Journal of Marine Science and Engineering doi: 10.3390/jmse14111059

Authors: Haitao Wang Mengliang Jiao Weimin Huang Linxu Huang Shouwen Zhang

The Indonesian Throughflow (ITF) is a critical conduit connecting the tropical western Pacific Ocean and the Indian Ocean, constituting an essential component of the global ocean circulation and exerting a significant influence on its large-scale balance. Under the backdrop of global warming, both the magnitude of ITF transport and its relationships with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are expected to undergo substantial changes. Using the SODA3.15.2 reanalysis as an observational benchmark, this study evaluates the ability of 14 CMIP6 models to simulate ITF volume transport. Following a systematic performance assessment, four poorly performing models were excluded, and the remaining 10-model ensemble was employed to construct a multi-model ensemble mean (MME). The MME is then employed to investigate the long-term trends in ITF transport during the historical period (1850–2014) and under two future emissions scenarios, SSP2-4.5 and SSP5-8.5 (2015–2100). During the historical period, ITF transport exhibits a transition from a weak strengthening to a weak weakening trend around 1934–1935, detected by both the sliding t-test and the Pettitt test, with relatively modest overall change. Under SSP2-4.5 and SSP5-8.5 scenarios, ITF transport weakens at rates of 0.318 Sv decade−1 and 0.466 Sv decade−1, respectively, with projected declines of approximately 3 Sv (27%) and 4 Sv (36%) by 2100. Reductions during boreal winter and spring exceed those in summer, indicating a pronounced seasonal asymmetry in the ITF response to future warming. The interannual variability of ITF is predominantly driven by ENSO, while the IOD also exerts an independent yet weaker modulating influence.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111058

Authors: Baiming Chen Cui Wang Shang Jiang

This study examines equifinality and compensatory calibration in hydrodynamic modelling of semi-enclosed coastal systems, using the Xiamen–Kinmen coastal waters as a representative tide-dominated case. A progressive diagnostic framework based on the normalized marginal contribution rate (MCR) was developed to quantify the relative effects of open-boundary forcing, spatially heterogeneous bottom friction, and atmospheric forcing within a depth-averaged barotropic model. Multi-metric validation against in situ water-level and depth-averaged current observations shows that the physical consistency of open-boundary forcing is the dominant control on model skill, particularly in reducing systematic elevation bias within the embayment. Bottom-friction parameterization produces more localized and site-dependent improvements, mainly affecting the spatial structure of current speed and direction under geomorphological constraints. Atmospheric forcing contributes only limited marginal gains during the study period, with modest directional corrections under weaker tidal conditions. These results indicate that hydrodynamic optimization for semi-enclosed bays should prioritize boundary consistency before local parameter tuning, thereby reducing compensatory calibration risk and improving physical interpretability. Remaining localized velocity errors in estuaries and high-curvature channels highlight the limitations of the depth-averaged barotropic assumption, under which density-driven baroclinic flows and vertical secondary circulations cannot be explicitly resolved. The proposed framework provides a reproducible approach for diagnosing and optimizing nearshore hydrodynamic models.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111057

Authors: Peiyuan Wang Jianghua Sui Shiye Wang

Diesel engine emissions remain a concern because of their environmental and health impacts. Homogeneous charge compression ignition experiments on low-speed two-stroke marine diesel engines are costly, risky, and limited by scarce transient data. To address this issue, a one-dimensional/zero-dimensional AVL BOOST-ANSYS CHEMKIN coupled framework was established for an MAN B&W 6S50MC low-speed two-stroke marine diesel engine, providing a reasonable approach under data-limited conditions. The framework provided key initial conditions for detailed chemical-kinetic analysis and was used to examine methyl decanoate (MD)/di-n-butyl ether (DBE) blends with 0–20% DBE. The results indicate that DBE addition alters the balance between aromatic growth and oxidative removal and enhances low-temperature chain branching, while the increased peak temperature raises nitrogen oxides (NOX) emissions. To relate these mechanistic results to engineering evaluation, the weighting scheme of the IMO NOX Technical Code 2008 test cycle was introduced. Pyrene and its isomers and NOX were treated by weighted normalization, followed by Pareto analysis and TOPSIS methods. MD90 (90 vol% MD and 10 vol% DBE) showed the best emissions trade-off over a wide range of weighting settings, which may provide useful guidance for optimizing oxygenated fuel blending ratios.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111056

Authors: Jun-Seong Kim

Main engine load varies continuously, whereas onboard carbon capture columns are installed with fixed capacities. For liquefied natural gas (LNG)-fueled ships, this mismatch between design and operation makes off-design robustness, rather than nominal-point performance, the governing sizing criterion. This study developed a variable-load design window for onboard monoethanolamine CO2 capture and evaluated a dual-loop organic Rankine cycle (ORC) as a secondary thermal integration option. A verified process model was applied to a 5 × 5 design–operating matrix (D50–D90/O50–O90). The mismatch was strongly asymmetric. When operating load did not exceed design load, capture rate remained near 90%; under overload, absorber treated only the design-point-equivalent exhaust-gas flow, causing capture performance to deteriorate rapidly. The mean CO2 avoided rate increased from 57.4% at D50 to 70.4% at D90, while absorber diameter increased from 3.23 to 4.06 m. D70 emerged as the balanced option for low- to medium-load services, D80 marked the transition before full robustness, and D90 was robustness-oriented for frequent high-load operation. The ORC recovered 104–185 kW net power and supplied 231–410 kW LNG-side heating. Results support capacity selection before ORC application; CO2 liquefaction and storage, voyage-weighted validation, and shipboard ORC feasibility remain outside the present scope.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111055

Authors: Žilvinas Vainoras Sergejus Lebedevas

The sustainable development of all economic sectors, including transport, requires decarbonization approaches that reduce greenhouse-gas emissions while preserving operational viability. This article develops a segment-based preliminary multi-criteria framework for evaluating the rational applicability of decarbonization technologies to commercial fishing vessels and demonstrates it for existing medium-to-large trawlers. The central premise is that decarbonization technologies cannot be ranked universally for the whole fishing fleet because vessel type, fishing gear, operating cycle, autonomy, onboard energy demand, and port dependence strongly affect practical applicability. Ten alternatives are assessed: sustainable drop-in biofuels/biodiesel/HVO (Hydrotreated Vegetable Oil), LNG/BioLNG/LBG, methanol, hydrogen fuel cells, ammonia, hybrid systems, operational measures, hull-form or hydrodynamic modifications, waste heat recovery and wind-assisted propulsion. Seven benefit-type criteria are combined using trawler-specific Rank-Order Centroid weights, Simple Additive Weighting, and a dynamic rationality extension for 2026, 2030, 2040, and 2050. The 2026 baseline results place operational measures and sustainable drop-in biofuel/HVO pathways in the leading practical group, while hydrogen and ammonia remain weak because of storage, safety, infrastructure, cost, and integration constraints. By 2050, a mixed long-term group emerges where HVO, LNG/BioLNG/LBG, methanol, ammonia, and hydrogen are all relevant, with no single dominant alternative. The framework supports early-stage screening before vessel-specific LCA, LCCA, CFD, safety assessment, and retrofit or newbuild design. Although this methodological approach was demonstrated for existing medium-to-large trawlers, the authors believe that it can be adapted for retrofit cases, other fishing vessel segments, and other types of seagoing vessels.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111054

Authors: Darius Jarmalavičius Gintautas Žilinskas Rasa Janušaitė Donatas Pupienis

Beach nourishment, as one of the most widely and effectively used coastal management measures recently, inevitably changes the coastal environment. This study aims to assess how the coastal profile is transformed during repeated beach nourishments with coarser-than-native sand in the Palanga recreational zone, Lithuania, Baltic Sea, using field survey data from the last three decades. When the granulometric composition of the sand is artificially changed during nourishment, the beach adapts to environmental changes by adjusting its morphometric parameters. These changes can be perceived as an intensification of coastal erosion, and, at the same time, a failure of the project. However, the results of this study show that these changes are associated with the transformation of the beach towards a morphologically adjusted state under the new sediment characteristics. In the Palanga case, the coarser-than-native sand used for nourishment led to narrower and steeper beaches compared to the pre-nourishment beaches composed of finer sand, and these characteristics persisted five years after nourishment. Therefore, the wide and low-slope beaches created during beach nourishment could not maintain the formed morphometric features with the coarser sand. For this reason, when implementing a replenishment project, it is important to predict the cross-shore profile that will develop for a given grain-size composition and quantity of the nourishment sand.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111053

Authors: Yongtao Zhang Haifeng Liu Yang Mo Peishuai Chen Fuquan Ji Ran Gao

Coral reef rudstone (CRR) exhibits distinctive fabric-controlled mechanical behavior that is strongly influenced by its internal pore structure and degree of diagenesis. This study combines petrographic observation, X-ray CT scanning, and saturated uniaxial compression testing to quantify the pore network characteristics and physico-mechanical properties of CRR. Three representative specimens were reconstructed in three dimensions and analyzed in terms of pore number, pore volume, throat length, and coordination number. The results show that CRR contains moderately developed pores dominated by micritic-calcite dissolution pores. Average pore radius ranges from 141.2 to 993.6 μm, the maximum pore radius reaches 5567.2 μm, and the throats are mainly short-range, with average lengths of 3705–5437 μm. Connectivity varies markedly among specimens: CRR-C contains an interconnected macropore cluster, whereas CRR-A and CRR-B are dominated by weakly connected mesopores. Dry density shows a strong nonlinear positive correlation with saturated uniaxial compressive strength, whereas porosity shows a negative correlation. Both variables exhibit preliminary exponential relationships with strength and constitute key controls on the mechanical response of CRR.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111052

Authors: Qingshan Wang Mengzhen Li

The continuous expansion of human activities into the marine environment imposes ever-increasing demands on the performance, reliability, and longevity of ships and offshore structures [...]

Journal of Marine Science and Engineering doi: 10.3390/jmse14111051

Authors: Imane Ghouafria Hana Ferkous Hichem Tahraoui Mohammed Rabeh Makhlouf Abdennouri Amdjed Mohammod Hafizur Rahman Farid Fadhillah Amine Aymen Assadi Jie Zhang Abdeltif Amrane

The intensifying global challenges of environmental degradation, escalating energy demands, and unsustainable waste accumulation necessitate the exploration of alternative, high-value biomass resources. Algal biomass has emerged as a uniquely versatile and sustainable candidate, offering transformative potential across a broad range of industrial and environmental sectors. This review comprehensively evaluates the recent advancements and multidisciplinary applications of algae, with a strong emphasis on their distinctive chemical composition, bioactive compounds, and environmental adaptability. The novelty of this review lies in its integrative scope, which spans from algae cultivation, production, and trade to cutting-edge extraction technologies for bioactive constituents. Furthermore, the review presents a detailed exploration of algae’s functionality as a feedstock for biofuels, pharmaceuticals, sustainable agriculture, bioplastics, green chemistry, and water treatment, positioning it as a cornerstone in the development of the blue economy. By critically analyzing both conventional and innovative applications, this work contributes to a deeper understanding of algae’s strategic role in shaping a sustainable and resilient bioeconomy.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111049

Authors: Yang Yu Jiandong Ma Jianxing Yu Peimin Li Lin Song Yuheng Yang Zhenglong Yang

LNG storage tanks are essential facilities for large-scale storage and transportation of cryogenic energy. Because of the flammable, explosive, and ultra-low-temperature characteristics of liquefied natural gas, failures in such systems may result in serious consequences for operational safety and the surrounding environment. Effective identification and prioritization of potential failure modes are therefore crucial for safe operation. Failure mode and effects analysis (FMEA) has been widely applied in risk assessment, yet conventional FMEA methods still show limited capability in describing uncertain linguistic evaluation information, reflecting the reliability of expert judgments, and representing high-order coupling relationships among failure modes. To address these issues, this study develops a modified FMEA framework that integrates confidence-enhanced probabilistic linguistic modeling with weighted hypergraph propagation for LNG storage tank risk assessment. In the proposed framework, confidence-enhanced probabilistic linguistic term sets are employed to represent the fuzziness, probabilistic preference, and reliability differences contained in expert assessments. A confidence-adaptive scoring function is further constructed to strengthen the discrimination of risk quantification by capturing structural differences in probability distributions without introducing externally specified parameters. Meanwhile, the importance of risk factors is determined through a combined subjective–objective weighting strategy, and a weighted hypergraph propagation mechanism is established to characterize high-order structural associations among failure modes and to revise baseline risk levels through a node–hyperedge–node transmission process. A case study of a large LNG storage tank system in Tangshan, China, is carried out to examine the applicability and effectiveness of the proposed framework. The results demonstrate that the proposed method can effectively integrate complex expert evaluation information with structural coupling effects, while sensitivity and comparative analyses further confirm its robustness and suitability for failure risk prioritization in LNG storage tanks.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111050

Authors: Baojiang Ye Haifeng Wang Wenbin Wang Tianyi Wang

Underwater images often suffer from color cast, low contrast, scattering-induced haze, and texture degradation, which limit the performance of underwater visual perception systems. To address these problems, this study proposes FreqMambaGAN, a frequency-decoupled selective state-space cycle-adversarial network for underwater image enhancement. The proposed method is built upon a CycleGAN-style bidirectional translation framework and introduces a frequency-decoupled Mamba generator to separately model low-frequency color and illumination information and high-frequency texture and edge details. In addition, Efficient Mamba Blocks are embedded into the generator and discriminator to enhance long-range dependency modeling with linear computational complexity. Skip-attention connections are further adopted to preserve shallow spatial details during reconstruction. To improve training stability and imaging plausibility, a multi-stage training strategy is designed by combining supervised warm-up, unpaired cycle-adversarial learning, perceptual regularization, total variation smoothing, and a lightweight physics-inspired consistency constraint based on dark-channel and underwater image-formation priors. Experiments on public underwater image enhancement datasets demonstrate that FreqMambaGAN achieves competitive quantitative performance and visually improved enhancement results in terms of color correction, contrast restoration, haze suppression, and structural preservation. These results indicate that integrating frequency-domain decomposition with selective state-space modeling is effective for underwater image enhancement.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111048

Authors: Gabriel Loureiro André Dias Eduardo Silva

The automated detection of deep-sea polymetallic nodules is critical for processing large volumes of benthic imagery. However, its scalability faces challenges from cross-expedition covariate shifts, such as changes in lighting, altitude, and camera payloads, which lower zero-shot model performance. While semi-supervised pseudo-labelling presents a potential alternative to time-consuming re-annotation, simple implementations can quickly lead to confirmation bias. This study identifies two primary sources of this degradation: spatial noise from tiling fragmentation at tile borders and an architecture-agnostic interior false positive floor caused by semantic domain shift. This work proposes using a multi-model ensemble for pseudo-labelling to reduce the noise impact. Using a spatial border filter and confidence stratification, three architecturally distinct teacher models (YOLOv8, Faster R-CNN, and DINO) are employed to determine a reliable and domain-invariant subspace. Under a strict anti-leakage Leave-One-Partition-Out protocol, the proposed approach surpasses the supervised fine-tuning baseline at 100-tile pseudo-label budget across four random seeds (macro mAP50:95 of 0.4745±0.0042 versus 0.4467±0.0079), with gains concentrated in the most domain-shifted fold. Beyond this budget, our findings highlight two important adaptation trends: a pool-size degradation trend where excessive pseudo-label volume actively degrades generalisation, and the observation that the fine-tuned models reduce pseudo-label fidelity despite higher precision, providing evidence for the advantage of using frozen source checkpoints for cross-domain adaptation.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111047

Authors: Jian Liao Jialong Wang Xiaopeng Tan

To address the performance degradation caused by coupling interference between control and identification filters in the active control of ship hydraulic systems, a multi-strategy collaborative optimization algorithm based on “Signal–Amplitude–Time” is proposed. The method constructs a variable-power white-noise module based on power factors to reduce auxiliary noise interference. It employs an improved variable-step-size LMS algorithm to achieve fast and high-precision online identification of the secondary path. Furthermore, an adaptive prediction error filter is introduced to decouple the control and identification processes, effectively resolving the conflict between convergence speed and steady-state precision. Simulation and experimental results demonstrate that the proposed optimization algorithm exhibits superior robustness and adaptive capability under various operating conditions. It can track complex load fluctuations in real time and achieve a line-spectrum pulsation attenuation of more than 90%. This multi-strategy collaborative scheme significantly enhances the pulsation suppression accuracy and dynamic response capability of ship hydraulic systems, providing an efficient and reliable technical approach for the acoustic stealth control of naval ship hydraulic systems.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111046

Authors: Xiumei Fan Lingzhi Li Yongchuang Shi Hanfeng Zheng Wei Chen Ziniu Li Chao Li Zhi Zhu Cuihua Wang

