Journal Description
Journal of Marine Science and Engineering
Journal of Marine Science and Engineering
is an international, peer-reviewed, open access journal on marine science and engineering, published monthly online by MDPI. The Australia New Zealand Marine Biotechnology Society (ANZMBS) is affiliated with JMSE and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed with Scopus, SCIE (Web of Science), GeoRef, Inspec, AGRIS, and other databases.
- Journal Rank: JCR - Q1 (Engineering, Marine) / CiteScore - Q2 (Ocean Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.4 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.9 (2022);
5-Year Impact Factor:
2.9 (2022)
Latest Articles
Multivariate USV Motion Prediction Method Based on a Temporal Attention Weighted TCN-Bi-LSTM Model
J. Mar. Sci. Eng. 2024, 12(5), 711; https://doi.org/10.3390/jmse12050711 (registering DOI) - 25 Apr 2024
Abstract
Unmanned surface vehicle (USV)’s motion is represented by time-series data that exhibit highly nonlinear and non-stationary features, significantly influenced by environmental factors, such as wind speed and waves, when sailing on the sea. The accurate prediction of USV motion, particularly crucial parameters, such
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Unmanned surface vehicle (USV)’s motion is represented by time-series data that exhibit highly nonlinear and non-stationary features, significantly influenced by environmental factors, such as wind speed and waves, when sailing on the sea. The accurate prediction of USV motion, particularly crucial parameters, such as the roll angle and pitch angle, is imperative for ensuring safe navigation. However, traditional and single prediction models often struggle with low accuracy and fail to capture the intricate spatial–temporal dependencies among multiple input variables. To address these limitations, this paper proposes a prediction approach integrating temporal convolutional network (TCN) and bi-directional long short-term memory network (Bi-LSTM) models, augmented with a temporal pattern attention (TPA) mechanism, termed the TCN-Bi-LSTM-TPA (TBT) USV motion predictor. This hybrid model effectively combines the strengths of TCN and Bi-LSTM architectures to extract long-term temporal features and bi-directional dependencies. The introduction of the TPA mechanism enhances the model’s capability to extract spatial information, crucial for understanding the intricate interplay of various motion data. By integrating the features extracted by TCN with the output of the attention mechanism, the model incorporates additional contextual information, thereby improving prediction accuracy. To evaluate the performance of the proposed model, we conducted experiments using real USV motion data and calculated four evaluation metrics: mean square error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and R-squared (R2). The results demonstrate the superior accuracy of the TCN-Bi-LSTM-TPA hybrid model in predicting USV roll angle and pitch angle, validating its effectiveness in addressing the challenges of multivariate USV motion prediction.
Full article
(This article belongs to the Section Ocean Engineering)
Open AccessArticle
An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal
by
Hongbin Chen and Wei Liu
J. Mar. Sci. Eng. 2024, 12(5), 710; https://doi.org/10.3390/jmse12050710 (registering DOI) - 25 Apr 2024
Abstract
In container sea–rail combined transport, the railway yard in an automated container terminal (RYACT) is the link in the whole logistics transportation process, and its operation and scheduling efficiency directly affect the efficiency of logistics. To improve the equipment scheduling efficiency of an
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In container sea–rail combined transport, the railway yard in an automated container terminal (RYACT) is the link in the whole logistics transportation process, and its operation and scheduling efficiency directly affect the efficiency of logistics. To improve the equipment scheduling efficiency of an RYACT, this study examines the “RYACT–train” cooperative optimization problem in the mode of “unloading before loading” for train containers. A mixed-integer programming model with the objective of minimizing the maximum completion time of automated rail-mounted gantry crane (ARMG) tasks is established. An adaptive large neighborhood search (ALNS) algorithm and random search algorithm (RSA) are designed to solve the abovementioned problem, and the feasibility of the model and algorithm is verified by experiments. At the same time, the target value and calculation time of the model and algorithms are compared. The experimental results show that the model and the proposed algorithms are feasible and can effectively solve the “RYACT–train” cooperative optimization problem. The model only obtains the optimal solution of the “RYACT–train” cooperative scheduling problem with no more than 50 tasks within a limited time, and the ALNS algorithm can solve examples of various scales within a reasonable amount of time. The target value of the ALNS solution is smaller than that of the RSA solution.
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(This article belongs to the Section Ocean Engineering)
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Open AccessArticle
Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data
by
Polina Lemenkova
J. Mar. Sci. Eng. 2024, 12(5), 709; https://doi.org/10.3390/jmse12050709 (registering DOI) - 25 Apr 2024
Abstract
This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in
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This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India.
