² approximately 0.96–1.00), whereas in CaseH only the Aframax surge force is reliable (R² approximately 1.00) and in CaseY the KVLCC2 surge force shows reasonable agreement (R² approximately 0.89), with several other responses producing negative R². The investigated depth range corresponds to moderate-to-large depth-to-draft ratios rather than classical shallow water, so the water-depth results are interpreted as finite-depth sensitivity within the numerical setup. The results demonstrate that Kriging reliability is both parameter-group-specific and response-specific, and model use should be restricted to validated responses within the sampled conditional domains.
Marine debris continues to pose a serious threat to marine ecosystems, biodiversity, and coastal economies, creating an urgent need for reliable and real-time detection mechanisms. Despite recent progress, conventional deep learning approaches often exhibit reduced performance in complex marine environments characterized by low visibility, occlusions, and inconsistent illumination. In this work, a hybrid quantum-inspired deep learning framework is proposed to address these challenges by integrating a Quantum ResNet-based feature encoding strategy with the YOLOv8 object detection architecture. The proposed model enhances feature representation by combining classical convolutional features with quantum-inspired transformations, implemented through angle encoding and parameterized quantum circuits. The framework was trained and evaluated on a dataset comprising 3,000 annotated images of marine debris, categorized into plastic, metal, glass, and fishing nets. Experimental results demonstrate that the proposed approach achieves a precision of 93.7%, a recall of 89.2%, and a mAP@0.5 of 91.3%, consistently outperforming the baseline YOLOv8n model by approximately 3%–4% in detection performance. Further analysis under challenging conditions, including Gaussian noise, motion blur, and underwater haze, reveals improved robustness, indicating that the incorporation of quantum-inspired feature transformations enhances the model’s discriminative capability. Overall, the findings suggest that integrating quantum-inspired representations with deep learning models provides a promising pathway for improving both accuracy and resilience in marine debris detection, thereby supporting the development of more effective intelligent environmental monitoring systems.
The joint optimization of vessel traffic organization and tugboat scheduling plays a critical role in improving the efficiency of port seaside operations. However, most existing studies are limited to single-channel environments or assume homogeneous tugboat fleets, whereas real-world ports are typically characterized by heterogeneous tugboat resources and, in some cases, complex multi-channel structures. To address this gap, this study investigates an integrated optimization problem combining vessel traffic organization with heterogeneous tugboat scheduling in a port with a dual one-way channel configuration. To capture the strong spatiotemporal coupling inherent in such operations, a bi-objective mixed-integer linear programming model is developed with the objectives of minimizing total weighted vessel waiting time and total tugboat fuel consumption. A tailored non-dominated sorting genetic algorithm incorporating an archive-guided adaptive multi-neighborhood search mechanism is proposed to efficiently solve the model. Computational experiments based on a northern Chinese seaport demonstrate that the proposed algorithm outperforms the CPLEX solver and several benchmark heuristic algorithms. The resulting Pareto solutions explicitly reveal the trade-off between vessel service efficiency and tugboat energy consumption, from which managerial implications are derived to support the formulation of coordinated scheduling strategies.
Using the set of 25 shipboard hydrographic transects across the northeastern part of the Barents Sea and the northern part of the Kara Sea obtained between 1995 and 2024, we have defined the existence of a surface current transporting Atlantic-origin water from the northern shore of Novaya Zemlya to the Kara Sea continental slope. It has been named the Keldysh Current after R/V “Akademik Mstislav Keldysh”, which performed numerous oceanographic surveys in the Arctic Ocean. The Keldysh Current is a part of the local complex system of Atlantic-origin surface, intermediate and bottom currents. It has a specific formation process and surface-advected pathway, which was not described before in dozens of papers focused on the circulation of water masses in this area. The Keldysh Current originates from the Barents Sea branch water (BSBW), which cools and sinks down in the northeastern part of the Barents Sea. Previously it was believed that the whole volume of BSBW loses contact with atmosphere in this area. In this paper, we demonstrate that the northern periphery of BSBW, which is freshened due to mixing with the Arctic surface water, remains at sea surface layer despite this cooling. This part of BSBW forms the surface-advected Keldysh Current with significantly higher temperatures and salinities, as compared to the adjacent surface waters. The Keldysh Current becomes isolated from the bottom-advected main flow of BSBW by cold dense water formed as a result of sea ice formation and salt ejection to the water column near Franz Joseph Land. However, due to dynamic entrainment, the Keldysh Current follows the flow of the BSBW, namely, northeastward along the northern shore of Novaya Zemlya, then northward along the eastern flank of the St. Anna Trough to the continental slope, then eastward along the continental slope towards the Laptev Sea. The Keldysh Current is order 50–100 km wide, 50–100 m deep, more than 1000 km long and transports ~0.4 Sv.