The Arabian Sea is a key region for global marine biogeochemical research, yet the distribution characteristics and influencing factors of dissolved oxygen and chlorophyll a concentration in its central oxygen minimum zone still require further in-depth investigation. Based on survey data and reanalysis data from 2024, this paper analyzes the distribution characteristics and underlying causes of chlorophyll a concentration and dissolved oxygen using empirical orthogonal function (EOF) decomposition of chlorophyll a concentration and dissolved oxygen saturation along the depth direction, combined with the distribution of the barrier layer, Ekman pumping induced by wind fields, and the diagnostic vertical velocity distribution calculated from ADCP-observed flow velocities. Taking approximately 10° N as the boundary, the chlorophyll a concentration in the layer shallower than 35 m exhibits a distribution pattern of high in the northwest and low in the southeast, while the water layer between 45 m and 95 m shows a pattern of low in the northwest and high in the southeast. A thick barrier layer exists in the southeastern region, whereas the barrier layer in the northwestern region is thinner or absent, resulting in lower surface chlorophyll a concentration in the southeast. ADCP observations indicate that horizontal flow velocities are higher in the south, bringing oxygen-rich water from the south, which leads to higher dissolved oxygen saturation in the southern region compared to the northern region in water shallower than 45 m. At the 65 m water layer, the higher chlorophyll a concentration in the south may result in relatively low dissolved oxygen. The hypoxic zone (dissolved oxygen saturation less than 30%) begins to appear at depths below 105 m, with its southern boundary located between 9° N and 11° N, and this boundary gradually shifts northward as depth increases. The diagnostic vertical velocity between 9° N and 11° N is higher than that in other regions, which may hinder the northward movement of oxygen-rich water from the south. In the southern region, influenced by wind stress, the vertical water movement induced by Ekman pumping is relatively significant, which may lead to a slight increase in dissolved oxygen saturation in water layers with a depth below 125 m.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111045

Authors: Christian Kaehler Fokke Saathoff

The design of coastal protection structures requires design parameters that accurately represent the hydrodynamic conditions along the coast. Currently, these input variables are based on univariate probability models, which do not consider the joint probability of water level and statistical wave parameters such as significant wave height. Bivariate probability modeling using copula models offers an alternative. Copulas can be used to describe the dependencies between water level and significant wave height and to compute joint probabilities of occurrence. First, various copulas are fitted to samples of physically consistent combinations of water level and significant wave height extracted from storm surge events along the German Baltic Sea coast of Mecklenburg-Western Pomerania. Next, the most appropriate copula model is used to compute design combinations of water level and significant wave height for selected return periods. The bivariate design parameters are compared with the univariate ones in a simplified design example for wave run-up on a dike. The validation of various models shows that the Frank copula best describes the dependence structure. The bivariate design parameters obtained for the same return periods are lower than those determined using the univariate method. The available data only allow a limited application of the copulas for engineering design in the study area. Nevertheless, copulas have the potential to replace univariate methods for determining design parameters and thus contribute to more reliable and cost-efficient coastal protection structure design.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111044

Authors: Liliana Olaya-Ponzone Rocío Espada Ruíz Estefanía Martín Moreno José Carlos García-Gómez

This study examines spatio-temporal patterns of dolphin species in a coastal ecosystem located in the Bay of Algeciras–Gibraltar (southern Spain), a highly anthropogenic coastal system influenced by a submarine canyon and exposed to intense anthropogenic pressure. Between 2017 and 2020, spatial and temporal relationships between short-beaked common dolphins (Delphinus delphis), striped dolphins (Stenella coeruleoalba), and bottlenose dolphins (Tursiops truncatus) were analysed. A solitary female bottlenose dolphin (Billie) was considered separately as an individual case due to its distinct behavioural patterns. Georeferenced data showed that distances between sightings of T. truncatus and subsequent observations of the other species ranged from 261 to 12,000 m, with temporal intervals spanning from 33 s to 5 h 38 min. Short temporal overlaps (≤300 s) were infrequent. These results indicate limited spatio-temporal overlap between D. delphis, S. coeruleoalba, and T. truncatus within the study area. While no statistically significant relationships were detected in the applied models, the observed patterns provide a descriptive quantitative characterisation of species distribution and co-occurrence in a highly anthropogenic coastal system. Given that D. delphis is classified as Endangered in the western Mediterranean and that both D. delphis and S. coeruleoalba are frequently observed with calves, these patterns may be relevant for understanding habitat use and potential implications for conservation. Overall, this study provides a detailed empirical characterisation of spatio-temporal patterns among sympatric dolphin species in this coastal system, highlighting the need for further research using targeted analytical approaches to assess interspecific dynamics.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111043

Authors: Joung-yun Lee Chang-su Kim Dae-Jung Hwang Samel An Mingyu Kim

The rapid adoption of alternative marine fuels has introduced safety challenges not fully addressed by regulatory frameworks developed for conventional fuels. This study examines how International Maritime Organization (IMO) safety regulations respond to the dominant risk characteristics of alternative fuels, focusing on LNG, LPG, methanol, and ammonia. A comparative analysis is conducted based on physicochemical properties, hazard pathways, and corresponding provisions under the IGF Code and Interim Guidelines. The results show that while the IGF Code provides a goal-based, flammability-centered framework, its extension to fuels with different risk profiles—such as toxicity and liquid-phase hazards—creates structural mismatches between dominant hazards and regulatory trigger mechanisms. In particular, reliance on flammability-based indicators (e.g., LEL) for safety system activation in toxicity-dominant fuels reveals a misalignment between regulatory assumptions and actual risk pathways. In addition, intensified conservatism in ammonia regulations enhances safety but raises challenges related to operability and regulatory predictability. The study concludes that future regulatory development should adopt an integrated framework aligning hazard-specific indicators with regulatory mechanisms and incorporating empirical evidence through the Experience Building Phase (EBP).

Journal of Marine Science and Engineering doi: 10.3390/jmse14111042

Authors: Chunjiang Bai Xinshuang Wang Guofu Tian Zhijian Gou Hongbin Sui

Arctic shipping lanes are gradually opening, creating an urgent demand for unmanned surface vehicles (USVs) capable of safe and efficient navigation in drifting-ice environments. However, dense, highly dynamic sea ice poses significant challenges for existing obstacle-avoidance approaches. This study proposes a dynamically weighted hybrid obstacle avoidance algorithm integrating an improved VO module and an enhanced APF module. The optimized VO method refines the velocity sampling strategy and incorporates DCPA/TCPA-based risk screening to eliminate high-risk candidate velocities. The improved APF method introduces adaptive parameter regulation, virtual-target-based local minimum escape, and historical-velocity-driven oscillation suppression. Furthermore, a real-time dynamic weighting mechanism is designed to balance the contributions of the VO and APF modules according to the instantaneous environmental risk level. Extensive simulation experiments demonstrate that the proposed algorithm achieves reliable collision avoidance performance, high navigation efficiency, and strong environmental adaptability for USVs operating in dynamic Arctic drifting-ice environments.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111041

Authors: Ante Čalić Nur Assani Goran Rilje Marko Katalinić

This study sets and evaluates a practical framework for predicting ship resistance under real operational conditions along a global shipping route. Despite extensive research, the literature lacks straightforward studies that separately assess wind, wave, and current resistance using real-world performance data for ships in varying conditions. To address this gap, a methodology is established using recommended semi-empirical approaches combined with full-scale onboard operational measurements and Copernicus Marine Service environmental data in a unified assessment procedure. Calm water resistance is scaled from reference values under near-calm conditions, wind resistance is calculated using established regression models, wave-induced resistance is estimated using state-of-the-art semi-empirical formulations and spectral calculations, and current effects are modelled through a dynamic correction based on speed-over-ground measurements. The aim is to assess the reliability and applicability of added resistance calculation methods recommended by recent regulatory standards. Validation is performed by comparing the predicted resistance components, converted to equivalent shaft power, against full-scale onboard shaft-power measurements. In addition, a comparison between onboard measurements of wind and current and Copernicus data is presented. Predicted resistance components are validated against full-scale power measurements, showing agreement with an average error of approximately 9%. The resulting framework provides a practical tool for assessing energy losses due to environmental factors along specific routes using readily available ship data.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111040

Authors: Jinshan Peng Haoran He Yingbo Huang

To improve the energy capture efficiency of wave energy converters (WECs), various control strategies based on adjustable power take-off (PTO) systems have been developed. However, such approaches often impose stringent requirements on PTO structural design and generator performance. To address this issue, this paper proposes a novel variable-stiffness point-absorber wave energy converter (VSPAWEC). In the proposed system, a stiffness regulator (SR) composed of a magnetorheological damper (MRD) and a spring mechanism is introduced as a frequency-tuning device, enabling stiffness compensation of the point absorber within a certain operating range. Based on the SR mechanism, a frequency-tracking resonance control strategy is further developed. Specifically, a sliding mode control algorithm is employed to regulate the MRD in real time, allowing the piston rod to track a reference position signal generated from the known dominant wave frequency. In this way, the spring force applied to the buoy can be adjusted adaptively, so that resonance between the buoy and the incident waves can be achieved. Finally, numerical simulations are conducted to evaluate the variable-stiffness characteristics of the proposed VSPAWEC and to verify the effectiveness of the developed frequency-tracking control strategy. The results demonstrate the feasibility of the proposed concept for resonance tuning and wave energy capture enhancement.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111038

Authors: Dmitry A. Ruban Svetlana O. Zorina Konstantin I. Nikashin Artem A. Trifonov Ilkhan I. Sakhabutdinov

Studying carbonate breccias enhances our understanding of various geological processes. Fieldwork in the vicinity of the Sakhray Massif in the Western Caucasus (western edge of the Caucasus Mountains) allowed us to discover a peculiar layer of carbonate breccia in the monotonous succession of Lower Triassic platy limestones. The lithological peculiarities of this breccia and the hosting rocks were examined in the field, as well as in polished slabs and thin sections. The results show that the breccia consists of a chaotic mass of chiefly angular clasts of entirely different limestones with abundant fossil debris and a micritic matrix similar to the hosting rocks but bearing siliciclastic debris. The age of the carbonate breccia is the same as that of the hosting rocks, i.e., it is late Induan–early Olenekian (Early Triassic), but the clasts are attributed to upper Changhsingian (Upper Permian) limestones (also reefal). It is proposed that these clasts were created by erosion in a subaerial environment, after which they were transported from a land mass to a deep sea. Apparently, extraordinary geological events (e.g., severe storms, earthquakes, or tsunamis) triggered submarine debris flows on a steep slope. From a practical point of view, the reported discovery extends the vision of the geological heritage of this part of the Western Caucasus.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111039

Authors: Xinhu Zhang Chengchun Yong Kuan Yang Yijun Liu

Pipeline walking induced by cyclic temperature and pressure loadings is a challenge in the design of deepwater subsea pipelines. To investigate the walking mechanisms, a 3D non-linear finite element (FE) model incorporating realistic pipe-soil interaction is established. A parametric study is performed to analyze the effects of vertical geometric imperfections, seabed slopes, structural tensions, and transient thermal gradients. The results show that single-end tension and downhill slopes accelerate the walking rate, whereas dual-end tension and uphill resistance restrict or reverse the walking direction. Notably, the unique mechanism of vertical geometric imperfections is revealed: increasing the imperfection height suppresses walking by absorbing thermal expansion, whereas increasing the imperfection length exacerbates the walking rate. Based on the numerical results, the complex pipeline walking mechanism is explicitly decoupled, which provides an evaluation for the reliable design of deepwater pipelines.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111037

Authors: Ze Zhang Tie Li Tian Zhou

Multibeam backscatter data are important for marine resource exploration and benthic habitat mapping. However, accurate estimation of absorption loss without concurrent CTD measurements can be challenging. This paper proposes an inversion method that combines a global Argo salinity model with sound speed profiles (SSPs). The method enables absorption loss correction using only SSP data, offering a potential engineering alternative that reduces the need for dedicated CTD casts and may support real-time processing. Salinity is interpolated from the Argo grid, temperature is inverted via empirical formula for sound speed, and the absorption coefficient is computed using the Francois–Garrison model. The method is evaluated using two open-access multibeam datasets from the NCEI: one from the Blake Plateau (depth 1050–1250 m, 26.5 kHz) and another from Johnston Atoll (depth 2000–5000 m, 28 kHz). Compared to concurrent CTD profiles, the maximum deviations observed are 0.3 ppt for salinity, 0.1 °C for temperature, and 0.06 dB/km for absorption coefficient. The difference in absorption loss between the inversion and the CTD-based reference is within 0.1 dB. A precomputed lookup table indexed by incidence angle and one-way travel time is constructed for rapid estimation. In a test of 5196 swaths (432 beams per swath), the total interpolation time is 0.726 s. These results suggest that the proposed method provides a practical solution for absorption loss correction when CTD data are unavailable.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111036

Authors: Maria V. Alvanou Ioannis Georgoulis Ioannis A. Giantsis Ioannis Mourtzinos Eleni Zymvrakaki Basile Michaelidis George Katselis Konstantinos Feidantsis

Fish nutritional value is a complex trait, highly influenced by fatty acid composition, which is correspondingly affected by a variety of factors, such as seasonality, abiotic conditions, and genetic background. Herein, the seasonal variations in lipid metabolism and the composition of fatty acids in three economically important mullet species (Chelon auratus, Chelon ramada, and Mugil cephalus) in an appropriate fisheries model marine area, Klisova Lagoon, Greece, were investigated. From seasonal sampling across one year, data regarding the sea temperature, fatty acid profiles in fish fillet, lipid-related gene expression (acc, hoad, and atgl), and key enzymatic activities (citrate synthase, HOAD, and lipase) in liver and muscle were obtained. Biochemical, molecular, and enzymatic analyses revealed pronounced interspecific and seasonal differences in lipid metabolism and the composition of fatty acids among Chelon auratus, Chelon ramada, and Mugil cephalus. M. cephalus exhibited strong metabolic plasticity, with enhanced lipid oxidation during colder periods and increased lipid synthesis and mobilization during warmer months. In contrast, C. ramada and C. auratus generally showed higher PUFA and ω-3 contents, although nutritional quality across all species was largely season-dependent, with colder periods favoring unsaturated fatty acid accumulation. Coordinated seasonal shifts in gene expression and enzyme activities reflected these temperature-driven metabolic regulation and distinct thermal-adaptation strategies. These metabolic traits support the ecological success of mullets in Mediterranean environments and highlight underutilized C. ramada and C. auratus mullet species as nutritionally valuable, sustainable alternatives for regional fisheries and aquaculture, supporting both sustainable fisheries and consumer awareness within the EU seafood market.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111034

Authors: Tianni Wang Tina Ziting Xu Zongjie Ding Mei Sha Lingzhi Ye Junqing Tang Mark Ching-Pong Poo Yui-yip Lau Chengpeng Wan

Climate change has intensified the frequency and severity of meteorological disasters, posing significant challenges to the resilience and adaptability of port-centric transport networks (PCTNs) and global trade stability. Unlike previous studies that adopt generalised resilience frameworks or treat disaster types uniformly, this study develops a disaster-specific, integrated assessment framework whose novelty lies in coupling three complementary methods, each playing a distinct role: (i) integer programming optimises post-disaster recovery decisions under budgetary constraints by selecting cost-effective measures that maximise re-stored container-handling capacity; (ii) Monte Carlo simulation (10,000 iterations) captures the stochastic nature of meteorological disruptions and quantifies probabilistic resilience under typhoons, storm surges, and heavy fog; and (iii) an Analytic Hierarchy Process–Evidence Reasoning (AHP–ER) hybrid integrates subjective expert judgement with objective field data to evaluate adaptability across a four-level indicator system, thereby reducing the subjectivity of conventional multi-criteria approaches. Applied to Shanghai Port, the framework yields normalised resilience scores on a [0, 1] scale, where 1.0 denotes full operational continuity (network throughput equals demand) and values below 0.80 indicate substantial disruption requiring urgent intervention. Heavy fog produces the lowest score (0.73, ‘moderate-to-severe disruption’), followed by typhoons (0.81, ‘mild disruption’) and storm surges (0.89, ‘near-normal operation’), revealing that low-visibility events—not high-energy storms—pose the dominant operational threat at Shanghai Port. Translating these findings into practice, the study recommends the following: (1) deploying real-time visibility-monitoring (LiDAR) and AI-driven traffic-scheduling systems to mitigate fog-related disruptions; (2) reinforcing gantry-crane anchoring and prepositioning emergency power supplies in typhoon-prone berths; (3) prioritising hinterland-port handling redundancy in Jiangsu and Anhui sub-networks (adaptability scores 0.639 and 0.642); and (4) piloting an integrated Shanghai–Zhejiang cross-regional emergency-response corridor with shared berthing rights and standardised joint drills. These targeted, quantitatively grounded recommendations offer port authorities and policymakers an evidence base for prioritising infrastructure investment and organisational reform to safeguard global supply chains against escalating climatic threats.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111035

Authors: Xiuyan Liu Jingtong Yuan Yufei Zhang Dalei Song Qi Qi

High-resolution turbulence data are essential for marine environment monitoring, climate change modeling, and aerospace engineering. However, numerical simulations and experimental measurements are often limited by high computational costs, insufficient sensor resolution, and sparse data acquisition, making it difficult to fully capture the multi scale details of turbulence. To address this challenge, a spatio-frequency fusion distillation network (SFDN) is developed to reconstruct finescale turbulent structures from low resolution inputs. The proposed model is built upon stacked Mamba-frequency distillation blocks, where each block integrates multiple Mamba-frequency fusion blocks (MFFBs) to refine and fuse the deep features of turbulence. By combining a Mamba-based state space model with a frequency attention mechanism, the MFFB is capable of capturing both long-range spatial dependencies and frequency-domain representations. Additionally, a physics-guided loss function is introduced to constrain the solution space and guide the learning process. To evaluate the performance of the proposed SFDN, comprehensive experiments were conducted on datasets of the forced isotropic turbulence and the turbulent channel flow, and comparisons were made with bicubic interpolation and several deep learning super-resolution models. The results demonstrate that SFDN achieves comparable or superior performance to state-of-the-art methods in terms of visual quality, quantitative accuracy, and preservation of physical characteristics, while using only 35.38% of the parameters of leading models. These findings highlight the effectiveness and efficiency of the proposed approach, as well as its strong generalization capability for reconstructing complex turbulent flows.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111033