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(This article belongs to the Special Issue Remote Sensing Applications in Marine Environmental Monitoring)
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Open AccessArticle
An Underwater Localization Algorithm for Airborne Moving Sound Sources Using Doppler Warping Transform
by
Junjie Mao, Zhaohui Peng, Bo Zhang, Tongchen Wang, Zhaokai Zhai, Chuanxing Hu and Qianyu Wang
J. Mar. Sci. Eng. 2024, 12(5), 708; https://doi.org/10.3390/jmse12050708 (registering DOI) - 25 Apr 2024
Abstract
When an airborne sound source is in rapid motion, the acoustic signal detected by the underwater sensor experiences a substantial Doppler shift. This shift is intricately linked to the motion parameters of the sound source. Analyzing the Doppler shift characteristics of received acoustic
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When an airborne sound source is in rapid motion, the acoustic signal detected by the underwater sensor experiences a substantial Doppler shift. This shift is intricately linked to the motion parameters of the sound source. Analyzing the Doppler shift characteristics of received acoustic signals enables not only the estimation of target motion parameters but also the localization of the airborne sound source. Currently, the predominant methods for estimating parameters of uniformly moving targets are grounded in classical approaches. In this study, the application of the Doppler warping transform, traditionally applicable to sound sources in uniform linear motion, is extended to encompass a broader spectrum of sound source trajectories. Theoretical and experimental data validate the efficacy of this transform in linearizing the Doppler shift induced by a source in curved motion. Building upon this foundation, a methodology is proposed for locating airborne acoustic sources in curved motion from underwater. Sea experimental data corroborate the method’s effectiveness in achieving underwater localization of a helicopter target during curved motion.
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(This article belongs to the Section Ocean Engineering)
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Open AccessArticle
The Coastal Scenery of São Miguel Island, Azores Archipelago: Implications for Coastal Management
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Claudia Tendero-Peiró, Francisco Asensio-Montesinos, Giorgio Anfuso and Hugo Corbí
J. Mar. Sci. Eng. 2024, 12(5), 707; https://doi.org/10.3390/jmse12050707 (registering DOI) - 25 Apr 2024
Abstract
In this study, coastal scenic beauty was assessed at 29 sites at São Miguel, which is one of the Azores Islands, i.e., a group of remote volcanic islands in the North Atlantic Ocean. The assessment was based on in situ observations and the
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In this study, coastal scenic beauty was assessed at 29 sites at São Miguel, which is one of the Azores Islands, i.e., a group of remote volcanic islands in the North Atlantic Ocean. The assessment was based on in situ observations and the use of the Coastal Scenic Evaluation System (CSES), which consists of a checklist with 26 physical- and anthropic-weighted parameters and the Fuzzy Logic Approach (FLA) mathematical tool. The study sites were classified into five classes according to their typology and their scenic value, ranging from Class I (natural sites of great scenic beauty) to Class V (unattractive, urbanized sites). Concerning beach typology, 13% were remote, 28% rural, 28% village, and 31% urban. Concerning scenic beauty, 10% of the sites belonged to Class I, 14% to Class II, 17% to Class III, 31% to Class IV, and 28% to Class V. The physical parameters were linked to the characteristics of the geological volcanic landscapes, and the anthropic parameters essentially reflected the presence of tourism and public services. The results of the assessment provide a scientific basis for developing a management strategy for the preservation and conservation of the coastal areas and their sustainable development.
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(This article belongs to the Section Geological Oceanography)
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Open AccessArticle
Global Strong Winds Occurrence Characteristics and Climate Index Correlation
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Di Wu, Kaishan Wang, Chongwei Zheng and Yuchen Guo
J. Mar. Sci. Eng. 2024, 12(5), 706; https://doi.org/10.3390/jmse12050706 (registering DOI) - 25 Apr 2024
Abstract
Guided by entering the deep sea and achieving deep marine development in marine construction, the factors hindering marine construction cannot be ignored. Strong ocean winds have a devastating impact on tasks such as ship navigation, carrier aircraft take-off and landing, naval operations and
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Guided by entering the deep sea and achieving deep marine development in marine construction, the factors hindering marine construction cannot be ignored. Strong ocean winds have a devastating impact on tasks such as ship navigation, carrier aircraft take-off and landing, naval operations and military exercises, and affect the planning of sea routes and the development of the long-distance sea. This paper uses ERA5 wind field data and key climate indices to conduct a systematic analysis of catastrophic winds in the global ocean using methods such as climate statistical analysis, the Theil–Sen trend method, Pearson correlation and contribution rate calculation. It points out the spatiotemporal distribution, variation trend, climate index correlation and contribution rate characteristics of strong winds occurrence (SWO) and hopes that the results of this study can serve as a guide for maritime route planning and provide technical assistance and decision-making support for marine development and other needs. The results show the following: The high global SWO occurs in the Southern Ocean, the North Atlantic, the North Pacific, near Taiwan, China, the Arabian Sea and other locations, with the strongest SWO in summer. The growth trend of SWO in the Southern Ocean is strongest, with decreasing regions near the Arabian Sea and the Bay of Bengal, and the growth trend is reflected in all four seasons. The climate indices with the strongest correlation and highest contribution to the global SWO are AAO (Antarctic Oscillation) and EP–NP (East Pacific–North Pacific pattern) with a correlation between −0.5 and 0.5 and a contribution rate of up to −50%~50%.