IntroductionAiming at the progressive failure and multi-domain coupling risks of battery management systems (BMS) for electric ships operating in marine environments, existing reliability evaluation methods fail to simultaneously characterize multi-state degradation evolution, sequential failure propagation, and common cause failure (CCF) coupling effects. This study constructs a quantitative reliability evaluation framework for ship BMS to support failure risk control and full-lifecycle operation and maintenance decision-making.MethodsA four-level multi-state fault tree model covering the cell, module, pack, and system layers is established, defining three operating states—intact, performance-degraded, and complete failure—to match the system failure evolution logic. An extended multi-group β-factor model is adopted to quantify CCF risks across four coupling domains: power supply, communication bus, thermal environment, and software. A modular dynamic fault tree (DFT) framework is proposed, with dedicated two-event and three-event DFT modules featuring sequential discrimination capability; an interval partitioning strategy is implemented to eliminate double-counting errors in sequential analysis. Closed-form analytical solutions are derived based on the inclusion–exclusion principle to avoid truncation errors inherent in numerical integration. A Multi-State continuous-time Markov chain (CTMC) model is built for analytical dynamic reliability assessment, with Monte Carlo simulation adopted for comparative verification of calculation results. Cross-validation of Birnbaum importance and Spearman rank correlation coefficients is conducted to distinguish inherent parameter risks from CCF-amplified secondary risks.ResultsValidation results demonstrate that the optimized sequential interval rule table eliminates double-counting defects of traditional algorithms, and all analytical expressions for system state probabilities satisfy the probability normalization axiom. The absolute error between the Multi-State CTMC analytical solutions and the closed-form solutions derived via the inclusion–exclusion principle remains negligible across the full-time horizon, with the relative error consistently approaching zero, verifying the mathematical consistency and accuracy of both solution frameworks. Compared with the independent failure assumption, CCF exhibits marked time heterogeneity: the probability of complete system failure at 1000 h is 10.1 times higher than that under the independent condition, while it decreases by 10.0% at 100000 h, an effect originating from the component screening mechanism. CCF reshapes component criticality rankings: the Birnbaum importance of bus-related basic events Total voltage detection and Total current detection increase by 159.9% and 168.8%, respectively, under CCF conditions, whereas that of the relay control fault rises by only 2.8%, establishing it as the core failure trigger throughout the entire service cycle. Parameter uncertainty analysis reveals that the 95% confidence interval of the system complete failure probability at 100000 h is [0.3737, 0.3971], which is 13.0% higher than the deterministic point estimate.DiscussionThe proposed framework addresses the limitation of traditional static fault trees in handling sequential and multi-state failures, and achieves compatibility between CCF modeling and hierarchical degradation logic. The modular DFT architecture balances computational accuracy and efficiency, making it applicable to reliability evaluation of complex marine electronic equipment. Comparative results between the Multi-State CTMC and closed-form approaches confirm that the proposed model is free of truncation errors, yielding bias-free reliability metrics over the entire mission duration. For engineering applications, global CCF monitoring is recommended in the early service stage; redundancy optimization and fault decoupling for bus-associated basic events should be prioritized in the medium stage; and independent redundancy design of relay units must be strengthened in the long-term service stage. Future research should incorporate component repair behaviors and cross-domain secondary CCF propagation mechanisms to improve model applicability further. This study provides a quantitative tool for the reliability design, risk assessment, and operation and maintenance strategy formulation of electric ship BMS.