Authors: Fanghong Zhang Hongwei Wang Yongliang Zhang Weipao Miao Chengyu Hou

Offshore wind energy plays an increasingly important role in the global energy transition, while its design, layout, and operation involve complex optimization problems with strong nonlinearity, high computational cost, and uncertainty. This paper reviews recent advances (2021–2025) in mathematical optimization methods applied to offshore wind energy systems, focusing on turbine system design, wind farm layout, and control strategy optimization. A systematic and semi-quantitative comparison of optimization methods is conducted, including gradient-based methods, metaheuristic algorithms, surrogate-assisted approaches, and multi-objective optimization techniques. These methods are analyzed in terms of computational efficiency, applicability, global search capability, and engineering relevance, supported by representative results reported in the literature. The review further identifies key methodological patterns, discusses trade-offs among different approaches, and proposes practical guidelines for method selection. Finally, research gaps are highlighted, particularly regarding uncertainty modeling, computational scalability, and integrated optimization frameworks. The findings provide useful insights for both researchers and engineers in offshore wind optimization.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111032

Authors: Xianghai Zhong Nini Wang Xinxin Guo Junwu Zhang Dagang Zhao Chunyu Guo

The present study conducts numerical simulations to investigate the excitation force characteristics of a pre-swirl stator–propeller–rudder system and analyzes the potential benefits of the combined pre-swirl stator and rudder bulb for vibration and noise based on force and pressure fluctuations. The propeller bearing force, rudder force and hull surface pressure are compared and analyzed under conditions with and without energy-saving devices. The results show that the pre-swirl stator and rudder bulb intensify the axial load pulsation of the propeller, which may affect the service life of the main engine and gearbox. The overall level of lateral load pulsation is also increased, which may lead to higher cabin noise. The load pulsation level of the pre-swirl stator is comparable to that of the propeller bearing force, while the increased vibration of the rudder may result in more complex structural safety and noise issues. The reduction in hull surface pressure fluctuation contributes to the mitigation of the low-frequency underwater radiated noise. The influence mechanism of the pre-swirl stator–rudder bulb on the excitation force is of great significance to the ship engineering design.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111031

Authors: Hongxiu Zhai Shuhui Li Yuting Ma

Three new species of free-living marine nematodes, which were collected from Chinese marine waters, are herein described and illustrated. Metadesmolaimus pilosus sp. nov. is distinguished by a colourless body bearing numerous long somatic setae; cephalic setae measuring 13–17 µm in length; arcuate spicules with a cephalated proximal end and a conical, pointed distal end, approximately 1.6 cloacal body diameters long; a boat-shaped gubernaculum without apophyses; and a conico-cylindrical tail with three terminal setae. M. sinicus sp. nov. is distinguished by a relatively large amphideal fovea (53% of corresponding body diameter) in males; cephalic setae measuring 12 µm in length; slender, almost straight spicules, with a cephalated proximal end and a conical distal end, approximately 1.9 cloacal body diameters long; gubernaculum hooked distally without apophysis; and tail conico-cylindrical with two terminal setae. Steineria gracilis sp. nov. is distinguished by outer labial setae comparatively thick; eight groups of subcephalic setae, each comprising four unequal setae, 15–49 µm long; two sublateral pairs of cervical setae posterior to each amphid; circular amphideal fovea located about one head diameter from the anterior end; spicules slightly bent ventrally, approximately 1.2–1.3 cloacal body diameters long; gubernaculum barrel-shaped with hooked dorso-caudal apophyses; and tails with two long terminal setae and two short terminal setae. Updated keys to all valid species of Metadesmolaimus and Steineria are provided.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111029

Authors: Junxue Zhang Yan Gong Hairuo Wang Ashish T. Asutosh Ge Song Weidong Wu Xiaoting Zhai

This study develops an integrated framework combining emergy analysis, carbon footprint accounting, and long short-term memory neural network modeling to investigate the effects of nature-based solutions on coastal ecosystem services and blue carbon functions from the perspective of river–coast connectivity. Three transects along a connectivity gradient were established in the Yellow River Delta, a typical large river delta in temperate China, covering riparian zones, estuarine transition areas, intertidal wetlands, and seagrass beds, with multi-source data collected over three consecutive hydrological years. Emergy–carbon coupling analysis based on this case study indicates that the high-connectivity transect shows a higher emergy yield ratio and net carbon sink compared to the low-connectivity transect, with salt marshes being most sensitive to connectivity change. Threshold analysis, specific to this delta, identifies a three-phase response pattern of carbon burial rate with increasing sediment connectivity, and reveals that wave attenuation efficiency declines notably when hydrological connectivity falls below approximately 0.5, although this value may vary across different coastal settings. A higher sea level rise rate raises the critical connectivity level required to maintain carbon sink function. The long short-term memory neural network trained on observational data achieves better prediction accuracy for blue carbon accumulation rates than traditional statistical methods, and SHAP value analysis suggests the possible existence of synergistic effects among connectivity dimensions. Based on these findings, three optimization strategies including tiered restoration, a dynamic pathway, and spatial configuration are proposed as case-specific recommendations for the Yellow River Delta. Framework-based simulations indicate the potential for connectivity-informed strategy adjustments to improve restoration efficiency under local conditions. This study concludes that river–coast connectivity represents an important lever regulating the ecological benefits of nature-based solutions, but emphasizes that all quantitative thresholds and benefit magnitudes reported here are case-specific estimates that require recalibration when applied to other coastal systems.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111030

Authors: Xinran Liu Haoran Meng

In situ marine particle-field observation by parallel phase-shifting digital holography (PPSDH) produces long image sequences under real deployment conditions, but exhaustive full-frame reconstruction and segmentation are computationally expensive when many frames are low contrast and particle-like targets occupy sparse regions. This paper presents a training-free two-stage selective-processing workflow for a 9521-frame coastal South China Sea PPSDH campaign. Stage 1 uses an amplitude-derived contrast metric as a campaign-specific pruning rule to form a retained-frame pool, and Stage 2 combines coarse reconstruction, candidate filtering, valid-field gating, and ROI merging for ROI-restricted reconstruction and segmentation. Stage 1 retained 6970 frames, corresponding to 73.2% of the full sequence. On a balanced 120-frame benchmark, Stage 2 achieved a spatial-support reduction ratio of 49.9% ± 12.0%, and the complete workflow provided a 5.66-fold end-to-end speedup relative to a matched full-frame baseline. The efficiency gain was accompanied by a measurable fidelity cost, with a baseline-matched correspondence rate of 0.612 and a count-based yield gap of 0.287, mainly associated with small or weak targets within the selected ROI support. These results show that the proposed workflow can support computation-aware review of real marine PPSDH particle fields by efficiently prioritizing informative frames and particle-like regions for downstream visual assessment.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111028

Authors: Haoyu Wang Shuai Chang Hao Zheng Shuo Yang Jianxin He Xiong Deng

High-precision identification of acoustic convergence zones (CZs) and acoustic shadow zones (SZs) is a core prerequisite for deep-sea sonar performance prediction and long-range underwater target detection. However, in data-scarce marine environments, traditional acoustic identification methods suffer from high environmental sensitivity and significant computational costs, while pure data-driven deep learning methods face dilemmas such as a lack of physical consistency and poor generalization on small samples. To address these issues, a three-level cascaded recognition framework based on physics-prior-augmented deep learning is proposed in this paper, enabling accurate segmentation of CZs and intelligent classification of sound field types under data-scarce scenarios. In this framework, physical acoustic principles are incorporated exclusively as priors through a training dataset generated by a Gaussian beam acoustic propagation code (Bellhop) and through hand-crafted geometric features derived post hoc from the initial segmentation outputs. Taking a typical deep-sea area in the Northwest Pacific Ocean as the research object, a hybrid dataset comprising 5000 simulated transmission loss images and 500 simulated images from a geographically distinct sea area is constructed. The sound field is categorized into four types: strong convergence, usable convergence, weak convergence, and shadow zone. In the first stage, the ResNet-34 backbone is improved by integrating deformable convolution and a global statistical feature module, which, combined with a joint loss function, achieves high-precision pixel-level segmentation of CZs and SZs, with the regional gray contrast reaching 86.9%. In the second stage, a customized dual-channel VGG16 architecture is designed to fuse the extracted geometric priors and visual features, achieving a sound field classification accuracy of 89.91%. In the third stage, a hybrid data augmentation technique combining Mixup and convolutional autoencoder is adopted alongside a transfer learning strategy to mitigate the data scarcity under cross-domain conditions, boosting the small-sample classification accuracy to 84.45%. The experimental results demonstrate that the models in each stage of the proposed framework significantly outperform traditional methods and baseline networks. This study provides a novel methodology and technical support for intelligent sound field identification in data-scarce marine environments. Finally, the core contributions and current limitations are summarized, and future research directions, such as constructing a dynamic hydrological parameter feedback mechanism and identifying three-dimensional complex sound fields, are prospected.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111027

Authors: Duo Wan Wei Chen Yongqing Shi Lu Han

Underwater manipulator grasping remains challenging because image blur, light attenuation, and flow-induced disturbances degrade perception and control. These factors make target localization, contact judgment, and stable lifting difficult, especially when visual degradation and tactile fluctuation occur together. We propose AVT-TD3, an adaptive visual–tactile fusion reinforcement learning method for underwater manipulator grasping. AVT-TD3 constructs a unified policy state from visual observations, short-horizon tactile variations, and manipulator proprioception. A gated fusion module adjusts the contribution of each sensory branch, while an action modulation mechanism limits abrupt velocity-command changes during contact establishment and lifting. We train the continuous grasping policy with Twin Delayed Deep Deterministic Policy Gradient (TD3) and evaluate it in simulation under different turbidity, flow velocity, and target conditions, followed by controlled water-tank feasibility validation. Simulation results show that AVT-TD3 achieves better performance than Deep Deterministic Policy Gradient (DDPG), Soft Actor-Critic (SAC), and standard TD3 in success rate, completion steps, slip rate, and velocity-command smoothness. In the standard test scenario, AVT-TD3 achieves a success rate of 92.7%, an average of 76 completion steps, a slip rate of 4.1%, and an action variation magnitude of 0.20. Controlled water-tank tests further support the feasibility of deploying AVT-TD3, although open-water validation remains for future work.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111026

Authors: Sergejus Lebedevas Jevgenija Rutė Dominykas Marozas

One of the most critical challenges in maritime transport decarbonization, as part of the EU greenhouse gas (GHG) neutrality strategy, is the reduction in GHG and harmful emissions from the energy systems of existing vessels. Furthermore, the potential for implementing decarbonization technologies in operating vessels remains significantly more limited compared to newly constructed ships. Selecting appropriate decarbonization measures requires a comprehensive evaluation of technological feasibility, economic viability, and environmental performance, in accordance with the regulatory frameworks established by the IMO and the EU. A major limitation in such decision-making processes is ensuring the representativeness and reliability of expert judgments. In order to improve the reliability of results by expanding and structuring the information base, this study proposes and implements a method based on the integration of SWOT analysis with multi-criteria decision-making (MCDM) methods. The objective of this study was to examine the methodological aspects of testing the integrated application of comprehensive analysis and ranking methods for decarbonization technologies as applied to a prototype oil tanker. Based on the SWOT analysis method, technological solutions that are available for practical application were identified for the medium-term decarbonization period considered in the study, up to 2030–2035. Subsequent rating based on several applied multi-criteria (MCDM) analysis methods (TOPSIS, COPRAS, SAW) allowed us to examine the range, stability and sensitivity of the obtained solutions in relation to the methods themselves and scenarios with variations in the weighting factors of the evaluation criteria. The complete match of the ratings obtained using the TOPSIS and COPRAS methods confirms the stability of the multi-criteria decision-making process (priority-compromise order): CCS, kite, air lubrication, Flettner rotor. The performed sensitivity analysis showed that the technology rankings remain relatively stable when the weighting factor for the CO2 reduction criterion varies within a range of approximately ±10%, while larger deviations result in an increasing difference between all three MCDM methods. For the TOPSIS method, the change limits for the critical values of the threshold indicators were ±20%, the COPRAS method showed intermediate results, and changing the weighting coefficients within a ±20% range did not alter the selection of the best technology. The results obtained allow for a positive assessment of the effectiveness of the proposed integrated methodology when applied as an alternative in the initial stage of ranking decarbonization methods for in-service ships.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111024

Authors: María José Ruelas Carlón Apolinar Santamaría Miranda Juan Pablo Apún Molina Luis Tupak Aguilar Bustos Máximo García Marciano Luis Parmenio Suescún-Bolívar Martín Armando Román Vega Mauro Espinoza Ortiz

The proliferation of microplastics in marine environments threatens coastal ecosystems via ingestion by planktivorous fish. This study evaluated the occurrence of microplastic-like particles (MPLPs), characterized morphologically, in the digestive tracts of Opisthonema libertate and Sardinops sagax in the Gulf of California. Blue and green fibers dominated the assemblages. O. libertate exhibited peak abundance in autumn (74.08 particles/individual), while S. sagax peaked in winter (78.10 particles/individual). Species-specific analysis revealed distinct patterns: S. sagax showed a strong positive correlation between MPLP abundance and both total length (r = 0.71, p < 0.01) and body weight (r = 0.68, p < 0.05), indicating ontogenetic accumulation. Furthermore, a significant negative correlation between MPLPs and triglycerides in S. sagax (r = −0.38, p < 0.05) suggests a potential metabolic cost. Conversely, ingestion in O. libertate appeared incidental. These findings document chronic exposure in key forage fish, with high fiber prevalence suggesting abandoned fishing gear as a likely source. While spectroscopic validation is needed, these results highlight the necessity of integrating microplastic monitoring into sustainable fisheries management to ensure food security in the region.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111025

Authors: Boyang Zhang Zhicheng Zhang Weixing Feng

Safe and intelligent collision avoidance technology is essential for the autonomous underwater vehicle (AUV) to navigate in underwater environments. Most existing spike methods are constrained by a fixed static threshold and are unable to dynamically adjust to threshold changes reasonably, leading to difficulties in robustly adapting to external dynamic interference and thus resulting in insufficient homeostasis and generalization. To address these limitations, inspired by the dynamic threshold changes in biological neural systems, a bioinspired dynamic adaptive threshold (BDAT) is proposed. Combining the spiking neural network with deep reinforcement learning, a novel bioinspired dynamic adaptive threshold planner (BDAT-Planner) framework is constructed for underwater dynamic collision avoidance tasks performed by AUVs in complex, unknown environments. The proposed BDAT-Planner consists of the spiking dynamic adaptive actor network (SDAAN) and the deep critic normal network (DCNN). The BDAT is deployed to each spiking neuron in the SDAAN, dynamically adjusting the spike firing rate through threshold changes and avoiding excessive excitation or inhibition, thus maintaining homeostasis. The spiking encoder and spiking decoder are designed to convert continuous information and spiking sequences. Experimental results from both the training process and evaluation process (ablation studies, comparison experiments, and homeostasis experiments) demonstrate that the proposed BDAT-Planner has achieved superior performance in dynamic collision avoidance and model homeostasis compared to static threshold methods and existing comparison methods. The novel idea of bioinspired dynamic adaptive threshold can maintain model homeostasis and effectively enhance its adaptability to external dynamic interference, which offers significant development potential for promoting the efficient and stable operation of AUVs in marine environments.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111023

Authors: Yiqi Shi Xiang Liu Yueying Wang Weidong Zhang

Unmanned surface vessels (USVs) equipped with onboard vision are increasingly used in environmental monitoring, search and rescue, and autonomous navigation. However, conventional USV autonomy systems often adopt a decoupled design in which target perception and disturbance estimation are developed independently. Such systems may suffer performance degradation when visual observations become unreliable under water-surface reflections, illumination variations, or partial occlusions, while the disturbance observer still depends on manually tuned parameters under time-varying environmental disturbances. To address these issues, this paper proposes a three-stage co-optimized target perception and disturbance estimation framework for USVs. First, a lightweight hybrid convolutional neural network (CNN)–Transformer perception module is developed to extract robust vessel features under challenging water-surface visual conditions. Second, a reinforcement learning (RL)-driven mechanism is used to adaptively tune a higher-order sliding mode observer (HOSMO) for disturbance estimation. Third, a confidence-guided perception-observer co-optimization strategy is formulated, in which visual confidence is used to regulate observer adaptation and reduce estimation divergence during temporary perception degradation. Simulation and outdoor lake experiments demonstrate that the proposed framework improves visual matching accuracy, observer convergence, and estimation stability compared with conventional decoupled methods. The outdoor lake experiments provide initial real-world validation under natural illumination variations and mild water-surface disturbances, while further open-water and multi-vessel validation is planned for future work.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111022