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(This article belongs to the Section Physical Oceanography)
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Open AccessFeature PaperArticle
Multi-Frequency Noise Reduction Method for Underwater Radiated Noise of Autonomous Underwater Vehicles
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Beibei Mao, Hua Yang, Wenbo Li, Xiaoyu Zhu and Yuxuan Zheng
J. Mar. Sci. Eng. 2024, 12(5), 705; https://doi.org/10.3390/jmse12050705 (registering DOI) - 25 Apr 2024
Abstract
The multi-frequency noisy vibration of an autonomous underwater vehicle (AUV) is a significant factor affecting the performance of shear probes mounted on the head of AUVs. Many efforts have been made to suppress mechanical radiation noise; however, conventional noise reduction methods have their
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The multi-frequency noisy vibration of an autonomous underwater vehicle (AUV) is a significant factor affecting the performance of shear probes mounted on the head of AUVs. Many efforts have been made to suppress mechanical radiation noise; however, conventional noise reduction methods have their limitations, such as mode mixing. In order to extract thorough information from the aliasing modes and achieve multi-frequency mode targeted correction, a multi-frequency noise reduction method is proposed, based on secondary decomposition and the multi-mode coherence correction algorithm. Weak impulses in aliasing shear mode are enhanced, and mixing frequencies are isolated for thorough decomposition. Noisy mechanical vibrations in the shear modes are eliminated with the use of the acceleration modes along the identical central frequency series. The denoised modes are used to reconstruct the cleaned shear signal, and the updated spectra are aligned with the standard Nasmyth spectrum. Compared with the raw profiles, the variation in the dissipation rate estimated from the corrected shear is reduced by more than an order of magnitude.
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(This article belongs to the Special Issue Marine Technology: Latest Advancements and Prospects)
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Open AccessArticle
The Formation of 2D Holograms of a Noise Source and Bearing Estimation by a Vector Scalar Receiver in the High-Frequency Band
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Sergey Pereselkov, Venedikt Kuz’kin, Matthias Ehrhardt, Yurii Matvienko, Sergey Tkachenko and Pavel Rybyanets
J. Mar. Sci. Eng. 2024, 12(5), 704; https://doi.org/10.3390/jmse12050704 (registering DOI) - 25 Apr 2024
Abstract
The holographic signal-processing method for a single vector scalar receiver (VSR) in the high-frequency band in shallow water is developed in the paper. The aim of this paper is to present the results of the theoretical analysis, numerical modeling, and experimental verification of
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The holographic signal-processing method for a single vector scalar receiver (VSR) in the high-frequency band in shallow water is developed in the paper. The aim of this paper is to present the results of the theoretical analysis, numerical modeling, and experimental verification of holographic signal processing for a noise source by the VSR. The developed method is based on the formation of the 2D interferogram and 2D hologram of a noise source in a shallow-water waveguide. The 2D interferograms and 2D holograms for different channels of the VSR (P sound pressure and and vibration velocity components) are considered. It is shown that the 2D interferogram consists of parallel interference fingers in the presence of a moving noise source. As a result, the 2D hologram contains focal points located on a straight line, and the angular distribution of the holograms has the main extreme value. It is shown in the paper that the holographic signal-processing method allows detecting the source, estimating the source bearing, and filtering the useful signal from the noise. The results of the source detection, source bearing estimation, and noise filtering are presented within the framework of experimental data processing and numerical modeling.