China employs a diverse mix of marine environmental governance instruments to address complex marine environmental risks. Existing studies have primarily examined these instruments through public-policy typologies or focused on particular legal institutions, leaving their underlying administrative-law logics insufficiently explored. This study develops an administrative law-based framework drawing on red-, green-, and amber-light theories to examine the configuration of policy instruments in China’s marine environmental governance. Based on content analysis of 34 currently effective national-level policy documents, supplemented by normative legal analysis, the study identifies the relative prominence and internal structure of different governance instruments. The findings reveal a strongly red-light-oriented configuration. Red-light instruments account for 83.4% of coded references, while green-light and amber-light instruments account for 7.3% and 9.3%, respectively. Within the red-light category, ex post regulation accounts for 52.6% of coded references, exceeding ex ante prevention and process-oriented regulation. Green-light instruments are concentrated in fiscal support, whereas cost-internalization, risk-sharing, and professional environmental service mechanisms remain less prominent. Amber-light instruments are centered on information disclosure, while substantive public participation and expert consultation receive comparatively limited attention. The study argues that the predominance of red-light instruments is institutionally justified by the externalities, cumulative pressures, and potentially irreversible consequences associated with marine environmental risks. The central challenge lies in the internal configuration and functional coordination of the instrument mix. China’s marine environmental governance should therefore strengthen prevention-first and risk-oriented red-light regulation, develop conditional fiscal support and diversified responsibility sharing, and move amber-light instruments from disclosure-centered transparency toward substantive participation and administrative accountability. By combining policy-text content analysis with normative administrative law analysis, this study offers an administrative law-based perspective for assessing the legality and effectiveness of marine environmental governance. It also provides theoretical reference and practical implications for the broader study of government regulation.
Maritime shipping, responsible for ~3% of global carbon dioxide (CO2) emissions, must rapidly decarbonise to meet the International Maritime Organization’s target of net-zero greenhouse gas (GHG) emissions by 2050. Renewable-based ammonia has emerged as a leading near-zero-carbon fuel candidate; however, its reactive nitrogen (Nr) footprint remains poorly characterised. Across the ammonia marine fuel (AMF) value chain, Nr emissions arise as nitrogen oxides (NOx) and nitrous oxide (N2O) from combustion, and ammonia (NH3) losses to air (i.e., fugitive leaks and operational emissions) during production, storage, bunkering, and shipboard use, alongside episodic releases to water from spills and nitrogen-bearing effluent. This review synthesises current evidence on Nr emissions across the AMF value chain, examines plausible pathways through which their downstream transport, deposition, and fate may impact marine ecosystems and climate, and highlights key knowledge gaps. We show that resulting impacts—including altered marine productivity and community structure, eutrophication, biodiversity loss, and indirect N2O formation—are geographically dependent. Identical emissions can produce markedly different outcomes depending on whether deposition and other inputs occur in oligotrophic gyres, coral reefs, oxygen minimum zones, or already-stressed coastal and marginal seas. We also highlight potentially vulnerable regions where major shipping corridors overlap with nitrogen-sensitive marine ecosystems and Nr inputs may generate disproportionate ecological or climate impacts. Finally, we review mitigation measures and governance gaps across the AMF lifecycle. Realizing the full climate and environmental benefits of AMF will depend on integrated lifecycle accounting, stringent emissions controls, and policies that address nitrogen-cycle impacts and protect marine ecosystems alongside carbon reductions.
Ocean warming is rapidly altering marine ecosystems and is negatively affecting marine invertebrates, especially during their earlier life stages which often exhibit narrower physiological tolerances than adult conspecifics. The Caribbean king crab (Maguimithrax spinosissimus) is a species of interest for coral reef restoration in the Florida Keys and throughout the Caribbean due to its herbivorous grazing which can reduce macroalgae cover on patch reefs. However, the effects of thermal stress on king crab larval physiology and swimming behavior remain unknown. This study determined the effects of thermal stress on survival, metabolic performance, and geotactic vertical swimming behavior in both of the larval stages of M. spinosissimus under two temperature treatments: 28 °C (control) and 32 °C (elevated). Exposure to elevated temperature significantly reduced larval survival, with larvae in 32 °C being nearly three times more likely to die than cohorts in the control. In contrast, oxygen consumption did not differ between temperature treatments or larval stages, however larvae in the elevated treatment were observed to be more lethargic (alive with tail movement but no longer swimming) than larvae in the control. Elevated temperature also resulted in a reversal in the geotactic vertical swimming response. First stage larvae significantly swam downward at a faster rate than individuals in the control. In the absence of acclimatization, these results suggest that outplanted king crab populations may experience a reduction in larval supply and a reduced dispersal potential which could limit connectivity among local reef habitats after outplanting. This research has implications for coral reef restoration programs interested in stocking king crabs onto reefs as those efforts will rely on successful recruitment to sustain outplanted populations of M. spinosissimus.