Authors: Chen Fang Ruijie Xu Peipei Zhang Minhui Zheng Junyi Yang

Investigations into deep-sea ecosystems are essential for elucidating the origins of life on Earth. Nevertheless, constraints in marine biotechnology have limited our understanding of biological processes occurring in these environments. In this study, we developed and evaluated an in situ cultivation system specifically designed for deep-sea environments. This system enables continuous induction cultivation directly on the seabed and facilitates comprehensive monitoring of the entire cultivation process via an imaging technique. The system is composed of three distinct modules: a cultivation and observation module, a methane slow-release module, and a power management module. This system enables controlled, slow release of energy and materials, allowing for the cultivation and sampling of communities on the seafloor, and supports long-term sequential monitoring through imaging. Through three deployment trials, we successfully established an artificial methane-driven deep-sea ecosystem on the seafloor of the South China Sea. Furthermore, by modifying the types of energy and materials supplied, the system can be adapted to address diverse scientific objectives, offering a robust tool for advancing research on deep-sea life.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111021

Authors: Zhenhao Song Bo Woo Nam

In this study, a systematic numerical study on design optimization was conducted for a tension leg platform (TLP)-type floating offshore wind turbine (FOWT), aiming to improve hydrodynamic performance, tendon behavior, and cost-effectiveness. Six design variables associated with hull geometry and tendon properties—pontoon length (PL), pontoon width (PW), platform draft (PD), main column diameter (CD), tendon pre-tension (Pre), and axial stiffness (EA)—were considered. For the global performance analysis, hydrodynamic coefficients were first obtained in the frequency domain, and motion and tendon tension responses were subsequently evaluated in the time-domain under a survival condition representative of a Southeast Asian site. A surrogate model based on the response surface method (RSM) was developed to predict platform responses across the design space. Multi-objective optimization was then performed using the non-dominated sorting genetic algorithm II (NSGA-II), yielding Pareto-optimal solutions that reveal trade-offs among competing performance metrics. The proposed framework is intended to provide Pareto-optimal design candidates for preliminary TLP-FOWT design, while the selection of a final design requires project-specific criteria and is beyond the scope of the present conceptual study. The optimization results show that the tendon tension can be effectively reduced while maintaining cost efficiency by increasing the pontoon length and slightly decreasing the tendon axial stiffness. For the tension–surge motion optimization, the Pareto-optimal solutions provide a balanced trade-off, where tendon tension is clearly reduced with only a slight increase in surge motion. In addition, the cost–nacelle acceleration optimization shows that nacelle acceleration can be further reduced by increasing the platform draft and pontoon length, although this is accompanied by a slight increase in the cost index. These findings provide practical insights for balancing global performance and cost in TLP-type FOWT design.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111020

Authors: Zeeshan Ahmad Jiacheng Xia Armindo H. Cambule Shudi Bao Zhengjie Ji Hao Zheng Meng Chen

Fish disease and species identification is critical for intelligent aquaculture, directly influencing productivity, sustainability, and economic viability. However, existing approaches largely treat species identification and pathological classification as independent tasks, limiting their ability to capture interdependent features under complex real-world conditions such as occlusion, low contrast, dynamic backgrounds, and high inter-class similarity. Moreover, challenges including class imbalance, cross-species variability, and fine-grained feature discrimination remain insufficiently addressed. To overcome these limitations, this paper proposes a hybrid ConvNeXt–BiLSTM–multi-head self-attention (MHSA) framework for joint fish species and disease classification, where a ConvNeXt-Small backbone extracts hierarchical spatial features that are transformed into a structured sequence and processed by a bidirectional LSTM to capture contextual dependencies, followed by an MHSA module for adaptive feature refinement. An auxiliary species classification branch is incorporated to provide multi-task regularization without additional inference costs. The training pipeline integrates CLAHE-based image enhancement, square-root inverse-frequency focal loss, targeted minority oversampling, and a two-stage progressive learning strategy with differential-rate cosine annealing, complemented by five-view test-time augmentation. For practical deployment, a YOLOv8s detector is employed for fish localization prior to classification. The experimental results demonstrate that the proposed model achieves superior performance, attaining overall top-1 classification accuracy of 94.33%, precision of 97.1%, recall of 90.9%, 96.1% mAP50, and an F1-score of 0.9264, while achieving a macro AUC of 0.994 and maintaining high computational efficiency (213.3 FPS), demonstrating a robust and efficient solution for real-time fish disease screening.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111019

Authors: Felipe S. Freitas Patrick Downes Alexander P. Webber Joaquim Bento Claire Dalgleish Leigh Marsh Michael Clarke

Organic matter production, recycling, and burial processes temporally fluctuate across the Clarion-Clipperton Zone (CCZ) in the Eastern Tropical Pacific. Between 2019 and 2022, we conducted pelagic and benthic surveys in Nauru Ocean Research Inc. contract area D (NORI-D) in the southeast CCZ to establish environmental baseline conditions. Here, we synthetise the natural ranges of variability in physicochemical and biogeochemical processes in NORI-D across multiple surveys and years. We present interannual water column physicochemical characteristics from five metocean and pelagic campaigns, annual satellite-derived net primary productivity and export production, time-integrated sediment trap annual particulate organic carbon flux, and seafloor biogeochemical and sediment physical characteristics from three benthic campaigns. Temperature and salinity seasonally varied at the sea surface. Strong thermohaline and oxygen stratification developed over 0–100 m. Mean net primary productivity, export production, and seafloor particulate organic carbon flux amounted to 634.1, 15.7, and 2.1 mg C m−2 d−1, respectively. These rates fluctuated nearly four-fold seasonally and interannually. An oxygen minimum zone (100–700 m) dampened organic carbon flux attenuation (b = −0.538) to the abyss. Abyssal seafloor organic matter dynamics showed more homogenous conditions in 2020–2021 (TOC = 0.57 ± 0.05%) than in 2022 (TOC = 0.42 ± 0.19%). Bioturbation rate and mixed-layer depth decreased from 2020 to 2022, while oxygen consumption increased at 0–1 cm bsf. Lipid consumption and compositional alteration in 2022 surpassed 2020–2021. Our findings provide critical baseline data to inform environmental impact assessments and monitoring programmes for deep-sea mining of polymetallic nodules in NORI-D.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111018

Authors: Yong-Qiang Zhang Zhe Feng Cong-Bo Xiong Wan-Qing Chi Wan-Jun Zhang

Breakwater construction at meso-tidal ports fundamentally alters near-field hydrodynamics and drives harbor sedimentation, yet the three-dimensional mechanisms linking entrance geometry to sediment flux remain poorly quantified. Here, we apply a validated Delft3D tidal–sediment coupled model to Caofeidian Port, Bohai Bay, comparing pre-construction baseline conditions against four entrance width scenarios (400, 300, 250, and 200 m). Breakwater enclosure reduces depth-averaged harbor velocities by 61.9–63.2% during spring tides, while generating tip-jet velocities of 1.41–1.53 m s−1 at the eastern breakwater head—exceeding pre-construction maxima by 14–18%. The eastern tip produces an ebb vortex (radius ~230 m; peak vorticity 0.034 s−1) approximately 34% larger and 62% more intense than its flood counterpart, driving vortex-assisted sediment recirculation toward the harbor interior despite ebb-dominant background velocities. Reynolds flux decomposition confirms that the eastern tip-vortex sector contributes ~39% of net sediment import (advective component: −0.7%), directly quantifying vortex-assisted recirculation as an independent transport mechanism. Bed shear stress falls below the critical erosion threshold (τce = 0.22 Pa) across 76.8% of the harbor area during spring tides (robust lower bound ~60% under wave-coupling correction), creating a structurally stable depositional interior, while the near-entrance zone sustains persistent tidal-cycle resuspension. Asymmetric tidal pumping—flood-phase open-sea SSC of 0.088 kg m−3 versus ebb-phase harbor SSC of 0.032–0.041 kg m−3—drives net spring-tide sediment import of 14.8 × 106 kg per cycle (wave-coupled upper bound: 17.8–19.2 × 106 kg per cycle). Entrance width reduction from 400 to 300 m achieves a favorable sedimentation-to-water exchange trade-off (marginal efficiency ratio 1.23), whereas further reduction to 200 m indicates onset of hydraulic choking. The marginal efficiency ratio declines sharply from 1.23 (400 → 300 m) to 1.03 (300 → 250 m) to 1.01 (250 → 200 m), indicating a hydraulic transition within the 250–300 m range that warrants targeted refinement in future studies.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111017

Authors: Yuelian He Rijin Jiang Rui Yin Peng Zhao Mengyuan Zhang Jinqing Wang

In recent years, climate change has increasingly shaped the potential habitat distribution of marine fishes, rendering this topic a focal area in marine ecology and biogeographical research. Using the MaxEnt modeling approach, this study projects the current and future potential habitats of eggs and larvae of two ecologically and economically important coastal species, the Liza haematocheilus and the Harpadon nehereus, across the nearshore waters of Zhejiang Province. Distribution records of early life stages and key environmental variables were integrated to model suitability under present-day conditions and three Shared Socioeconomic Pathway–Representative Concentration Pathway climate scenarios: SSP2-4.5, SSP3-7.0, and SSP5-8.5. Results identify sea surface salinity, surface current velocity, and sea surface temperature as the primary drivers of habitat suitability for Liza haematocheilus early-life stages; in contrast, chlorophyll-a concentration emerges as an additional significant predictor for Harpadon nehereus, alongside the aforementioned three variables. Under contemporary climatic conditions, high-suitability habitats for Liza haematocheilus eggs and larvae are predominantly concentrated in estuarine and island-adjacent nearshore zones, constituting 40.76% of the total predicted suitable area. For Harpadon nehereus, high-suitability areas are broadly distributed across nearshore shelf waters, representing 65.57% of its total modeled suitable habitat. Projected under future scenarios, the largest absolute increase in high-suitability area for Liza haematocheilus occurs under SSP3-7.0 in the 2050s (+0.38 × 104 km2), whereas Harpadon nehereus exhibits its greatest expansion under SSP5-8.5 in the 2090s (+0.45 × 104 km2). Collectively, the total suitable habitat area for Liza haematocheilus is projected to expand across all three scenarios, while that of Harpadon nehereus remains relatively stable overall—yet its high-suitability fraction increases markedly under high-emission, high-warming conditions. These findings suggest that ongoing climate warming may facilitate range expansion and enhanced nursery habitat availability for both species in Zhejiang’s coastal zone, positioning them as potential ecological beneficiaries of regional climate change.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111016

Authors: Jinfeng Zhang Zijun Tu Taoning Yang Junchi Zhu Yongqiang Sun

The maritime industry faces the urgent challenge of reducing greenhouse gas (GHG) emissions while maintaining economic viability, especially under the International Maritime Organization’s (IMO) Net-Zero Framework and Carbon Intensity Indicator (CII). Optimizing ship speed is a key operational measure, but it involves a complex trade-off between fuel consumption, voyage time, and regulatory compliance costs. This paper presents a multi-objective ship speed optimization method using Evolutionary Deep Learning (EDL). In this study, EDL is defined as the integration of a deep gradient boosting fuel predictor (CatBoost) and a gradient-free evolutionary optimizer (Natural Evolution Strategies, NES). A hybrid fuel consumption prediction model combines ISO 15016:2015 physical constraints with CatBoost, achieving a Mean Absolute Percentage Error of 6.45%. The optimization model minimizes total operating costs and GHG emissions, incorporating Greenhouse Gas Fuel Intensity (GFI) compliance costs, CII rating constraints, and a voyage segmentation strategy. The problem is solved with an NES algorithm using Gaussian population representation and an elitism strategy. A case study of a transpacific voyage of a large container vessel (COSCO PACIFIC) shows that the proposed EDL method achieves the lowest GHG emissions among all benchmark algorithms (reducing CO2eq by 9.18% compared to NSGA-II) and the fastest computation time (63.9% shorter than NSGA-II). While MOPSO and MOACO yield lower raw fuel costs by sacrificing emissions and compliance performance, EDL attains a superior balance across all objectives—emissions, compliance costs, and Comprehensive Fitness—with robust convergence and high computational efficiency. This approach offers practical support for sustainable ship navigation under complex regulatory pressures.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111013

Authors: Rui Yang Zili Dai

Submarine landslides pose severe marine geological hazards. Their movement and deposition behaviors can seriously threaten marine engineering stability and coastal safety. The propagation characteristics of landslide-generated tsunamis are therefore critical for hazard assessment. Physical model experiments provide an effective approach for investigating the underlying mechanisms of tsunami generation and propagation. To investigate the complete process from landslide motion to wave generation and propagation, this study developed an underwater soil-movement physical model test system. The system integrates controllable landslide initiation, real-time monitoring of landslide motion, wave height measurements, and full-field image acquisition, enabling synchronous observation of landslide movement and water body response. By controlling the main variables influencing submarine landslide dynamics, a series of physical model experiments were conducted to investigate water surface waves generated under different test conditions. The study examines the complete process from the initial water disturbance caused by submerged landslide motion to tsunami generation and propagation. The effects of landslide volume, particle size, initial submergence depth, and slope angle on tsunami parameters, including wave height, wave velocity, and wave period, were evaluated. Using 21 experimental datasets for each landslide type, namely, cohesionless sandy slides and muddy debris flows, empirical formulas for maximum surge height were established through dimensional analysis, SPSS (v25)-based multiple nonlinear regression, and validation against experimental results. The validation results show strong agreement between the empirical predictions and the physical model test data.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111015

Authors: Anthony S. Saaiby Mayur S. Patil Prabhakar R. Pagilla Sivakumar Rathinam HeonYong Kang

Autonomy in maritime operations has increased, especially through advancements in Maritime Autonomous Surface Ships (MASS). Despite technical progress, there’s a gap in understanding how human involvement affects safety during transitions between different levels of autonomy. Such transitions are crucial for MASS’s effective operation in mixed fleets of marine vessels across both near-port and open ocean environments. To address this, a hazard analysis framework using System-Theoretic Process Analysis (STPA) is proposed to systematically identify and prioritize critical factors influencing these transitions between human and autonomous agents in marine navigation under different levels of autonomy. The method involves: (1) assessing hazards and operation modes at different autonomy levels; (2) modeling the control structure involving human and autonomous agents; (3) identifying unsafe control actions (UCAs), their causes scenarios and critical factors; and (4) prioritizing critical factors by analyzing triggering events and systemic vulnerabilities from maritime incident reports. We apply this framework to Autopilot (an example of a MASS navigation function) between two ports, reviewing incident reports to uncover UCAs like delayed transition activations, alarm failures, and incorrect initiations by humans or machines. Our findings support the development of targeted safety recommendations to improve MASS navigation operations and are adaptable to other maritime functions.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111014

Authors: Jinxing Yu Sanming Song Liming Li Yuyang Lu Taofeng Wang Hairui Cao Jiaxin Dong Weilin Zang Adam Rushworth Bailu Si Miaomou Chen

Subsea Christmas trees are often deployed in turbid coastal waters or seabed environments. During manipulator operations on Christmas tree panels, conventional optical servoing is severely limited by rapid electromagnetic attenuation and strong scattering from suspended particles, resulting in reduced visibility. Forward-looking sonar (FLS) provides stable imaging, but its unique imaging geometry and low resolution make direct 6D pose estimation challenging. To address this issue, this paper proposes a 6D object pose estimation method for FLS images, in which conventional optical control-point-based pose estimation is restructured to resolve the mismatch between optical-centric network assumptions and acoustic imaging characteristics, and is further integrated with acoustic projection-based pose inversion. First, to address the limited diversity of target appearances and the scarcity of training data, we construct an FLS imaging model based on primary truncation for image simulation, providing data for model pretraining. Second, a multi-task acoustic control-point detection network, Acoustic-Yolo6D, is designed to mitigate localization degradation caused by heavy speckle noise, low boundary contrast, and resolution variations associated with polar-coordinate imaging, through heatmap regression, auxiliary object segmentation, and explicit range-bearing positional encoding. An Acoustic-n-Point (AnP) model is then used to recover the target 6D pose. Finally, simulation and water-tank experiments on the socket target verify the feasibility and robustness of the proposed method under limited-data conditions. The method achieves a 3.1 cm mean translation error, a 10.88° mean orientation error, and 52 FPS in real underwater acoustic environments.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111012

Authors: Wenbo Zhao Guocang Liu Qi Kong Yunlong Liu Yu Wang Jincheng Gao

In extremely shallow water environments, the limited water depth is comparable to the maximum bubble radius. The pulsation of an underwater explosion bubble is strongly constrained by both the free surface and the rigid seabed, exhibiting complex nonlinear coupling effects, which are of great significance for the safety assessment and protection design of nearshore engineering. To address this issue, an axisymmetric two-dimensional numerical model based on the Eulerian finite element method (EFEM) with operator splitting technique and the volume of fluid (VOF) interface-capturing approach is established. Under the assumptions of inviscid and compressible flow, a systematic numerical investigation is carried out to examine the effects of the water depth parameter λ, position parameter γ, and buoyancy parameter δ on the bubble dynamics and the evolution of free surface structures. The results show that the maximum bubble radius, pulsation period, and jet characteristics are all significantly regulated by the above three parameters. Moreover, under multi-period bubble pulsation, different parameter conditions lead to diverse evolution characteristics of free surface structures, including the water spike, wrinkles, and water skirt. The findings reveal the governing mechanisms of key dimensionless parameters on the nonlinear bubble-multi-boundary coupling dynamics in extremely shallow water explosions, providing an important numerical basis and theoretical reference for the theoretical analysis and safety design of related shallow water explosion engineering problems.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111011