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(This article belongs to the Special Issue Underwater Acoustics and Digital Signal Processing)
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Pore Pressure Prediction for High-Pressure Tight Sandstone in the Huizhou Sag, Pearl River Mouth Basin, China: A Machine Learning-Based Approach
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Jin Feng, Qinghui Wang, Min Li, Xiaoyan Li, Kaijin Zhou, Xin Tian, Jiancheng Niu, Zhiling Yang, Qingyu Zhang and Mengdi Sun
J. Mar. Sci. Eng. 2024, 12(5), 703; https://doi.org/10.3390/jmse12050703 (registering DOI) - 24 Apr 2024
Abstract
A growing number of large data sets have created challenges for the oil and gas industry in predicting reservoir parameters and assessing well productivity through efficient and cost-effective techniques. The design of drilling plans for a high-pressure tight-sand reservoir requires accurate estimations of
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A growing number of large data sets have created challenges for the oil and gas industry in predicting reservoir parameters and assessing well productivity through efficient and cost-effective techniques. The design of drilling plans for a high-pressure tight-sand reservoir requires accurate estimations of pore pressure (Pp) and reservoir parameters. The objective of this study is to predict and compare the Pp of Huizhou Sag, Pearl River Mouth Basin, China, using conventional techniques and machine learning (ML) algorithms. We investigated the characteristics of low-permeability reservoirs by observing well-logging data sets and cores and examining thin sections under a microscope. In the reservoir zone, the average hydrocarbon saturation is 55%, and the average effective porosity is 11%. The tight sandstone reservoirs consist of fine- to extremely fine-grained argillaceous feldspathic sandstone. The mean absolute error for reservoir property prediction is 1.3%, 2.2%, and 4.8%, respectively, for effective porosity, shale volume, and water saturation. Moreover, the ML algorithm was employed to cross-check the validity of the prediction of Pp. Combining conventional and ML techniques with the core data demonstrates a correlation coefficient (R2) of 0.9587, indicating that ML techniques are the most effective in testing well data. This study shows that ML can effectively predict Pp at subsequent depths in adjacent geologically similar locations. Compared to conventional methods, a substantial data set and ML algorithms improve the precision of Pp predictions.
Full article
(This article belongs to the Special Issue Production Prediction in Onshore and Offshore Tight Reservoirs)
Open AccessArticle
Stiffness Anisotropy and Micro-Mechanism of Calcareous Sand with Different Particle Breakage Ratios Subjected to Shearing Based on DEM Simulations
by
Yan Gao, Ketian Sun, Quan Yuan and Tiangen Shi
J. Mar. Sci. Eng. 2024, 12(5), 702; https://doi.org/10.3390/jmse12050702 (registering DOI) - 24 Apr 2024
Abstract
Stress-induced anisotropy in calcareous sand can cause an uneven displacement in island reef engineering. In this study, stiffness, as a quantitative indicator, is explored to reveal the stress-induced anisotropy in calcareous sand. Based on the discrete element method, the stiffness anisotropic characteristics of
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Stress-induced anisotropy in calcareous sand can cause an uneven displacement in island reef engineering. In this study, stiffness, as a quantitative indicator, is explored to reveal the stress-induced anisotropy in calcareous sand. Based on the discrete element method, the stiffness anisotropic characteristics of calcareous sand during shearing, as well as the impact of particle breakage, are investigated by numerical simulations. Both the macro and micro responses, i.e., the maximum shear modulus, contact normal, strong and weak contact normal force, and the direction of particle breakage, are explored for calcareous sand with different particle breakage ratios. The results show that calcareous sand exhibits notable anisotropy during shearing, with the maximum shear modulus in the vertical direction (deviatoric stress direction) being significantly greater than that in the horizontal direction. Moreover, the higher the particle breakage rate, the lower the stiffness and its anisotropy. The micro-mechanism results indicate that the primary particle breakage during the shearing process occurs in the vertical direction. That is, the particle breakage weakens the strong contact force in the vertical direction, leading to a redistribution of the strong contact forces from the vertical direction to other directions. This redistribution mainly manifests in a decrease in the anisotropy of contact normal and contact vector within the sample, as well as a decrease in the proportion of strong contact forces in the overall contacts. This, in turn, reduces the shear strength and stiffness of calcareous sand, particularly in the vertical direction, and results in a decrease in the maximum shear modulus and its anisotropy. The maximum reduction can be up to 50% of the original value. These insights can provide a certain theoretical support for the uneven displacement and long-term stability of calcareous sand for islands and reefs.