Autonomous underwater gliders are pivotal for sustained ocean observations; however, maximizing effective data utilization requires highly standardized, end-to-end data processing workflows. Despite the availability of generic glider toolboxes, to our knowledge, no published open-source workflow currently provides an end-to-end, SeaExplorer-specific processing chain from vendor raw files to CF-compliant, quality-controlled outputs. Here, we present a Python-based pipeline that standardizes post-mission raw SeaExplorer data, applies automated Quality Control (QC) tests, and generates both diagnostic and user-oriented products designed for reproducible scientific use. This framework is designed to automate, under expert supervision, the entire processing chain, from raw data ingestion to the generation of CF-compliant NetCDF files. The proposed workflow implements a QC approach, adhering to the principle of data preservation over elimination, ensuring that original data are preserved for future scientific re-evaluation. The framework applies a suite of fourteen QC tests and produces two distinct outputs: a granular diagnostic file preserving detailed per-test flags for technical validation, and an aggregated file providing a single quality indicator per variable for immediate scientific use. The pipeline was demonstrated using data from two SeaExplorer missions conducted in La Palma (Canary Islands). Designed according to FAIR (Findable, Accessible, Interoperable, Reusable) principles, this tool supports reproducible data management and facilitates the integration of operational engineering data into scientific workflows.
Climate change induced warming of temperate coastal waters is expected to affect the biodiversity, community structure, seasonality and production in planktonic protist communities, and benefit heterotrophic taxa. We investigated long-term changes in the plankton protist community of the Outer Oslofjord by comparing two distinct periods across 15 years (2009–2011 vs. 2023–2024). Monthly 18S rRNA gene metabarcoding (V4 region) revealed dinoflagellates and diatoms as the dominating major taxonomic groups, with a 5.6-fold decrease in the dinoflagellate:diatom ratio and a 3.1-fold decrease in the heterotrophic dinoflagellate:phototrophic dinoflagellate ratio. These changes were primarily driven by a decrease in relative read abundance of the heterotrophic dinoflagellate genus Gyrodinium, and a widespread increase in the relative read abundances of diatoms (24 out of 27 ASVs with significant increase) between the time periods. Our results indicate that projected trends of heterotrophic protists profiting from changing oceanic conditions due to climate change, e.g. in temperate coastal waters, may not be the case for all coastal ecosystems.
Underwater ecosystems play a crucial role in maintaining marine biodiversity and global environmental sustainability. However, underwater monitoring and imaging is a highly challenging area of image processing, where images are severely degraded by haze, wavelength-dependent light absorption, color distortion, scattering, and noise, affecting marine monitoring, object detection, underwater navigation, and limited assessment of coral reefs, marine organisms, benthic habitats, and water quality. The conventional anisotropic diffusion filters do not effectively suppress noise and often fail to adequately preserve image edges and structural details. The manual selection of conductance parameters done in existing methods does not adequately account for the physical degradation mechanisms present in underwater environments. To address these limitations, a new framework, known as Rayleigh scattering-adapted diffusion anisotropic filter (RSADAF), has been proposed, which is a wavelength-aware physics-based diffusion framework that integrates a second-order partial differential equation (PDE) diffusion with the atmospheric scattering model (ASM) and Rayleigh scattering law. The adaptive conductance gradient parameter has been derived from ambient light estimation, and the dominant wavelength of the images has been derived from the CIE 1931 chromaticity model, giving spatial variation of diffusion and reducing local degradations. The second-order PDE formulation (two-stencil approach) preserves the structural information and mitigates staircase artifacts commonly observed in conventional diffusion schemes. Experimental evaluation on the EUVP and UIEB benchmark datasets demonstrates that the proposed approach achieves superior enhancement performance in terms of both full-reference and no-reference image quality metrics. The CIE 1931 wavelength-aware framework achieved a PSNR of 42.85 dB, SSIM of 0.967, UCIQE of 0.341, and BRISQUE of 21.99, outperforming conventional anisotropic diffusion and related enhancement methods. Visual results further confirm improved color restoration, contrast enhancement, edge preservation, and texture retention, offering an interpretable, computationally efficient, and physically meaningful alternative solution for underwater imaging applications.