Authors: Yingjie Liu Liwen Nan Qiaoling Gao Jiawang Chen Yuankun Chen Qinghua Sheng Lieyu Tian Chenlu Xu

Natural gas hydrates are regarded as a vital strategic energy resource for the future owing to their high energy density and clean combustion characteristics. To facilitate research into the physical and mechanical properties of pressure-maintained hydrate samples, this paper presents an integrated multi-parameter online analysis system capable of rapidly measuring the P-wave velocity, electrical resistivity, thermal conductivity, and shear strength of core samples under pressure-maintaining conditions. The system comprises hardware acquisition boards based on ZYNQ and ARM platforms, specialized measurement probes, and comprehensive data acquisition and analysis software. To mitigate the susceptibility of P-wave signals to noise interference, an improved denoising algorithm combining Empirical Mode Decomposition (EMD) and wavelet thresholding is proposed. By employing autocorrelation function analysis, the algorithm identifies the transition boundary between noise-dominated and signal-dominated Intrinsic Mode Functions (IMFs), subsequently applying wavelet soft-thresholding to the noise-dominant components. Experimental results demonstrate that the proposed algorithm achieves a superior signal-to-noise ratio (SNR) compared to traditional EMD methods, particularly under low SNR conditions. System validation indicates measurement accuracies of 3.2% for P-wave velocity at 20 °C, 1.76% for electrical resistivity at 25 °C, and within 7% for both thermal conductivity and shear strength. Furthermore, sea trials conducted aboard the “HAIYANG SHIYOU 708” drilling vessel confirm that the system operates stably and effectively fulfills the requirements for deep-sea core parameter characterization.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111009

Authors: Mohamed Hassan C. Guedes Soares

This study presents a comparative assessment of two installation methodologies, i.e., a conventional towing-based approach and the Nordic Wind installation concept, where fully assembled wind turbine generators are transported and installed using a dedicated installation vessel. A simulation-based logistics framework is developed to evaluate installation performance under realistic metocean conditions, incorporating operational limits, weather downtime, and vessel utilisation. The methodology combines response-based operability criteria with long-term hindcast data to quantify installation duration across multiple percentiles (P20, P50, and P90). The results show that both methods are sensitive to weather variability, with installation duration increasing significantly from favourable to adverse conditions. The Nordic Wind method achieves a substantial reduction in installation duration, typically of the order of 40–60%, primarily due to reduced offshore exposure and more efficient utilisation of workable weather windows. Under more challenging environmental conditions, both methods exhibit increased variability; however, the Nordic Wind method maintains shorter overall campaign durations. A time-dependent cost model demonstrates that installation duration is the dominant cost driver. Accordingly, the reduced campaign duration achieved by the Nordic Wind method leads to lower installation costs in most scenarios, while remaining competitive under more severe conditions. The proposed framework enables a consistent comparison of installation strategies by integrating operability analysis, logistics simulation, and cost assessment, providing a basis for optimising installation approaches in floating offshore wind projects.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111010

Authors: Qingyang Wang Junjie Lu Bin Yang Chen Jiao Tao Yue Bo Song Jianwu Jiang Guoqing Zhou Jingwen Li

Unmanned Aerial Vehicle (UAV) remote sensing images provide high-resolution and flexible monitoring data for oil spill detection. To address the high computational cost and low accuracy of traditional models, this study proposes an improved model, YOLOv8m-CGSE. The model replaces standard convolution with Group Shuffle Convolution (GSConv), substitutes the C2f module with SENetV2, and introduces a light-weight Cross-scale Context Fusion Module (CCFM) to enhance multi-scale feature representation while maintaining a lightweight structure. Mosaic augmentation was applied to the marine oil spill dataset, improving mAP50 and mAP50–95 to 85.4% and 62.0%, respectively. Based on YOLOv8m, the proposed YOLOv8m-CGSE achieved mAP50 and mAP50–95 of 91.2% and 73.3%, respectively, improving accuracy while reducing parameters by 16.1% and computational cost by 12.6%. Furthermore, a supplementary vulnerability test on highly deceptive oil-free sea surfaces demonstrated that the proposed model actively suppresses complex background clutter (e.g., ship wakes and wave anomalies), effectively reducing false positive detections from 21 (baseline) to 15. The results demonstrate that the proposed model effectively balances high precision, robustness against visual lookalikes and computational efficiency for real-time marine oil spill monitoring.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111008

Authors: Meng Zhu Jun Hu Yanan Zhang Enjin Zhao

The spatiotemporal evolution of seepage fields and the associated hydrodynamic risk of subsequent internal erosion pose a critical threat to the structural integrity of marine and hydraulic infrastructure. To quantify these complex fluid–solid interactions, this study develops a high-fidelity numerical model—coupling the Navier–Stokes equations with the Darcy–Forchheimer resistance model and the Volume of Fluid (VOF) method—to investigate transient hydrodynamics within porous foundations under complex geometric and geological boundary conditions. Parametric analyses reveal that spatial porosity distribution fundamentally dictates the system’s seepage capacity; notably, relocating a highly permeable stratum to the shallow sub-surface eliminates upper hydraulic bottlenecks and significantly escalates total volumetric discharge. Furthermore, the study systematically evaluates the hydrodynamic efficacy of multi-dimensional seepage control structures. Results demonstrate that while increasing the vertical depth of a cutoff wall is highly efficient in restricting bulk volumetric flux, it inadvertently induces intense localized streamline convergence and flow acceleration at the structural tip. Conversely, lateral expansion of the wall base, though yielding only a moderate reduction in total seepage, successfully diffuses this concentrated flow and substantially attenuates peak pore fluid velocities. Ultimately, a combined design paradigm is proposed for practical coastal engineering applications: prioritizing vertical penetration to optimize bulk seepage reduction, concurrently integrated with moderate lateral base expansion to redistribute concentrated hydrodynamic shear stresses, thereby minimizing the hydrodynamic potential for localized piping and ensuring long-term stability against seepage-induced degradation.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111007

Authors: Hyunsik Son Sanghun Lee Sanghwan Heo Weoncheol Koo

This study investigates the influence of data preprocessing techniques on the development of an artificial neural network (ANN)-based surrogate model for predicting the hydrodynamic coefficients of a two-dimensional rectangular barge. Conventional potential-flow-based numerical simulations are associated with high computational costs and time constraints, motivating the need for ANN models that can provide fast and efficient predictions. However, the predictive performance of ANNs strongly depends on the statistical characteristics of the training data. In this work, three types of input datasets—raw data, cube-root-transformed data, and Yeo–Johnson-transformed data—were used to train a representative multilayer perceptron (MLP) ANN model, and their prediction accuracies were systematically compared. The results show that models trained with preprocessed data consistently outperformed those trained with raw data across all hydrodynamic coefficients. In particular, for coefficients exhibiting strong nonlinear behavior, such as added mass and radiation damping coefficients, the Yeo–Johnson transformation yielded the highest prediction accuracy. The findings highlight the essential role of appropriate data preprocessing in enhancing the reliability and accuracy of data-driven predictive models in ocean engineering and provide a foundation for the development of robust surrogate models for high-dimensional engineering problems.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111006

Authors: Yan Zheng Wenhai Lu Hefeng Wang

Temperate seagrass carbon-stock data remain limited in northern China, especially for island meadow systems with mapped distribution and repeated field verification. This study quantified standing seagrass ecosystem carbon stocks in the Changshan Archipelago, Dalian, using a standardized field survey covering eight meadow zones, 39 sampling stations, and 323.37 ha of confirmed seagrass area. Plant biomass carbon and sediment organic carbon were assessed, and the 0–100 cm sediment profile was sampled at all stations. The mapped meadows stored 29,305.75 Mg C in total ecosystem carbon. Sediment organic carbon accounted for 28,965.71 Mg C, representing 98.84% of the total stock. Plant biomass carbon contributed 340.04 Mg C, or 1.16%. The area-weighted ecosystem carbon stock per unit area was 90.63 Mg C ha−1. This per-area stock ranged from 52.11 Mg C ha−1 in Xiaochangshan to 209.50 Mg C ha−1 in Haiyang Island. Guanglu Island contained the largest total carbon stock, with 9247.73 Mg C, because of its large meadow area and relatively high per-area carbon stock. The results show how mapped meadow area, sediment carbon dominance, and local sediment setting jointly shape regional carbon-storage patterns. This standardized baseline provides field-based evidence for comparing northern Chinese seagrass meadows with other temperate Zostera systems. The estimates describe standing ecosystem carbon stocks. Annual carbon sequestration rates were outside the scope of the assessment.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111005

Authors: Ming Xiang Luobin Wang Yankun Chen Kangrong Li Zhengqiao Zhao Jie Chen

Dolphins are widely recognized as intelligent marine mammals with sophisticated communication and echolocation. Accurately classifying their whistles is essential for understanding their communication patterns and monitoring their population size, structure, and distribution. In this study, we assembled a large, high-quality dataset of Indo-Pacific bottlenose dolphin (Tursiops aduncus) whistle signals collected at the Chimelong Ocean Kingdom. The dataset included multiple whistle categories, including a whistle type that has not previously been available for research. We then applied convolutional neural networks (CNNs) for classifying whistle signals, using five CNN architectures to analyze the signals. Model performance was evaluated using mean average precision (mAP), and the best-performing model achieved 0.929 in mAP on the test set, demonstrating that CNN-based approaches can effectively distinguish among different whistle classes. To probe robustness, we also introduced noise at defined SNR levels to increase testing complexity and assess the stability of the classifier. BELLHOP acoustic propagation modeling was used to generate channel impulse responses. These simulated signals were combined with the original signal data to construct an augmented training set. The results indicate that this augmentation enhanced the robustness of the classification model. Differentiating the whistle types is crucial as whistle categories may reflect variation in communication structure, behavioral context, or group-level acoustic patterns. Therefore, the proposed approach can support large-scale bioacoustic analysis and provide useful information for future studies on dolphin communication, behavior, and conservation.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111004

Authors: Zhenhua Ma Jianguang Qin

Aquaculture has long been a cornerstone of global food production, providing a significant source of seafood to meet the growing demand for animal protein [...]

Journal of Marine Science and Engineering doi: 10.3390/jmse14111003

Authors: Yonglin Guo Jingshi Ning Zhengchao Wu Qian P. Li

Microzooplankton grazing is a key regulator of phytoplankton standing stock and the export of particulate organic carbon (POC) in the ocean, yet its spatial coupling with phytoplankton growth across shelf-basin gradients remains underexplored in marginal seas. Using 43 dilution experiments in the South China Sea (SCS), this study systematically examined the spatial variability and environmental drivers of phytoplankton growth rate (μ) and grazing mortality rate (m) as well as the resulting grazing impact (m/μ) across shelf, slope, and basin habitats. Results show a significant seaward decline in m (shelf: 0.73 ± 0.53 d−1; basin: 0.27 ± 0.19 d−1; p < 0.01), while μ decreased non significantly (shelf: 0.88 ± 0.53 d−1; basin: 0.70 ± 0.18 d−1; p = 0.49). Consequently, growth and grazing were strongly coupled on the shelf (r = 0.82, p < 0.01) but completely decoupled in the basin (r = 0.21, p = 0.46), coinciding with a shift toward picophytoplankton dominance and reduced grazing pressure. We also found that export efficiency was positively correlated with both m/μ and m, highlighting the important role of microzooplankton grazing in carbon export, but that the overall carbon export flux itself was also shaped by nutrient-driven changes in POC recycling. These findings underscore the role of bottom-up nutrient forcing and top-down grazing impact in controlling carbon export in the SCS.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111002

Authors: Jisheng Ding Fengbiao Jiang Fangqi Wang Long Yang

The topographic features of the seafloor can be observed clearly via high-resolution side-scan sonar imagery. However, the faithful interpretation of a sonar image depends strongly on the accuracy with which the location of the sea bottom line can be tracked within the image, and current tracking methods function poorly under high sonar signal noise or suffer from high complexity. The present work addresses this issue by applying the characteristics of simple sonar waterfall maps in conjunction with robust edge detection and multi-scale analysis based on wavelet transform modulus maxima. The proposed tracking method is demonstrated to provide superior effectiveness and accuracy in comparison with existing baseline methods based on the results of experiments conducted with a representative side-scan sonar image with and without applied speckle noise. This superiority can be attributed to the good localization characteristics and multi-scale detection features of wavelet transform analysis, which can suppress the impact of noise in the sonar image on the accurate extraction of edge information.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111001

Authors: Xiang Li Yuming Cao Neven Alujević Zili Zhang

An efficient hybrid modeling framework is developed for the dynamic analysis of offshore wind turbines (OWTs) by coupling an aero–servo–elastic rotor–nacelle superelement with a hydroelastic substructure. The complex rotor–nacelle dynamics are condensed into a reduced-order 14-DOF representation through a modal-based multibody formulation, while retaining blade deformation, spinning effects, nonlinear aerodynamic loading, and active servo controls. Its interface compatibility at the nacelle enables the coupling with either numerical or physical substructures, establishing a unified basis for system hybrid formulation, co-simulations, and real-time hybrid simulations. The validity of the superelement is verified by comparing the resulting fully coupled modal model against OpenFAST, demonstrating high consistency in time-domain responses. As a demonstration, the verified superelement is further coupled with a 1D finite element model of the supporting structure (tower–monopile substructure) to form a hybrid model, enabling accurate force analysis of the OWT structure. Dynamic analyses of the IEA 10 MW OWT reveal that while the blade flapwise responses and the operation-related edgewise responses are 1P-dominated, tower side–side responses and idling-related tower fore–aft and blade edgewise responses manifest at their corresponding resonance frequencies. The maximum displacement and maximum bending moment envelopes vary monotonically with height. Instead, the maximum stress envelope possesses high values in the mid-lower sections of the tower. This high-stress region undergoes a spatial shift driven by the blade feathering mechanism.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110999

Authors: Zaid Al-Husban Jack A. Puleo

Beach cusp geometry arises from coupled hydrodynamic and morphodynamic feedback in the swash zone. This study used the numerical model XBeach in nonhydrostatic mode to examine cusp development on an idealized sandy beach forced by monochromatic, bichromatic, and band-limited irregular waves. Simulations systematically varied foreshore slope (tan β = 0.05–0.15), wave period (8–12 s), and wave height (0.4–0.8 m), while grouped and irregular cases isolated the effects of infragravity modulation and spectral bandwidth. Under monochromatic forcing, cusp spacing increased primarily with wave period and foreshore slope, whereas wave height played a secondary role. Cusp spacing scaled strongly with horizontal swash excursion, supporting self-organization. Grouped and band-limited forcing increased shoreline excursion but weakened the direct proportionality between cusp spacing and swash excursion, indicating the temporal organization of forcing modulated pattern evolution. Across monochromatic, bichromatic, and irregular cases, spectral diagnostics did not show dispersion-aligned energy consistent with edge-wave forcing. The results support the interpretation of beach cusps as predominantly swash-driven, self-organized features whose geometry is controlled by slope and incident-wave timescale and modulated by spectral structure.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110994

Authors: Meiyao Chu Yifei Wu Ruijie Kong Yong Fang Yuan Kong

Accurate forecasting of significant wave height (WVHT) is essential for marine disaster prevention, offshore operations, and coastal management. However, WVHT time series typically exhibit strong nonlinearity and non-stationarity, which pose significant challenges for reliable prediction, especially under complex sea conditions. To address these issues, a hybrid forecasting framework based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and the iTransformer model is proposed for the North Atlantic Ocean. In the proposed method, the original WVHT time series is first decomposed into multiple intrinsic mode functions using CEEMDAN to alleviate non-stationarity and reveal multi-scale characteristics. Subsequently, the iTransformer model is employed to capture the temporal dependencies of each decomposed component, and the final prediction is obtained through reconstruction. Experiments are conducted using multi-variable buoy observations from the North Atlantic, incorporating meteorological and oceanographic factors. Results demonstrate that the proposed CEEMDAN-iTransformer model significantly improves forecasting accuracy and stability compared with baseline models across multiple prediction horizons. The framework shows strong capability in handling complex wave dynamics and provides an effective solution for high-precision WVHT forecasting.