Full article
(This article belongs to the Special Issue Wave/Current–Structure–Seabed Interactions around Offshore Foundations)
Open AccessArticle
Numerical Study on the Swimming and Energy Self-Sufficiency of Multi-Joint Robotic Fish
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Guodu Liang, Zhiqiang Xin, Quanlin Ding, Songyang Liu and Liying Ren
J. Mar. Sci. Eng. 2024, 12(5), 701; https://doi.org/10.3390/jmse12050701 - 24 Apr 2024
Abstract
Energy is one of the primary challenges in the long-term operation of robotic fish. The research on combining wave energy-harvesting technology with robotic fish for energy supplementation is not extensive, and there is insufficient comprehensive analysis on energy harvesting from waves and energy
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Energy is one of the primary challenges in the long-term operation of robotic fish. The research on combining wave energy-harvesting technology with robotic fish for energy supplementation is not extensive, and there is insufficient comprehensive analysis on energy harvesting from waves and energy costs during swimming. Therefore, the energy self-sufficiency of multi-joint robotic fish is investigated by employing the coupling method of smoothed particle hydrodynamics (SPH) and multi-body dynamics in this study. A reversible energy conversion mechanism is applied to the robotic fish, serving as a driving system during swimming and as a power take-off (PTO) system during energy harvesting. The energy costs of the multi-joint robotic fish under various undulation parameters (including amplitude, frequency, and body wavelength) are analyzed, along with an examination of the influence of the PTO system on energy harvesting. The results show that, compared to the undulation amplitude and body wavelength, the undulation frequency has the greatest impact on swimming efficiency and energy costs, with low-frequency swimming being advantageous for efficient energy utilization. Additionally, the damping coefficient of the PTO system directly affects energy-harvesting efficiency, with higher energy-harvesting power achievable with an optimal PTO system parameter. Through a comprehensive analysis of energy costs and energy harvesting, it is concluded that the achievement of energy self-sufficiency for multi-joint robotic fish in marine environments is highly feasible.
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(This article belongs to the Section Marine Energy)
Open AccessArticle
Mid-Deep Circulation in the Western South China Sea and the Impacts of the Central Depression Belt and Complex Topography
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Hongtao Mai, Dongxiao Wang, Hui Chen, Chunhua Qiu, Hongzhou Xu, Xuekun Shang and Wenyan Zhang
J. Mar. Sci. Eng. 2024, 12(5), 700; https://doi.org/10.3390/jmse12050700 - 24 Apr 2024
Abstract
As a key component of meridional overturning circulation, mid-deep circulation plays a crucial role in the vertical and meridional distribution of heat. However, due to a lack of observation data, current knowledge of the dynamics of mid-deep circulation currents moving through basin boundaries
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As a key component of meridional overturning circulation, mid-deep circulation plays a crucial role in the vertical and meridional distribution of heat. However, due to a lack of observation data, current knowledge of the dynamics of mid-deep circulation currents moving through basin boundaries and complicated seabed topographies is severely limited. In this study, we combined oceanic observation data, bathymetric data, and numerical modeling of the northwest continental margin of the South China Sea to investigate (i) the main features of mid-deep circulation currents traveling through the central depression belt and (ii) how atmospheric-forcing (winds) mesoscale oceanic processes such as eddies and current–topography interactions modulate the mid-deep circulation patterns. Comprehensive results suggest that the convergence of different water masses and current–topography interactions take primary responsibility for the generation of instability and enhanced mixing within the central depression belt. By contrast, winds and mesoscale eddies have limited influence on the development of local circulation patterns at mid-deep depths (>400 m). This study emphasizes that the intensification and bifurcation of mid-deep circulation; specifically, those induced by a large depression belt morphology determine the local material cycle (temperature, salinity, etc.) and energy distribution. These findings provide insights for a better understanding of mid-deep circulation structures on the western boundary of ocean basins such as the South China Sea.
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(This article belongs to the Special Issue Recent Developments and Advances in Geological Oceanography and Ocean Observation in the Pacific Ocean and Its Marginal Basins)
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Open AccessArticle
Characteristics and Environmental Indications of Grain Size and Magnetic Susceptibility of the Late Quaternary Sediments from the Xiyang Tidal Channel, Western South Yellow Sea
by
Fei Xia, Dezheng Liu and Yongzhan Zhang
J. Mar. Sci. Eng. 2024, 12(5), 699; https://doi.org/10.3390/jmse12050699 - 24 Apr 2024
Abstract
To reveal the characteristics and environmental indications for the combination of the grain size and magnetic susceptibility of coastal sediments, we provided a necessary basis for further study on their genetic mechanisms. Based on the data of grain size and magnetic susceptibility of
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To reveal the characteristics and environmental indications for the combination of the grain size and magnetic susceptibility of coastal sediments, we provided a necessary basis for further study on their genetic mechanisms. Based on the data of grain size and magnetic susceptibility of the 36.10 m long core 07SR01 sediments in the Xiyang tidal channel of western South Yellow Sea, we analyzed their variations and correlations and further revealed their environmental indications and corresponding regional sedimentary evolution via the combination of the aforementioned analysis results, the reinterpretation results of the sedimentary sequence and the age of core 07SR01 and shallow seismic profiles, and the findings of climate and glacial–eustatic cycles during Late Quaternary. The three stages of the sedimentary evolution of the Xiyang tidal channel between marine isotope stage (MIS) 7 and MIS 5 were summarized as follows: First is the stage of marginal bank and riverbed developments in the tidal estuary under a relatively high sea level and strong hydrodynamic conditions during MIS 7 (core section: 36.10–26.65 m). The sediments deposited in this stage were mainly affected by the paleo-Changjiang River and characterized by a coarse grain size (mean: 4.02 Φ) and relatively high magnetic susceptibilities (mean: 27.06 × 10−8 m3·kg−1), with small fluctuations which were strongly and positively correlated with the sand component. Second is the stage dominated by fluviolacustrine and littoral environments with the weak hydrodynamics during MIS 6–5, in which the climate changed from cold and dry to warm and humid as the sea level rose after a drop (core section: 26.65–15.77 m). The sediments deposited in this stage were characterized by a fine grain size (mean: 5.27 Φ) and low magnetic susceptibilities with minor variations (mean: 10.83 × 10−8 m3·kg−1) which were weakly and positively correlated with the coarse silt component. Third is the stage of delta front in the tidal estuary with a relatively high sea level and strong hydrodynamics during MIS 5 (core section: 15.77–0 m). The sediments deposited in this stage were strongly influenced by the paleo-Yellow River and characterized by a relatively coarse grain size (mean: 4.86 Φ), and high magnetic susceptibilities (mean: 37.15 × 10−8 m3·kg−1) with large fluctuations which were weakly and positively correlated with the sand and coarse silt components.