The large yellow croaker (Larimichthys crocea) is an economically important marine fish in China. In order to explore the feasibility of inland saline-alkaline water aquaculture, this study systematically compared the effects on gonadal development of 14-month-old large yellow croaker, cultured in two different culture environments (offshore seawater in Ningde, and indoor saline-alkaline water in Ningxia). The evaluation was conducted on multiple parameters, including growth parameters, gonadosomatic index, sex ratio, gonadal histology, sex hormone levels (progesterone, estradiol, testosterone), and gonadal transcriptomes. The results showed no significant differences in growth and gonadal development between the two environments, with both ovaries at early developmental stages (phase I–III oocytes) and testes fully mature with abundant sperm. However, saline-alkaline water culture significantly reduced gonadal estradiol and testosterone levels in females, while increased progesterone levels in males. Transcriptomic analysis revealed a striking sex-specific response: females exhibited 8,744 differentially expressed genes (6,518 up-, 2,226 down-regulated), whereas males showed only two upregulated genes. GO and KEGG enrichment analyses of female differentially expressed genes indicated profound effects on energy metabolism, ovarian steroidogenesis, and cell cycle pathways. qRT-PCR validated the RNA-seq results. In conclusion, the saline-alkaline water environment in Ningxia does not impair gonadal development of large yellow croaker up to 14 months of age. Females undergo extensive transcriptomic reprogramming and hormonal changes, while males remain transcriptionally stable. These findings support the feasibility of the “marine fish inland farming” model, which alleviates pressure on coastal aquaculture, utilizes underappreciated saline-alkaline water resources, and promote coordinated regional development.
IntroductionModern armed conflicts at sea frequently trigger transboundary marine pollution, inflicting irreversible damage on regional ecological baselines; however, contemporary international law exhibits a pronounced normative deficit in regulating such harm.MethodsEmploying doctrinal legal analysis and systematic interpretation, this study deconstructs and maps core legal norms—including Article 35(3) of Protocol Additional I to the Geneva Conventions and Article 192 of the United Nations Convention on the Law of the Sea (UNCLOS)—alongside key judicial precedents to examine the normative interaction between International Humanitarian Law (IHL) and the law of the sea during wartime.ResultsThe findings reveal a structural misalignment between the permissive logic of military necessity and the protective logic anchored in obligations erga omnes. Under strict judicial interpretation, the threefold cumulative threshold of "widespread, long‑term and severe" presents an insurmountable evidentiary barrier, creating a critical accountability void in modern naval warfare characterised by grey‑zone operations and non‑state actors.DiscussionTo bridge these lacunae, this study formulates a collaborative governance framework grounded in Article 31(3)(c) of the Vienna Convention on the Law of Treaties (VCLT). At the macro level, it transposes the ecological vulnerability assessment criteria of Particularly Sensitive Sea Areas (PSSAs) into the IHL framework to reconstruct a legal mechanism for wartime special marine ecological protection zones, while drawing analogies from Articles 100 and 107 of UNCLOS to establish a cooperative universal visit‑and‑search mechanism targeting wartime environmental hazards. At the micro level, using the domestic legal integration of China's maritime rights enforcement as an illustrative case, it demonstrates a feasible pathway for sovereign states to fill international legal vacuums via domestic legislation. Ultimately, this research underscores that effective wartime marine environmental protection requires a paradigm shift in international law—transitioning from a pure "law of war regulation" toward a framework that actively safeguards common interests.