Journal of Marine Science and Engineering doi: 10.3390/jmse14111000

Authors: Joar Dalheim

Industry has for a long time aspired to a dynamic QRA (quantitative risk analysis), but due to the complexity of the traditional scenario-based risk analysis, it has not been practicably possible to perform fast enough analyses for real-time risk updates. As an analogy, if the speedometer had required several hours to calculate the speed of a car, it would never have become the valuable and mandatory risk management tool it is for all car drivers today. A completely new approach to QRAs has now rendered real-time risk updates a reality for industry, both for onshore plants and for offshore facilities. The new modal risk analysis represents a technical solution offering real-time QRA calculations, even for the largest and most complex facilities. A pilot version of the modal QRA has been developed and tested, and the modal risk updates are seen to be both real-time and sufficiently accurate for expedient risk-based decision-making. The new modal QRA can disruptively change the way we understand and manage the risk of our facilities.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110997

Authors: Nicolas Aleman Franck Levoy Edward J. Anthony Luc Hamm

Human modification of tidal embayments, estuaries, and deltas through polders, dykes, and embankments has profoundly altered sediment dynamics and coastal morphology worldwide. Mont-Saint-Michel Bay (northwestern France) exemplifies a macrotidal system affected by large-scale land reclamation, accelerated infilling, rapid saltmarsh expansion, and progressive loss of the insular character of the World Heritage abbey. To restore its maritime setting, a large-scale restoration programme initiated in the 1990s combined engineering measures with nature-based management, including embankment removal, managed retreat, and controlled hydraulic flushing. Future morphodynamic evolution was initially assessed using a movable-bed physical model complemented by numerical simulations. Here, a 22-year LiDAR dataset is used to quantify post-restoration topographic changes and sediment budgets, and evaluate model performance. The results show enhanced erosion and deepening of tidal flats around Mont-Saint-Michel, indicating effective sediment export, together with spatial redistribution of salt marshes that maintained the overall ecological value of the bay. Discrepancies between model predictions and field observations reflect both the difficulty of reproducing long-term channel migration variability and evolving hydro-meteorological forcing conditions, as well as differences between the initially modelled restoration scheme and the engineering works ultimately implemented. This study provides a rare multi-decadal comparison between pre-project morphodynamic forecasts and post-restoration observations. The results highlight both the potential and the limitations of long-term morphodynamic forecasting in non-stationary tidal systems undergoing anthropogenic modifications and climate-driven environmental change, emphasising the importance of long-term monitoring and adaptive management strategies.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110998

Authors: Jianping Yuan Lei Wan

Target detection in complex marine environments serves as a core technology for marine environmental monitoring, underwater search and rescue, and vessel collision avoidance. However, traditional detection methods struggle to accurately identify low-pixel marine targets (e.g., small vessels, buoys) while balancing detection accuracy and computational efficiency in complex environments. To address the low accuracy and high computational costs of object detection in complex marine environments, this paper proposes YOLO-ELR, a lightweight model based on the YOLOv11 framework, designed to identify object categories and directional positions with enhanced precision while optimizing resource efficiency. The Efficient Multi-Branch Scale and Light Adaptive-weight downsampling (EMBSLaw) backbone network enhances multi-scale object detection in complex scenes by dynamically adjusting feature contributions through adaptive weight computation, while maintaining a lightweight architecture. To reduce computational parameters and complexity, a novel lightweight spatial multi-branch detector Lightweight Shared Convolutional Separamter BN Detection head (LSCSBD) is introduced. Furthermore, the RepGhostCSPELAN and Efficient Multi-Scale Conv (RGCEL_EMSC) module, integrating multi-neural networks, is proposed to improve detection accuracy and precision. Experimental results demonstrate that the YOLO-ELR model achieves an mAP@50 of 84.87%, surpassing the baseline YOLOv11 by 3.94% while reducing parameters by 35% and GFLOPs by 7.56%, which validates the effectiveness in balancing detection accuracy and computational efficiency.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110996

Authors: Roberto Zivieri Vincenzo Crupi

In this work, the underwater acoustic signatures of marine vessels are investigated, with a focus on the impacts of methanol-based high-temperature proton exchange membrane fuel cell (HT-PEM FC) propulsion systems and their coupling with structural dynamics. The acoustic field is modeled through a monopole–dipole representation directly linked to the vibration and dynamic response of the vessel structure and propulsion units. The model is validated against experimental sound pressure level (SPL) data as a function of depth, showing excellent agreement: the SPL decreases from about 140 dB at 5 m to approximately 120 dB at 50 m, where the model prediction (119 dB) closely matches the experimental value (121 dB). Representative numerical results indicate the suppression of the monopole component for the HT-PEM FC and a reduction in the dipole pressure amplitude by approximately a factor of 19 relative to the diesel engine (DE) configuration. In the 20–100 Hz band, at r=10 m, the acoustic pressure amplitudes range from O(101−102) Pa for the diesel engine (DE) to O(100−101) Pa for the HT-PEM FC, while, at r=105 m, they decrease to O(100−101) Pa and O(10−1−10−2) Pa, respectively. The absolute levels depend on the assumed structural excitation and vibro-acoustic coupling and are mainly used here to quantify the relative reduction achieved by the HT-PEM FC with respect to the DE. A distance-normalized formulation is introduced to account for geometric spreading, enabling a consistent comparison despite differences in source characteristics. Overall, the proposed framework establishes a direct link between structural vibrations and underwater radiated noise and provides a physically consistent and quantitatively validated approach for the design of low-signature marine propulsion systems.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110995

Authors: Chunyu Zhang Jianan Zhao He Yang Yaqiang Xue Zilong Peng

The rim-driven thruster (RDT) adopts a shaftless design, thus eliminating the mechanical excitation and frictional noise caused by shaft movement. In this study, dynamic and noise prediction models of the composite-material RDT have been developed, and numerical examples are given to study the characteristics of radiated-noise RDTs. Studies have shown that the layup method of composite materials has a significant impact on the natural frequency of the blade’s free vibration and further affects the spectral characteristics of the RDT flow-induced noise. In the low-frequency range, the flow-induced load has not yet caused the blade to vibrate, and the noise is mainly hydrodynamic noise. As the frequency increases, the blade starts to vibrate, and a distinct flow-induced vibration spectral pattern is observed. Compared with metal blades, composite material blades can effectively suppress the amplitude of the flow-induced noise spectrum and reduce the total noise of the propeller. The composite RDT generally exhibits lower noise levels than the metal RDT, with a difference of approximately 10 dB observed at the resonance frequency. By comparing the three RDTs with different fiber layer-ups, it can be observed that the fiber-laying angles have a direct impact on the resonance characteristics of the blade and its flow-induced noise. It can be concluded that composite materials have significant potential in the low-noise design of RDT, and a reasonable layup design of the blades can achieve excellent noise-control effects.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110993

Authors: Liang Huang Jianhua Miao Haishao Chen Xiaojun Mei Zhongdai Wu Feng Wang Yuxuan Zhang

The accurate prediction of Arctic sea ice concentration is essential for polar ecological protection and shipping safety. However, existing prediction methods suffer from insufficient feature representation, which limits their ability to capture the complex spatiotemporal distribution of sea ice. Furthermore, they cannot effectively integrate multi-source, heterogeneous sea ice-related data, resulting in limited prediction accuracy. To address these issues, this paper proposes a Multimodal Feature and Trend analysis (MFT) method for sea ice concentration prediction. In the feature extraction stage, MFT combines a Convolutional Neural Network with a Convolutional Block Attention Module to deeply extract global deep semantic features while also employing the Scale-Invariant Feature Transform algorithm to accurately capture local stable features. To improve processing efficiency for high-dimensional remote sensing data, a coarse-resolution dimensionality reduction strategy is developed to select core spatial features, thereby preserving key spatial distribution information while optimizing computational efficiency. For temporal analysis, the Mann–Kendall (MK) non-parametric test and Sen’s slope method are integrated to quantitatively analyze long-term evolution trends in Arctic sea ice concentration. Experimental results show that the proposed MFT model outperforms random forest (RF), LSTM, and traditional MK methods in both prediction accuracy and computational efficiency.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110992

Authors: Tingting Wu Laihe Qi Yaxin Liu Pu Wang Lijian Li Shuai Li Xingxing Wang

Pipeline intelligent plugging robots (PIPRs) are used for in-line isolation and emergency repair of oil and gas pipelines. During anchoring, slip teeth contact the inner pipe wall. This contact causes stress concentration, microslip, and local wear. Pipe wall wear may reduce pipeline service life and plugging reliability. This study proposes a wear-response-based optimization method for slip structure design. A simplified slip–pipe contact model was established. Wear depth was selected as the main response. Five slip structural parameters were used as design variables. The Box–Behnken Design (BBD) model was constructed to describe the relationship between structural parameters and wear depth. The Ant Lion Optimizer (ALO) model was introduced to search for the minimum-wear parameter combination. Contact stress and local deformation were used as auxiliary indicators for structural safety evaluation. Experimental tests were conducted to verify the simulation and optimization results. Strain-derived stress and wear scar morphology were compared with the numerical results. The results show that the optimized structure reduces the minimum wear depth to 0.045 mm. The experimental results agree with the simulation trend. This indicates that the proposed method can reduce pipe wall wear while maintaining anchoring reliability. The BBD–ALO framework provides a general optimization method for contact structures with wear constraints. This method can be applied to anchoring, gripping, and support structures in pipeline robots and other mechanical systems.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110991

Authors: Mayao Cheng Hongzhen Zhou Zhuang Jin

Scour around monopile foundations is a pivotal challenge in nearshore engineering, as it undermines sediment support and threatens structural stability. This study systematically investigates the dynamic evolution of scour under four distinct flow regimes—steady, sinusoidal, pulsatile, and irregular—coupled with varying pulsation frequencies (39, 69, and 100 Hz). Utilizing a laboratory flume and underwater high-resolution imaging, near-pile flow velocities and morphological development were monitored in real time. Results indicate that the pulsation frequency, acting as the primary energy input, dictates the ultimate scour scale and acceleration. Three distinct evolutionary modes are identified: “gradual advancement” at 39 Hz, “ Rapid development phase” at 69 Hz, and “instantaneous stabilization” at 100 Hz. Higher frequencies concentrate energy release into the incipient stage, drastically shortening the duration to reach equilibrium. Morphological analysis reveals that equilibrium scour shapes are highly regime-dependent, manifesting as teardrop (steady), elliptical (sinusoidal), pronouncedly elliptical (pulsatile), and semi-circular (irregular) configurations. While scour dimensions generally scale with frequency, their sensitivity is governed by the flow regime; Constant Current Flow exhibits the highest volumetric vulnerability, whereas pulsatile flow demonstrates the greatest morphological stability. These findings provide a theoretical framework for predicting scour geometry in complex marine environments and optimizing foundation protection strategies.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110990

Authors: Hui Liu Jiayi Chen Zhaochen Zhu Jing Wang

Vortex-induced vibration (VIV) is the main cause of fatigue failure in steel catenary risers (SCRs). This study developed a fluid–structure interaction (FSI) model, combining Reynolds-Averaged Navier–Stokes (RANS)-based computational fluid dynamics (CFD) with the Newmark-β algorithm, to simulate VIV responses under ocean currents and platform heave motion. First, the FSI model analyzed SCR behaviors under steady currents, then was adapted to oscillatory flow mimicking heave motion. A finite element model (FEM) was built, using the simulated VIV response as displacement boundary conditions to compute the equivalent stress time history along the riser. Finally, Miner’s rule was applied to quantify fatigue damage in three scenarios: current-only, heave-only, and the combined action of both factors. The results indicate that, in the South China Sea’s 10-year return period sea state, the SCR experiences a broad vortex-induced resonance interval under ocean current loads, with a maximum vibration amplitude of 0.7D. At the associated resonant height, platform heave motion triggers near-complete lock-in of the SCR’s VIV. The peak fatigue damage induced by ocean currents alone, platform heave motion alone, and their combined action all concentrates at the riser touchdown point (TDP). Over the 600 s VIV response duration, fatigue damage from platform heave motion alone constitutes 8.48% of that caused by ocean currents alone, while the combined action results in fatigue damage 1.847 times that of ocean currents alone. Thus, the combined action significantly amplifies both the magnitude and spatial non-uniformity of VIV-induced fatigue damage in SCRs.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110989

Authors: Zhiyong Zhang Youxiang Lu Jinlong Zhang Jin Xu Guodan Zheng Chunyang Xu Kun He Gang Chen Yuanping Yang

Local scour around offshore wind turbine foundations is a common engineering challenge. It changes the hydrodynamic loads and affects the foundation’s load-bearing capacity. This study investigates the field scour characteristics and wave–current force characteristics under local scour effects using field data, physical modeling, and numerical simulations. The results show that the field scour hole slope is more gradual than that observed in laboratory settings, and Zhang’s scour depth equation proves more accurate for practical engineering. In addition, under wave–current conditions (Keulegan–Carpenter number, 2 < KC ≤ 15), the relative maximum post-scour wave–current force increases with the relative post-scour water depth but decreases as the KC rises. An equation is developed to predict the relative maximum post-scour wave–current force. This provides key insights for improving load assessments of offshore wind foundations on scoured seabeds.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110988

Authors: Chao Li Yudong Feng Yuliang Zhao Xin Ma

Environmental condition assessment is essential for the design of floating wind turbines, particularly when determining design sea states that balance safety and economy. The environmental contour method, typically constructed through the Inverse First Order Reliability Method combined with parametric joint distributions, is widely adopted for this purpose. However, conventional models often struggle to adequately characterize complex sea states involving mixed wind and swell systems, which exhibit multimodality and irregular dependence structures. To address this limitation, this study applies the use of Gaussian mixture models (GMM) to construct environmental contours. The GMM-based approach models the joint distribution of environmental variables in a flexible and data-adaptive manner, with the number of mixture components determined by the Bayesian Information Criterion and model parameters estimated via the expectation-maximization algorithm. Compared with the conventional conditional Weibull–Lognormal model, the GMM significantly improves fitting accuracy: the RMSE decreases from approximately 0.06 to below 0.0013, and the R2 increases to nearly 1.000 across all three datasets. The KS and χ2 tests confirm that the GMM adequately fits the observed data at the 0.05 significance level, whereas the baseline model is rejected in several cases. For the 100-year return period, the GMM yields maximum significant wave heights of 4.19–4.55 m with associated peak periods of 18.8–20.3 s, while the baseline model gives 4.02–4.18 m and 14.3–14.6 s, respectively. These quantitative improvements demonstrate that the mixture-based contours capture the intricate characteristics of wind–swell coexisting sea conditions more accurately, leading to enhanced representativeness of extreme sea states. Consequently, the adopted method enables more refined and reliable design sea state assessments for tested datasets, contributing to the optimization of environmental parameter selection for floating wind turbines.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110987

Authors: Xuan Li Jinlei Mu Yuan Zhang Yuchen Hu Fuyu Yan

The residual ratio of ultimate bending moment is a critical indicator for hull structural safety assessment of damaged ships. In maritime emergency scenarios, the empirical formula method has insufficient prediction accuracy, while nonlinear finite element (FE) simulation bears prohibitive computational cost. To address this limitation, we propose a rapid surrogate model for predicting the residual ultimate bending moment ratio of side-damaged ships. The model integrates a lightweight one-dimensional U-Net (1D U-Net) for nonlinear feature extraction and multi-scale feature fusion and a fuzzy inference module for embedding engineering prior constraints. Trained on a 1D structured dataset generated via the modified Smith method (covering multiple damage conditions, hogging and sagging), the model achieves an overall mean absolute error (MAE) of 1.79% and root mean squared error (RMSE) of 2.39% on the test set. It outperforms empirical formulas in accuracy with ultra-short inference time, far lower computational cost than FE simulation, and provides engineering interpretability via activated fuzzy rules. This work offers an efficient alternative tool for rapid safety assessment of damaged hull structures.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110986

Authors: Sung-Hyub Ko Hyunjoon Cho Daehyeong Ji Jong-Wu Hyeon Seom-Kyu Jung Joon-Young Kim

Underwater gliders are suited for long-duration oceanographic observation, but their endurance is bounded by onboard energy capacity. An overlooked source of energy loss is the attitude control system, which repeatedly repositions the internal moving mass to hold the desired pitch angle throughout each gliding cycle. Conventional PID and manually tuned fuzzy controllers continue driving the actuator after pitch convergence and adapt poorly to nonlinear buoyancy variations at depth. To address this, we propose an ANFIS (Adaptive Neuro-Fuzzy Inference System)-based pitch control strategy for a 1000 m-class underwater glider. A nonlinear 6-DOF dynamic simulator incorporating experimentally derived power models for the buoyancy engine and attitude controller was validated up to 100 bar. A 13-rule Sugeno-type fuzzy inference system was optimized through ANFIS hybrid learning using approximately 5500 samples from PID steady-state data. Simulation results show energy savings of 57.05% over PID and 4.98% over a manually tuned fuzzy controller, with no degradation in tracking accuracy. Sea trials confirm a reduction in moving mass displacement under real disturbance conditions, providing qualitative evidence consistent with the simulation results. Further quantitative validation of the energy reduction effect through free-running sea trials remains as future work.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110985

Authors: Wenbo Zhu Bingzhen Yu Bin Lin Yonghai Li Shi Ouyang Guoliang Dai

The suction caisson foundation has been extensively adopted for offshore wind turbine infrastructure owing to its adaptability to deep-water environments, cost-effectiveness, and convenient construction. However, such foundations suffer from relatively low horizontal and vertical bearing capacities when embedded in soft clay deposits. To address this limitation, this study proposes a novel mobile jet-reinforcement technique and the corresponding composite suction caisson configuration. Physical model tests are conducted to investigate the soil fracturing-erosion mechanism induced by jet injection and the bearing performance of the reinforced composite foundations. Test results reveal that the soil breaking depth increases with injection pressure and injector diameter, whereas the soil breaking width increases with jet angle. Larger breaking depth and width contribute to an expanded horizontal–vertical bearing capacity failure envelope. The ultimate bearing capacity of the composite caisson increases with greater soil breaking depth, and a larger number of circumferentially arranged jet pipes enables more uniform cement–soil cladding around the caisson body. Overall, the reinforced foundations achieve a bearing capacity 3.0–5.0 times that of conventional unreinforced suction caissons. Furthermore, a time-dependent hyperbolic model for soil breaking depth prediction and a bearing capacity failure envelope method are established for the reinforced composite suction caissons. The outcomes of this study can provide a reference for the engineering design of jet-reinforced suction caisson foundations in offshore areas with soft clay.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110984