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(This article belongs to the Special Issue Morphological Processes and Evolution of Marine Geomorphology: Observations, Modeling and Applications)
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Open AccessArticle
Techno-Economic Evaluation of Direct Low-Pressure Selective Catalytic Reduction for Boil-Off Gas Treatment Systems of NH3-Fueled Ships
by
Sangmin Ji, Wongwan Jung and Jinkwang Lee
J. Mar. Sci. Eng. 2024, 12(5), 698; https://doi.org/10.3390/jmse12050698 - 24 Apr 2024
Abstract
This study proposes a feasible solution for boil-off gas (BOG) treatment to facilitate NH3 fuel use by ocean-going ships, which is currently considered an alternative fuel for ships. Two systems were designed and analyzed for BOG in IMO Type-A NH3 fuel
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This study proposes a feasible solution for boil-off gas (BOG) treatment to facilitate NH3 fuel use by ocean-going ships, which is currently considered an alternative fuel for ships. Two systems were designed and analyzed for BOG in IMO Type-A NH3 fuel storage tanks for 14,000 TEU container ships. First, BOG lost inside the storage tank minimized economic losses through the onboard re-liquefaction system. The total energy consumed by the system to process NH3 gas generated in the fuel tank at 232.4 kg/h was 51.9 kW, and the specific energy consumption (SEC) was 0.223 kWh/kg. Second, NH3 was supplied to the direct Low-Pressure Selective Catalytic Reduction (LP-SCR) system to treat marine pollutants generated by combustion engines. The feasible design point was determined by calculating the NH3 feed flow rate using three methodologies. The energy consumed by the direct LP-SCR system was 3.89 and 2.39 kW, and the SEC was 0.0144 at 0.0167 kWh/kg at 100% and 25% load, respectively. The feasibility was indicated via economic analysis. Depending on the life cycle cost, the competitiveness of the re-liquefaction system depends on the price of NH3, where a higher price yields a more economical solution. In conclusion, the direct LP-SCR system has a low overall cost because of its low energy consumption when supplying NH3 and its reduced amount of core equipment.
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(This article belongs to the Special Issue Maritime Alternative Fuel and Sustainability)
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Open AccessArticle
A Lightweight Model of Underwater Object Detection Based on YOLOv8n for an Edge Computing Platform
by
Yibing Fan, Lanyong Zhang and Peng Li
J. Mar. Sci. Eng. 2024, 12(5), 697; https://doi.org/10.3390/jmse12050697 - 23 Apr 2024
Abstract
The visual signal object detection technology of deep learning, as a high-precision perception technology, can be adopted in various image analysis applications, and it has important application prospects in the utilization and protection of marine biological resources. While the marine environment is generally
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The visual signal object detection technology of deep learning, as a high-precision perception technology, can be adopted in various image analysis applications, and it has important application prospects in the utilization and protection of marine biological resources. While the marine environment is generally far from cities where the rich computing power in cities cannot be utilized, deploying models on mobile edge devices is an efficient solution. However, because of computing resource limitations on edge devices, the workload of performing deep learning-based computationally intensive object detection on mobile edge devices is often insufficient in meeting high-precision and low-latency requirements. To address the problem of insufficient computing resources, this paper proposes a lightweight process based on a neural structure search and knowledge distillation using deep learning YOLOv8 as the baseline model. Firstly, the neural structure search algorithm was used to compress the YOLOv8 model and reduce its computational complexity. Secondly, a new knowledge distillation architecture was designed, which distills the detection head output layer and NECK feature layer to compensate for the accuracy loss caused by model reduction. When compared to YOLOv8n, the computational complexity of the lightweight model optimized in this study (in terms of floating point operations (FLOPs)) was 7.4 Gflops, which indicated a reduction of 1.3 Gflops. The multiply–accumulate operations (MACs) stood at 2.72 G, thereby illustrating a decrease of 32%; this saw an increase in the AP50, AP75, and mAP by 2.0%, 3.0%, and 1.9%, respectively. Finally, this paper designed an edge computing service architecture, and it deployed the model on the Jetson Xavier NX platform through TensorRT.