Marine biofouling poses a significant challenge for ocean engineering, with microbial biofilm formation being a critical prerequisite for macrofouling colonization. Traditional chemical antifouling strategies face increasing restrictions due to ecological toxicity and microbial resistance, creating an urgent demand for eco-friendly physical alternatives. This study aimed to systematically compare the wavelength-dependent effects of 405 nm and 450 nm antimicrobial blue light on Halomonas pacifica biofilm formation. Biofilms were constructed on glass slides and continuously irradiated at 50 mW/cm2 for 4 days (cumulative radiant exposure about 17,280 J/cm2), with a non-irradiated control. Total biomass was quantified by crystal violet staining, three-dimensional morphology was analyzed by white light interferometry, and bacterial viability was visualized by confocal laser scanning microscopy with DMAO/PI staining. The 450 nm treatment significantly reduced total biofilm biomass by 20.9% (P < 0.05), while 405 nm decreased biomass by 15.5% without statistical significance. In contrast, 405 nm strongly suppressed vertical growth, reducing average dry thickness by 77.2% (P < 0.01) and arithmetic mean roughness (Ra) by 55.0% (P < 0.01), whereas 450 nm optimized overall micromorphology by reducing maximum height (Sz, P < 0.05). Confocal imaging revealed dense continuous biofilms in controls, sparse fragmented structures in the 450 nm group, and intermediate density in the 405 nm group. These results indicate that the two wavelengths regulate biofilm formation through distinct mechanisms: 450 nm excels in inhibiting proliferation and reducing biomass, while 405 nm is superior in suppressing vertical thickening and minimizing attachment sites for subsequent macrofouling. This study demonstrates that 405 nm and 450 nm blue light are promising complementary strategies for eco-friendly marine antifouling.
Polychlorinated biphenyls (PCBs) are legacy pollutants associated with numerous adverse health effects. We synthesized PCB and health data collected over multiple decades and across six bottlenose dolphin (Tursiops spp.) populations, including a population near the heavily PCB-contaminated LCP Chemicals Site in Brunswick, Georgia, US. We used samples from males and juvenile females (n=396) to compare PCBs across populations, explore fine-scale spatial trends near the LCP Chemicals Site, and examine temporal trends for bottlenose dolphins sampled near Brunswick, and near Charleston, South Carolina. As females depurate a large portion of their PCB burden to their offspring, we also used the full sample set (n=580) to examine timing of decrease in blubber PCB burden in females as an indicator of first successful reproduction. Finally, we investigated associations of PCB concentrations with health indicators and thyroid hormones. We found that, although PCBs declined over time (3.54% and 5.01% decline per year for Brunswick and Charleston, respectively), concentrations are still extremely high in dolphins sampled near the LCP Chemicals Site. Geometric mean total PCBs combined over years for the Brunswick population was 236 (95% CI:198–280) μg/g lipid, but ranged from only 46 to 60 μg/g lipid for populations outside southern Georgia. At Brunswick, concentrations of summed congeners of Aroclor 1268, the commercial PCB mixture associated with LCP Chemicals Site operations but rarely used elsewhere, decreased with increasing sampling distance from the site. The median age for females classified to the sample group that had presumably successfully reproduced, indicated by decreased PCB concentration, was 20.4 years for Brunswick, compared with 11.6 years for other populations, suggesting that Brunswick females experience a number of failed attempts at breeding prior to their first success. Aroclor 1268 levels were associated with decreases in health indicators. Strongest associations were with alkaline phosphatase and albumin; for both, low measures have been associated with substantial increase in mortality risk for dolphins. In addition, all three thyroid hormones decreased with increasing Aroclor 1268. Previous human studies have found that hypothyroidism is associated with infertility, miscarriage, and poor fetal outcome, suggesting a likely pathway for PCB-related effects on reproduction in bottlenose dolphins.
IntroductionLongitudinal bending distortion is a major manufacturing problem in thin-walled T-beam stiffened structures used in large Pure Car and Truck Carrier (PCTC) ships. This study investigates the formation mechanism of welding distortion under different welding speeds and develops an induction-assisted dynamic thermal tensioning method for active distortion control.MethodsThermo-elasto-plastic finite element models were established to investigate the transient temperature field, plastic-zone evolution, residual stress distribution, and bending distortion of T-beams under high- and low-speed welding conditions. A temperature-dependent modified Johnson–Cook constitutive model for AH36 steel was developed from tensile tests at multiple temperatures and strain rates and implemented in ABAQUS through a UMAT subroutine. The constitutive model was validated against an independent AH36 butt-welding experiment. The effects of induction heating temperature and heating distance were then investigated numerically, followed by full-scale validation on a high-speed tandem submerged arc welding production line for large PCTC shipbuilding.ResultsLow-speed welding produced a larger plastic compression zone and greater longitudinal shrinkage strain accumulation because of the longer high-temperature residence time, resulting in more severe final longitudinal bending distortion. High-speed welding was mainly characterized by transient thermo-elastic sagging during the welding stage. Induction-assisted dynamic thermal tensioning effectively reduced longitudinal bending distortion by regulating the temperature field and longitudinal shrinkage in the web region. The best-performing induction heating conditions depended on the welding speed. In the full-scale production experiments, the selected induction heating parameters reduced the longitudinal bending distortion of the T-beam by up to 66.7%, and the observed regulation trends were consistent with the numerical results.