Authors: Maria Anna Cusenza Maria Leonor Carvalho Giovanni Dotelli Pierpaolo Girardi

Battery-based electrification is increasingly recognised as a key pathway for reducing greenhouse-gas emissions in maritime transport, particularly for vessel segments characterised with short, predictable operation profiles. To ensure an environmentally sustainable transition, it is essential to quantify the potential environmental benefits of these solutions. Life Cycle Assessment (LCA), standardised by ISO 14040 and ISO 14044, is the internationally recognised methodology for evaluating environmental impacts across the entire life cycle and for consistently comparing options providing the same function. This study presents a methodological review of LCA applications to battery-based ship electrification, with the objective of analysing key assumptions, comparability issues, and limitations across the existing literature. A systematic review was conducted on 24 studies, focusing on core methodological aspects, including product system definition, functional unit selection, system boundaries, life cycle inventory modelling, and impact assessment methods, while considering contextual elements such as fleet segmentation and propulsion configurations to support the interpretation of methodological choices. The analysis reveals significant methodological heterogeneity across studies, particularly in product-system definitions, functional unit selection, modelling detail, and impact category coverage, which limits cross-study comparability. This review also highlights a strong concentration of applications on short-route passenger ferries, while other vessel categories remain underrepresented, further constraining the generalisability of the findings. Although a direct quantitative comparison of results is not methodologically appropriate due to this heterogeneity, climate change mitigation consistently emerges as a key benefit across the analysed studies. At the same time, the multi-impact perspective of LCA highlights relevant trade-offs related to material use, toxicity, and resource depletion. Overall, the findings underline the need for more harmonised methodological approaches and a holistic life cycle perspective to support robust and comparable environmental assessments as battery-based solutions expand within the maritime sector. This review provides a structured interpretation of methodological variability and identifies priorities for future LCA applications.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110983

Authors: David Escribano Arias Daniel Gomez-Lendinez Beatriz Navas de Maya Christian Velasco-Gallego

When accidents occur, official investigations are carried out, and reports are generated, which are usually reviewed for safety improvements. The retrieval of information is typically performed manually, which can lead to biases, errors, and poor judgement. Moreover, manual reviews can be tedious and highly time-consuming tasks. For these reasons, the implementation of LLMs has been analysed in this context. However, previous studies have been limited, and no proper justification for the implemented LLMs has been provided. Consequently, this work proposes a comparative framework to assess LLM candidates across two main dimensions: cybersecurity and performance. Specifically, a total of 9 LLMs from different providers were analysed, and 18 prompt injection techniques were implemented across 7 categories based on OWASP LLM01:2025 and previous academic studies. Additionally, a RAG system based on these results is introduced to validate the potential of these models in supporting experts in the retrieval of information from maritime accident reports. For validation purposes, a case study on the Marine Accident Investigation Branch (MAIB) reports was conducted. Results show that a comparative framework is required, as model selection may vary depending on the task being performed, which is critical from both a performance and cybersecurity perspective.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110982

Authors: Huan Wu Shijian Zhou Fengwei Wang Tieding Lu

This study introduces a novel fusion deep learning framework that integrates a convolutional neural network (CNN), a bidirectional gated recurrent unit (BiGRU), and a self-attention (SA) mechanism to address the shortcomings of conventional linear models in modeling and predicting nonlinear dynamics of sea level changes. To further enhance model adaptability and performance, the Dream Optimization Algorithm (DOA) is incorporated to enable hyperparameter tuning, resulting in the DOA-CNN-BiGRU-SA framework, which significantly improves the model’s ability to predict nonlinear sea level time series. To mitigate the impact of randomness in neural network initialization, we initially employed a default random seed and conducted experiments with data from five tidal stations in Japan. The DOA-CNN-BiGRU-SA framework outperformed seven other relevant models. Subsequently, an extended evaluation was carried out using data from six additional tidal stations, with predictions generated across 30 different random seeds, confirming the model’s competitive accuracy and robustness. Finally, the proposed framework was applied to satellite altimetry data over the entire East and South China Sea region. Two distinct processing strategies yielded regional sea level rise trends of 3.96 ± 0.47 mm/year and 4.02 ± 0.47 mm/year, respectively, over the 1993–2023 period, and these results closely agree with those reported in the China Sea Level Bulletin report in 2023. This paper presents an integrated approach that enables joint optimization of deep learning architectures and investigates the effects of initialization randomness in neural networks, offering a robust technical solution for predicting short-term regional sea level changes.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110981

Authors: Qinglei Zhang Binwei Ye Ying Zhou Jiyun Qin Jianguo Duan

Vessel traffic service systems in remote or newly established maritime regions face significant operational limitations due to the scarcity of historical AIS data, which undermines the reliability of trajectory-based situational awareness and collision risk assessment. Existing deep learning models, predominantly validated on data-rich major shipping corridors, suffer severe performance degradation under cross-domain deployment, rendering them impractical for vessel traffic management in underserved waters. To bridge this operational gap, this study proposes a Boundary-Aware Distillation and LoRA-Based Transfer (BD-LT) framework that enables reliable trajectory prediction with as few as 132 target-domain trajectories. The framework integrates HDBSCAN-based geographic-semantic domain partitioning, a Time-Aware Transformer with Time2Vec encoding for irregular AIS sampling, hybrid knowledge distillation with error-boundary gating for selective cross-domain transfer, and LoRA-based parameter-efficient adaptation to mitigate overfitting. Validated on NOAA full-scale AIS measurements, the framework reduces the 60 min Final Displacement Error by 35.2% relative to the no-framework baseline, consistently outperforming state-of-the-art models across all prediction horizons, with statistical reliability confirmed via bootstrap resampling. These results demonstrate the practical feasibility of deploying data-driven trajectory prediction in maritime regions where conventional approaches have historically been inapplicable, with direct implications for collision avoidance decision support and port approach traffic management.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110979

Authors: Gemma Aiello

Seabed studies are a valuable tool in the investigation of active continental margins, both in volcanic and sedimentary settings. Being an example of a slope-confined sedimentary basin, the “Ammontatura” slope basin has been discussed using multibeam bathymetry and seismo-stratigraphic data matched with previously available cores. Being a significant tectonically controlled slope bounded by the Capri-Sorrento regional fault, the southern slope of the Sorrento Peninsula has been explored employing a dense network of bathymetric profiles. The data have shown the underwater extension of the mainland drainage system, comprising a dense network of submarine gullies, reflecting the onshore drainage system. The northern Ischia debris avalanche deposits have been studied through seismo-stratigraphic data, previously unpublished, whose geologic evolution has been placed within the Quaternary stratigraphic framework of Ischia. This research revealed how several geological events, such as the tectonic phases, the emplacement of erosional and depositional domains, the volcanic eruptions, and the reworking of volcanic deposits, interacted in controlling the sedimentary structure of slope basins. In the Ammontatura slope basin, the tectonic setting has probably controlled its emplacement along a NE–SW trending regional fault, resulting from the submarine prolongation of the Sarno-Sebeto normal fault, while intense reworking of volcaniclastic deposits acted as the main control factor in slope settings.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110980

Authors: Youli Shen Lihong Peng Shaofei Wang Xiaofei Wang Zaijin You Hongyuan Shi

Nourishment grain size is a key parameter in beach nourishment projects, directly determining beach stability under extreme hydrodynamic environments. Taking Xiaoshizui Beach on Wailingding Island as the study area, this paper establishes a coupled typhoon storm surge–wave–sediment model based on the MIKE 21 HD-SW-ST coupled model. This model has been systematically verified through the measured data of tide levels, waves, and beach profiles, and the verification results are satisfactory. Four scenarios with nourishment grain sizes of 0.4, 0.6, 0.8, and 1.0 mm were established to quantify the morphological evolution patterns of the beach under strong typhoons. The results indicate that during the typhoon, the beach exhibits a cross-shore sediment transport pattern characterized by erosion of the backshore dune, accretion of the upper-middle foreshore, and erosion of the lower foreshore. The influence of nourishment grain size shows significant spatial variability: increasing grain size enhances the erosion resistance of the backshore and berm, reducing the erosion extent; however, within the breaker zone, coarse sand tends to form a steep profile, intensifying wave breaking, which increases the scour depth in this region. This study elucidates the regulatory mechanism of grain size under extreme conditions, providing scientific reference for grain size selection in beach restoration projects.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110978

Authors: Fangshi Zhang Guoliang Jin Baozhu Jia Huihu Lu

To meet the requirement for high-precision dynamic positioning of fully actuated vessels under wave-frequency disturbances, and to achieve clock-synchronous triggering for system analysis, decision-making and reliable communication, this paper proposes a minimum-time simultaneous triggering (MTST) scheme based on a modified self-adaptive observer. Firstly, the concepts of result-dependent event (RDE) and conflict are introduced to describe the internal coupling characteristics of the system and the continuous actuation behavior under the superposition of triggering signals. Then, for the estimation of yaw perturbation, a self-adaptive parameter algorithm is employed in the modified observer, whose stability is subsequently proven. To reduce channel occupancy during the cooperative transmission of distributed triggering signals, a multi-port scheme is proposed, including RDE, and a corresponding controller is designed. Furthermore, to avoid the computational explosion phenomenon and estimate complex nonlinear unknown terms, the dynamic surface method and radial basis function neural network are used in filtering and function approximation, respectively. Finally, theoretical derivations show that the multi-port processing ensures the stability of all system nodes without the Zeno phenomenon. Meanwhile, the MTST scheme also maintains system stability while effectively eliminating both the Zeno phenomenon and signal conflict. Numerical simulation results reveal that compared with the multi-port event-triggering (MET) scheme, the MTST scheme achieves performance improvements of 9.76%, 0.37%, and 43.15% in tracking precision, energy efficiency, and control smoothness, respectively, which demonstrates its prominent advantages in event-triggered control systems. While improving positioning accuracy, the scheme exhibits a slight slowdown in heading-direction convergence and introduces a heavier communication load. These characteristics reflect a fundamental trade-off: the MTST scheme provides superior control performance at the cost of an increased triggering frequency and greater communication overhead.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110977

Authors: Yutao Li Laidi Li Bin Zhang Jiasheng Jiang Jieyu Shuai

Building underground water-sealed oil storage (UWSOS) caverns on islands poses a potential risk of seawater intrusion. As UWSOS is mostly constructed within rock masses, research on seawater intrusion through rock fractures holds important engineering value. This study combines single-fracture model tests with numerical simulations to investigate patterns of seawater intrusion in fractured rocks. Results show that, due to the density difference between seawater and freshwater, a saltwater wedge forms in coastal zones. Under tidal action, an upper saltwater plume forms in the intertidal zone, with its scale positively correlated with tidal range. After cavern excavation, the saltwater–freshwater transition zone widens, and seawater gradually intrudes from the cavern bottom. The upper saltwater plume evolves into a “saltwater tongue” during intrusion, with a growth rate ranging from 921.89% to 5691.52%, while the lower saltwater wedge moves landward by 37.86% to 82.65%. The saltwater tongue scale increases with tidal amplitude, but the lower wedge scale shrinks. With the horizontal water curtain installed, the saltwater wedge area decreases by 45.42% to 57.33%; in contrast, installing a vertical water curtain can effectively block seawater intrusion. These results provide an important experimental foundation for seawater intrusion research in island UWSOS caverns.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110976

Authors: Lifu Fu Chunling Zhang Yijun Ge Bo Shu Ruoxiao Zhou

Based on the large volume of observational data obtained from Argo and several satellites, an increasing number of datasets are being developed and applied to oceanographic research. However, there are still problems such as sparse subsurface observations, insufficient parameters, and weak pertinence. This study provides a basic framework for high-resolution data fusion that focuses on the multi-source observations in the Western North Pacific. Multi-source observations from satellites, Argo floats, and historical in situ profiles are fused using a statistical model and a gradient-dependent optimal interpolation method. A daily gridded dataset with a 0.25° horizontal resolution is developed, which includes temperature, salinity, and currents. The results show that the correlation coefficients between the observations and the inverted profiles of temperature and salinity are about 0.99 and 0.94, respectively, with mean root mean square errors of about 1.27 °C and 0.13, respectively. In the Northwest Pacific Ocean, the most suitable parameter settings are a search radius of 1.5° in longitude and latitude, correlation scale constant of 0.25°, and relative observation error of 2. Consequently, the average RMSEs of the fused temperature and salinity fields are 0.43°C and 0.056, respectively. Compared with other reanalysis datasets, the product constructed in this study retains more high-frequency ocean signals, and its temperature error relative to XBT observations is also the smallest. Furthermore, the dataset effectively depicts the characteristics of marine dynamic processes such as the Kuroshio paths and mesoscale eddies.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110975

Authors: Guojing Zhu Jin Yang Jiakang Wang Shuzhan Li Ying Zhao Wenbo Gong Lei Li Chao Liu Segen Estefen

The suction pile well construction technique is increasingly adopted in deepwater drilling projects. The soil–structure interaction mechanism during the penetration and installation of the wellhead suction pile in clay is complex. Given the critical demand for precise installation outcomes in engineering practice, the influence of penetration velocity on installation performance requires significant consideration. Through scale-model experimental methods, various penetration velocities were configured primarily by adjusting suction pump flow rates. The influences of these velocities on penetration resistance, penetration depth, and related metrics were systematically assessed. A case study was conducted based on the engineering parameters of a wellsite in the South China Sea. A theoretical algorithm for WSP penetration resistance was developed and subsequently refined through experimental data. Coefficient optimization was established via theoretical assessment of strain-rate dependency and experimental data calibration. The optimized algorithm demonstrated strong agreement with field measurements, achieving a coefficient of determination (R2) exceeding 0.9. Compared to conventional theoretical approaches, it incorporated explicit consideration of penetration velocity. The analysis indicates that in soft clay, the penetration resistance of wellhead suction piles exhibits significant sensitivity to penetration rate, increasing with higher velocities. The influence of penetration rate on penetration depth is relatively weak. This computational approach offers design guidance for installation procedures and enables the implementation of the suction pile well construction mode in the South China Sea.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110974

Authors: Benkun Lu Xuesong Han Jiawei Zong Jie Chen Muzi Yang Fei Xu

Ship lock concrete is simultaneously subjected to surface wearing and carbonation under service, yet the coupled deterioration mechanism has not been systematically clarified. In this study, an equivalent cycling test is established to elucidate the synergistic effect of surface wearing and carbonation on carbonation kinetics, pore structure development and mechanical performance. By employing micro-hardness profiling, the thermogravimetric analysis (TGA), mercury intrusion porosimetry (MIP) and scanning electron microscope (SEM), the coupled mechanism is revealed and a carbonation model of ship lock concrete under the influence of surface wearing was established. Results show that surface wearing significantly promotes ship lock carbonation, which is confirmed by the increasing carbonation depth and surface densification. Meanwhile, the changes in concrete porosity and carbonation products further emphasize the promoting effect of surface wear on carbonation. Accordingly, the carbonation showed a persistently accelerated deterioration pattern. By revealing the coupled deterioration mechanism of surface wearing and carbonation, this study systematically provides theoretical insights into the durability of ship lock concrete.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110973

Authors: Xiaomei Xu Qiangtai Huang Zhongsheng Zhang Zirui Qi Wenhui Liu Yujie Zhong Zifeng Hu

The South China Sea serves as a premier location for investigating sediment provenance and source-to-sink processes within marginal seas. However, the sediment composition and transport mechanisms within the deep-water areas of the Qiongdongnan Basin remain poorly understood. This study analyzed the grain-size distribution, bulk geochemistry, and clay mineralogy of surface sediments to identify their origins and transport controls. Results indicate that the sediments are predominantly silt-sized with a high smectite content. Major element geochemistry suggests derivation from stable ancient terranes, while trace element patterns—characterized by LREE enrichment and negative Eu anomalies—point toward a multi-source contribution. Our analysis suggests that the Red River is the primary sediment source, supplemented by inputs from the Pearl River, the Vietnamese coast, and Hainan Island. We propose that monsoon-driven surface circulation is the primary transport driver, while deep-water currents and a branch of the Kuroshio Current facilitate the influx of Taiwan-derived materials. Our study clarifies the source–sink relationship and transport mechanism in a semi-quantitative manner, offering new insights into sediment dynamics in monsoon-influenced marginal seas.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110972