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(This article belongs to the Special Issue Underwater Engineering and Image Processing)
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Controls on Deep and Shallow Gas Hydrate Reservoirs in the Dongsha Area, South China Sea: Evidence from Sediment Properties
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Chenyang Bai, Hongbin Wang, Qing Li, Yu Zhang and Xiaolei Xu
J. Mar. Sci. Eng. 2024, 12(5), 696; https://doi.org/10.3390/jmse12050696 - 23 Apr 2024
Abstract
The Dongsha area, a key region in the northern South China Sea (SCS), features both diffusive deep and seepage shallow gas hydrate reservoirs. Utilizing sediment samples from gas hydrate reservoirs and adjacent layers at sites W08 and W16 in the Dongsha area, this
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The Dongsha area, a key region in the northern South China Sea (SCS), features both diffusive deep and seepage shallow gas hydrate reservoirs. Utilizing sediment samples from gas hydrate reservoirs and adjacent layers at sites W08 and W16 in the Dongsha area, this study aims to uncover the sediment property differences between deep and shallow gas hydrate reservoirs and their impact on gas hydrate accumulation through grain size, X-ray diffraction, and specific surface area (SSA) analyses. The findings classify the study intervals into four distinct layers: shallow non-gas hydrate layer (shallow-NGHL), shallow gas hydrate reservoir (shallow-GHR), deep non-gas hydrate layer (deep-NGHL), and deep gas hydrate reservoir (deep-GHR). In the clayey silt sediment reservoirs, grain size has a minor influence on gas hydrate reservoirs. Both shallow and deep NGHLs, characterized by high smectite content and SSA, possess a complex structure that impedes gas and fluid migration and offers limited potential reservoir space. Consequently, both shallow and deep NGHLs function as sealing beds. The deep GHR, having low smectite content and SSA, exhibits a strong capacity for gas and fluid migration and greater potential reservoir space. As a result, sediment properties significantly influence the deep GHR. Seepage primarily controls the shallow GHR.
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(This article belongs to the Special Issue Advances in Marine Gas Hydrate Exploration and Discovery)
Open AccessArticle
An Obstacle Avoidance Strategy for AUV Based on State-Tracking Collision Detection and Improved Artificial Potential Field
by
Yueming Li, Yuhao Ma, Jian Cao, Changyi Yin and Xiangyi Ma
J. Mar. Sci. Eng. 2024, 12(5), 695; https://doi.org/10.3390/jmse12050695 - 23 Apr 2024
Abstract
This paper proposes a fusion algorithm based on state-tracking collision detection and the simulated annealing potential field (SCD-SAPF) to address the challenges of obstacle avoidance for autonomous underwater vehicles (AUVs) in dynamic environments. Navigating AUVs in complex underwater environments requires robust autonomous obstacle
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This paper proposes a fusion algorithm based on state-tracking collision detection and the simulated annealing potential field (SCD-SAPF) to address the challenges of obstacle avoidance for autonomous underwater vehicles (AUVs) in dynamic environments. Navigating AUVs in complex underwater environments requires robust autonomous obstacle avoidance capabilities. The SCD-SAPF algorithm aims to accurately assess collision risks and efficiently plan avoidance trajectories. The algorithm introduces an SCD model for proactive collision risk assessment, predicting collision risks between AUVs and dynamic obstacles. Additionally, it proposes a simulated annealing (SA) algorithm to optimize trajectory planning in a simulated annealing potential field (SAPF), integrating the SCD model with the SAPF algorithm to guide AUVs in obstacle avoidance by generating optimal heading and velocity outputs. Extensive simulation experiments demonstrate the effectiveness and robustness of the algorithm in various dynamic scenarios, enabling the early avoidance of dynamic obstacles and outperforming traditional methods. This research provides an accurate collision risk assessment and efficient obstacle avoidance trajectory planning, offering an innovative approach to the field of underwater robotics and supporting the enhancement of AUV autonomy and reliability in practical applications.