Rapid glacier retreat across the Arctic is transforming coastal landscapes and generating a growing number of previously non-existent aquatic habitats. In Svalbard, this process has led to the formation and expansion of coastal lagoons, including a substantial proportion of newly emerged paraglacial systems. Despite their increasing abundance, these environments remain poorly represented in Svalbard research and monitoring programs, and their ecological and biogeochemical significance is only beginning to be recognized. Herein we synthesize current knowledge of Svalbard coastal lagoons, integrating perspectives from geomorphology, hydrology, ecology, and biogeochemistry. We propose that these systems form a developmental continuum, ranging from newly formed, glacier-influenced basins to more stable and biologically structured lagoons. Observations from recently studied lagoon systems indicate strong environmental gradients, spatial heterogeneity and dynamic hydrological conditions that support diverse and evolving biological communities across trophic levels. Emerging evidence suggests that Arctic lagoons may function as biogeochemical reactors, including potential sources of methane, while also acting as accumulation zones for contaminants such as microplastics and persistent organic pollutants. At the same time, their ecological role – as biodiversity hotspots, transitional habitats, or stepping-stones for species redistribution – remains insufficiently understood. We identify key knowledge gaps related to lagoon formation, physical dynamics, ecosystem development, and greenhouse gas fluxes and outline a research roadmap for coordinated interdisciplinary investigations. We argue that Svalbard lagoons represent a rapidly expanding nature type that provides a unique opportunity to study ecosystem development under climate change and should be integrated into future Arctic research and assessment frameworks.
Robust and versatile detection of maritime vessels present in aerial images is a considerable challenge. While neural networks, particularly convolutional neural networks (CNNs), have revolutionized object detection and classification across many industries by enabling machines to learn complex patterns and features from large datasets, maritime vessel detection continues to pose challenges. One challenge is the limited quantity and diversity of training data required by AI/ML systems. In this paper, we present a system which uses multiple sensors in conjunction with salient data augmentation techniques and multiple convolutional neural network (CNN) architectures to test cross-sensor object detection resiliency. Our system is composed of six main subsystems: Image Acquisition, Image Processing, Data Augmentation, Model Creation, Object-of-Interest Detection and System Validation. We show that the data augmentation subsystem improves cross-sensor vessel detection precision by over 10%, paving the way for the design of similar systems which can prove robust across maritime applications, sensors and dataset sizes.
Reliable maritime object detection and tracking are essential for civilian ocean engineering applications, including vessel traffic monitoring, offshore infrastructure inspection, port management, marine debris surveillance, sea ice observation, hydrographic surveying, and environmental risk assessment. However, complex ocean environments present substantial challenges for automated perception systems because of dynamic sea surfaces, sea clutter, low SNRs, atmospheric interference, scale variation, occlusion, weak target signatures, and limited annotated datasets. This review examines recent advances in ocean-aware deep learning for maritime detection, segmentation, localization, and tracking using optical, infrared, Synthetic Aperture Radar (SAR), multibeam echosounder (MBES), satellite, airborne, unmanned aerial vehicle (UAV), unmanned surface vehicle (USV), and autonomous sensing data, together with Automatic Identification System (AIS) information. It synthesizes methodological developments in robust feature extraction, multi-scale representation, small-object detection, multimodal data fusion, weakly supervised learning, domain adaptation, and tracking under intermittent visibility. Existing limitations remain in sea-state annotation, cross-sensor benchmarking, long-term tracking datasets, operational validation, and real-time deployment. Future research should prioritize sea-state-aware architectures, physics-informed learning, SAR–optical–AIS–MBES–USV data fusion, synthetic data generation, lightweight implementation, and standardized evaluation protocols. These directions are critical for developing reliable civilian maritime monitoring systems under diverse sensor, weather, and ocean conditions.