Authors: Shuhui Li Lin Liu Mian Huang

Four new species of Chromadorea (Nematoda) from marine benthic habitats in Chinese sea areas are described and illustrated. Halichoanolaimus parvulus sp. nov. is characterized by a comparatively smaller body; amphideal fovea comprising 4.5–5 turns; spicules arched, middle portion broad, progressively attenuating distally; gubernaculum slender, comprising two detached lateral elements becoming narrower toward the distal end; a short precloacal seta present; tail conico-cylindrical with three-fifths cylindrical portion in males. Cobbionema sinica sp. nov. is characterized by a pharynx with a distinct anterior bulb and an enlarged posterior portion; cephalic setae measuring 6 µm in length; amphideal fovea consisting of 4–4.5 turns; spicules 2.1–2.5 cloacal body diameters long, arrow-shaped; gubernaculum rod-like, parallel to the distal part of spicules, tail conico-cylindrical, terminating in an enlarged end and a distinct spinneret; precloacal supplement absent. Linhystera longispicula sp. nov. is characterized by cuticle with subtle transverse striations; six lateral labial sensory setae and four cephalic sensory setae are setiform, collectively forming a single circle; buccal cavity minute and slit-like, amphideal fovea circular far from the anterior end; curved, stout spicules reach a length exceeding two times the cloacal body diameter; gubernaculum is absent; conico-cylindrical tail without terminal setae. Linhystera nanhaiensis sp. nov. also has the common characteristics of the genus. It has relatively large body size with long conico-cylindrical tail; three terminal setae present; spicules resembling ox horns, reaching 1.2 times the cloacal body diameter, gubernaculum absent. This work contributes to the study of nematode diversity in China.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110970

Authors: Haiying Liu Yingchao Li Shilong Xu Huaide Zhou Huilin Jiang

Maritime aerial imaging is strongly affected by rapid illumination variations induced by dynamic sea conditions, which often cause conventional exposure control approaches to misinterpret intrinsic scene brightness as overexposure resulting from elevated camera settings. To overcome this issue, an adaptive exposure control framework based on a Glare-Aware Attention Network is proposed, implemented within an end-to-end dual-branch architecture. The framework utilizes an Exposure State Encoding (ESE) module to encode the current frame’s exposure parameters as conditional vectors, thereby resolving physical ambiguities in scene understanding. A Glare-Aware Spatial Attention (GASA) mechanism is further introduced, incorporating a glare prior map (GPM) generated using a “high-luminance, low-texture” heuristic to explicitly suppress sun glint effects. A Scene Difficulty-Adaptive Loss Weighting (SDAW) scheme is designed to adaptively regulate loss weights, and region-aware evaluation metrics, KREA and ISR, are defined. On a self-collected maritime aerial imaging dataset, the proposed approach significantly outperforms both traditional and deep learning-based methods in terms of full-frame and region-level performance metrics. Compared with the multi-task CNN baseline that has the closest parameter count, it achieves a 1.7 dB gain in PSNR. Cross-dataset validation on SeaDronesSee, temporal consistency analysis, and embedded platform testing further support the generalization and real-time feasibility of the proposed solution. Offering a high-accuracy, region-aware exposure control solution for aerial cameras in complex sea surface scenarios.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110971

Authors: Fengfeng Zhu Chuan Xie Zhaoru Zhang Meng Zhou

As sea ice recedes, the strategic importance of Arctic shipping routes has intensified, yet the complex polar environment poses severe challenges to navigational safety. Through a systematic search of the Scopus database, relevant key studies in both English and Chinese were identified and selected based on predefined inclusion criteria for in-depth review. The present study establishes a systematic categorization framework to parse existing research on Arctic navigational risk assessment. It structurally analyzes the literature across three core dimensions: sea ice characteristics, accident statistical analysis, and risk modeling methodologies. Addressing current limitations in data sparsity, factor coupling, and dynamic forecasting, this study proposes that future research should focus on the construction of structural models for risk interdependencies, multi-source data-driven environmental risk learning, and intelligent small-sample assessment based on Case-Based Reasoning (CBR), which extracts effective risk solutions from limited historical samples by interpreting past navigational successes and failures to improve decision quality. This review aims to provide a comprehensive reference for developing a systematic and intelligent risk assessment architecture for Arctic shipping.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110968

Authors: Xiaofei Zhang Aijun Wang Xiang Ye Wanqing Pang Zhenkun Lin Yanbin Fan

Tidal flats are shrinking and eroding due to sea-level rise and human activities. Ecological submerged breakwaters (ESBs) offer a novel solution combining coastal protection and ecological restoration, but their effects on sediment dynamics lack field evidence. This study presents synchronous in situ measurements from an inner tidal flat (WN01) and an outer shallow area (WN02) of a newly built riprap slope-type ESB on the northern coast of the Sheyang River Estuary, Jiangsu, China. Using Acoustic Doppler Velocimeters (ADVs) and wave-tide gauges, we examined hydrodynamics, suspended sediment concentration (SSC), bed shear stress, erosion–accretion, and sediment transport under normal-weather and strong wave events. Within the constraints of a 14-day observation at two stations, our results indicate that: (1) The ESB reduced wave height and weakened currents, shifting dominant bed shear stress from wave-dominated outside to tide-dominated inside. Under normal weather, both sides were accretive. (2) Strong wave events caused sharp increases in bed shear stress, net erosion on both sides, and a 2–3-fold SSC rise, breaking the normal balance. (3) Suspended sediment transport direction remained northwest inside during strong wave events but shifted to northeast/southeast outside, demonstrating effective isolation of wave-driven anomalies. Bedload was trapped inside, resulting in no net sediment loss, in contrast to the unprotected southern tidal flat. (4) We recommend moderately lowering the ESB crest elevation to prevent excessive accretion and implementing “grey-green” restoration (salt marshes or oyster reefs) to enhance coastal resilience against sea-level rise.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110969

Authors: Dongdong Li Zhigang Lai Mingting Li Jun Wei

In the boreal winter of the Northern Hemisphere, a weakening of the surface Indonesian throughflow (ITF) is commonly observed. The intraseasonal mechanism of the weakening, namely, the impact of the atmospheric Madden–Julian Oscillation (MJO), is well-known and has been extensively studied. However, a significantly low volume transport of ITF (<100 m in depth) was also observed in the Makassar Strait during the traverse of tropical cyclones (TCs). The observed transport decrease is 0.31 Sv (1 Sv = 106 m3/s) on average, which is ~70% of the estimated influence of the MJO. The time scale of the incurred variation is up to 30 days, comparable to the time of 20–90 days caused by the MJO. The winds in the TC circulation have a major impact on the Makassar Strait’s ITF transport reduction. Numerical experiments reveal that the reduction is due to the along-strait sea level anomaly (SLA) variability that is forced by the winds from the upstream region. The mechanism involves the propagation of coastal Kelvin waves along the Sulawesi Sea generated by the TCs and is confirmed by theoretical analysis. Based on the numerical experiments, this mechanism contributes ~40% to the total ITF transport reduction, while the large-scale guiding circulation surrounding the TCs may contribute to the remaining ITF transport reduction. These results support that TCs are also important forcing components in the intraseasonal variation in surface ITF.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110967

Authors: Haodong Ran Dezhong Chen Baogui Huan

Accurate Structural Health Monitoring of offshore wind turbines is critical for ensuring their long-term operational safety in harsh marine environments. Although displacement is a fundamental metric for assessing structural deformation and stress distribution, its direct measurement in open-ocean conditions is severely hindered by environmental interference and the absence of stable spatial references. Consequently, reconstructing displacement from structural acceleration through double integration is widely adopted, yet it suffers from severe baseline drift. Furthermore, existing drift-mitigation techniques often rely on empirical parameter selection and are limited to single-point reconstructions, failing to capture the full three-dimensional (3D) spatial attitude of the structure. To address these limitations, this paper proposes a novel 3D spatial attitude reconstruction framework based on advanced drift removal and spatial interpolation. First, an improved drift removal algorithm is developed to accurately eliminate baseline errors from acceleration signals, ensuring the physical fidelity of the reconstructed local displacements. Subsequently, cubic spline interpolation is utilized to extrapolate these discrete local measurements into a comprehensive full-field attitude profile of the entire turbine structure. The performance and robustness of the proposed method are systematically verified through numerical simulations and finite element analysis. Finally, its engineering applicability and accuracy are further validated via laboratory experiments and field measurements. The proposed framework effectively mitigates noise sensitivity and significantly enhances the accuracy of full-field attitude reconstruction, providing a reliable foundation for refined structural health assessments of OWTs.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110966

Authors: Kailun Liu Yanbo Wei Guoteng Li Zhizhong Lu

A significant wave height (SWH) estimation method for X-band ocean radar images based on the shadow modulation principle is studied. The conventional shadow method obtains the wave steepness by analyzing the bright and dark patterns in the radar image and then calculates the SWH. The shadow method relies on accurate estimation of wave steepness, which is the most reliable in the upwave area, so it shows a strong azimuth dependence. Under the actual observation conditions, it is usually difficult to obtain an ideal analysis region to effectively mitigate the direction dependence due to the limitations of physical obstacles and platform attitude changes, which affects the inversion accuracy. To solve the problem, this paper proposes a wave steepness correction method based on harmonic fitting. By establishing a harmonic fitting model between wave steepness and wave angle, the method reconstructs the continuous and stable wave steepness distribution with wave angle from 0° to 360° according to limited data points. Then, the wave steepness independent of azimuth is obtained when the wave angle is 0°. The effectiveness of the proposed wave steepness correction method is validated using a total of 466 sets of radar data collected from 8 November to 18 November 2014 and 10 January to 20 January 2015. After applying the wave steepness correction method, compared to the conventional shadow method without correction, although the correlation coefficient (CC) increased by only 0.07, the bias (BIAS) decreased by 0.12 m, and the average root mean square error (RMSE) decreased by 0.12 m.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110965

Authors: Chaogang Guo Weihua Ai Xianbin Zhao Ganzhen Chen Zhancai Liu

The radial structure and azimuthal asymmetry of tropical cyclone (TC) eyewall winds are critical for intensity change and wind-related hazards, yet they remain difficult to characterize using conventional observations. Using multi-platform C-band synthetic aperture radar (SAR) wind fields and collocated Stepped Frequency Microwave Radiometer (SFMR) wind speed and rain-rate observations, this study examined TC inner-core structure, eyewall asymmetry, and rainfall-dependent wind retrieval uncertainty for 51 TCs and 130 SAR scenes. The TC inner-core structure was characterized using a best-track-constrained center refinement and quality control procedure, in which the storm center was refined from the minimum of a Gaussian-smoothed SAR wind field and scenes were screened by eye/annulus sampling, eye–eyewall contrast, and annular wind organization. Of the 130 SAR scenes, 53 were retained for refined-center evaluation, and the 32 QC-passed scenes were used for the primary storm-centered structural analysis. The RMW showed a weak tendency to decrease with an increasing SAR-derived maximum azimuthal-mean wind speed, and the normalized wavenumber-1 asymmetry at the RMW decreased in stronger storms. Under strict temporal collocation (Δt≤30 min), the SAR–SFMR comparison achieved an RMSE of 4.22 m s−1, a bias of −1.61 m s−1, R2 = 0.82, and a regression slope of 0.90. Rainfall-related SAR–SFMR mismatch was most evident around the eyewall and adjacent outer-eyewall region, indicating the need to consider center uncertainty, scene suitability, temporal collocation, and rain-sensitive retrieval effects when interpreting SAR-derived TC inner-core structure.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110964

Authors: Yanhua Sun Baoxiao Sui Ailian Li Yunxia Guo

In this study, we employ seven well-established machine learning algorithms for the stochastic simulation of tropical cyclones in the Northwest Pacific, namely Support Vector Machine (SVM), Random Forest (RF), Bayesian Network (BN), Backpropagation Neural Network (BPNN), Wavelet Neural Network (WNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) network. First, based on the CMA (China Meteorological Administration) Tropical Cyclone Best-Track Dataset, we statistically analyze key typhoon parameters within each 5° × 5° grid over the Northwest Pacific. Second, the Random Forest method is applied to rank the importance of feature factors for predicting typhoon translation speed, storm heading, and central pressure in each grid. Third, each algorithm is used to develop prediction models, with hyperparameters optimized via a time-series cross-validation scheme. Fourth, the prediction models are compared to identify the best-performing model for predicting translation speed, storm heading, and central pressure, respectively. The optimal models are then evaluated in terms of computational efficiency and overfitting/underfitting, and validated both against traditional statistical methods and through multi-lead-time (1–72 h) predictions for four independent typhoons: Lekima 2019, Doksuri 2023, Ragasa 2025, and Yagi 2024. The results show that the optimal machine learning models outperform traditional statistical benchmarks, achieve a direct position error of <7 km and R2 ≥ 0.979 at 1 h lead time, with track prediction remaining useful up to 48–72 h, while effective intensity prediction does not exceed 24 h. This study provides a robust data-driven framework for short-term typhoon forecasting within stochastic simulation, with future work aiming to extend to long-term predictions.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110963

Authors: Jiawei Zhang Dan Shen Lei Wang Baoqiang Hu Jianfeng Zhan Deyong Song Xiufeng Li

Dynamic target following in underwater environments is challenging because delayed target-state feedback, external disturbance, and model uncertainty can significantly reduce tracking performance. This paper proposes a delay-compensated predictive robust tracking method for underwater robots. A relative-following framework is first constructed by defining a reference point with a prescribed offset from the target. To reduce the adverse effect of delayed target information, a prediction mechanism is introduced for reference generation. A robust tracking controller is then designed to improve disturbance rejection and robustness against model mismatch. The proposed method is evaluated through multi-scenario simulations with progressively increased delay, target maneuverability, disturbance intensity, and uncertainty. Comparative results with PID, robust-only, and prediction-only controllers show that the proposed method achieves the smallest mean tracking error in all considered scenarios and provides more reliable tracking performance in difficult underwater conditions. The results demonstrate that the integration of delay compensation and robust control is effective for dynamic target-following tasks with delayed and uncertain target-state feedback.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110962

Authors: Dong Wang Jiayi Liu Lei Cao Dianjun Zhang

As one of the three major bays in the Chinese Bohai Sea, Bohai Bay is located in a semi-encircled area consisting of three important provinces and cities with rich energy and fishery resources. The bay is not only a maritime gateway and transportation hub but also an important industrial base, energy production base, and port. In this study, we combined Landsat remote sensing and Geographic Information System technologies to extract the coastline of Bohai Bay from 2001 to 2021 and obtained the variation in coastline length by refinement vector processing. Sediment as the natural driver was quantitatively analyzed based on sand transport in the Yellow River and Hai River. Moreover, port construction was qualitatively analyzed as the anthropogenic driver. The results demonstrated that the coastline of Bohai Bay showed an overall growth trend in this period, with a total increase of 881.05 km in shoreline length; the main increase was in the artificial shoreline. The two natural driving factors, sediment and hydrodynamic conditions, were weak, and the anthropogenic driving factor, i.e., various human activities, played a dominant role in the variation in the Bohai Bay shoreline in the past 20 years. The extracted shoreline information is important not only for the rational and effective development and utilization of the various natural resources in the coastal zone of Bohai Bay but also for the plan to develop this important region in the future.

Journal of Marine Science and Engineering doi: 10.3390/jmse14110961

Authors: Dongha Kang Hansoo Kim Young Geul Yoon Jihoon Jung Fredrich Simanungkalit Hyun-Young Kim Myounghee Kang Donhyug Kang

The finless porpoise (Neophocaena asiaeorientalis) is a species frequently observed in Korean coastal waters that remains highly vulnerable to bycatch and habitat disturbance. To develop effective conservation strategies, it is essential to understand their acoustic behavior and environmental preferences. This study utilized Passive Acoustic Monitoring to investigate the acoustic characteristics and activity patterns of finless porpoises in coastal waters near cage aquaculture farms from September to October 2021. A total of 372,707 clicks and 175,119 click trains were identified. Mean acoustic parameters were peak frequency 122.0 ± 11.1 kHz, 3 dB bandwidth 15.4 ± 12.0 kHz, 10 dB bandwidth 45.3 ± 16.1 kHz, and ICI 39.0 ± 34.8 ms. Click activity exhibited a distinct diel pattern, with significantly higher activity during the early morning and nighttime. Generalized Additive Model analysis revealed significant non-linear relationships between click activity and tide, temperature, salinity, and hour. Specifically, click activity decreased with rising temperatures and lower salinity, while the effect of tide was relatively limited. These findings provide critical baseline data for the development of acoustic deterrent devices tailored to Korean marine environments and contribute to the management of bycatch mitigation and coastal ecosystem conservation.

Journal of Marine Science and Engineering doi: 10.3390/jmse14100960

Authors: Juncheng Ruan Ji Huang Jiewei Liao Bo Hu Yulin Wang

This study establishes a triangular numerical wave tank based on the viscous incompressible Navier–Stokes equations. The model is implemented in STAR-CCM+, employing the Reynolds-Averaged Navier–Stokes equations and the Volume of Fluid method, combined with velocity boundary wave-making and momentum source wave-making techniques for wave generation. On this basis, systematic numerical simulations of oblique and head-on waves were conducted, along with simulation studies of wave interactions with both fixed and floating circular cylinders. The accuracy and reliability of the model were validated by comparing simulation results with theoretical solutions and existing literature data. The results demonstrate that the performance of this triangular wave tank is not affected by the wave incident direction. It can stably generate high-quality oblique and head-on waves, making it suitable for numerical simulation studies of wave–structure interactions.