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(This article belongs to the Section Ocean Engineering)
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Open AccessArticle
Distributed Formation–Containment Tracking Control for Multi-Hovercraft Systems with Compound Perturbations
by
Zhipeng Fan, Yujie Xu and Mingyu Fu
J. Mar. Sci. Eng. 2024, 12(5), 694; https://doi.org/10.3390/jmse12050694 - 23 Apr 2024
Abstract
Aiming at the problem of hovercraft formation–containment control with compound perturbations including model uncertainties and ocean disturbances, a distributed control algorithm for underactuated hovercraft formation–containment is proposed by combining adaptive linear extended state observer (ALESO) and radial basis function neural network (RBFNN). Firstly,
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Aiming at the problem of hovercraft formation–containment control with compound perturbations including model uncertainties and ocean disturbances, a distributed control algorithm for underactuated hovercraft formation–containment is proposed by combining adaptive linear extended state observer (ALESO) and radial basis function neural network (RBFNN). Firstly, ALESO and RBFNN are designed to estimate the ocean disturbances and model uncertainties, respectively, for dynamic compensation in the controller. Then, the auxiliary variables are introduced into the formation error function, and the lateral and longitudinal error stabilization is transformed into the design of longitudinal force and rotational torque by using the skew-symmetric matrix transformation, which solves the lateral underactuated problem of the hovercraft. Finally, the uniform ultimate boundedness of formation–containment cooperative errors is proved by the Lyapunov stability theory. Digital simulation verifies the effectiveness of the proposed method.
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(This article belongs to the Special Issue Unmanned Marine Vehicles: Perception, Planning, Control and Swarm)
Open AccessArticle
Assessment of the Carbon Footprint of Large Yellow Croaker Farming on the Aquaculture Vessel in Deep Sea in China
by
Fei Fan, Jianli Zheng, Huang Liu and Mingchao Cui
J. Mar. Sci. Eng. 2024, 12(5), 693; https://doi.org/10.3390/jmse12050693 - 23 Apr 2024
Abstract
The present study conducted a Life Cycle Assessment (LCA) to evaluate the carbon emissions associated with large yellow croaker farming on Aquaculture Vessel “Conson No. 1”. The functional unit considered was 1 kg of fresh large yellow croakers delivered to a wholesaler. The
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The present study conducted a Life Cycle Assessment (LCA) to evaluate the carbon emissions associated with large yellow croaker farming on Aquaculture Vessel “Conson No. 1”. The functional unit considered was 1 kg of fresh large yellow croakers delivered to a wholesaler. The life cycle of large yellow croaker farming on the aquaculture vessel was divided into five processes: feed production (FP), ship construction (SC), fingerling breeding (FB), adult fish farming (AF), and fish distribution (FD). Results showed that the carbon footprint (CF, kgCO2e/kg LW) for the complete life cycle amounted to 6.2170 kgCO2e/kg LW, while the CF per unit economic value of “Conson No. 1” large yellow croaker was estimated at 31 gCO2e/CNY. Among all processes, AF and FP had the highest CF contribution rates at 69.30% and 24.86%, respectively. Notably, energy consumption by aquaculture equipment on board emerged as the primary contributor across all sources of CF. Comparative analysis demonstrated that the CF of marine fish farming on the aquaculture vessel was lower than that of closed aquaculture systems’ average level and it was a viable option for implementing low-carbon aquaculture in the deep sea. In order to reduce energy consumption and promote a low-carbon economy in aquaculture vessels, several suggestions were proposed, including adjusting energy structure, enhancing energy efficiency, improving feed ratio, and optimizing feeding methods.
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(This article belongs to the Special Issue Fisheries and Aquaculture: Current Situation and Future Perspectives)
Open AccessArticle
Numerical Investigation of Local Scour Protection around the Foundation of an Offshore Wind Turbine
by
Ning Zhang, Bingqian Yu, Shiyang Yin, Caixia Guo, Jianhua Zhang, Fanchao Kong, Weikun Zhai and Guodong Qiu
J. Mar. Sci. Eng. 2024, 12(5), 692; https://doi.org/10.3390/jmse12050692 - 23 Apr 2024
Abstract
The pile foundations of offshore wind turbines face serious problems from scour damage. This study takes offshore wind turbine monopile foundations as the research object and proposes an innovative anti-scour device for the protection net. A numerical simulation research method based on CFD-DEM
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The pile foundations of offshore wind turbines face serious problems from scour damage. This study takes offshore wind turbine monopile foundations as the research object and proposes an innovative anti-scour device for the protection net. A numerical simulation research method based on CFD-DEM was used to model the local scour of the pile foundation and protection net. The validity of the numerical model was verified by comparing the simulation results of the local scour of the pile foundation under the condition of clear water scour and the results of the flume test. The permeability rate was defined to characterize the overwatering of the protection net, and numerical simulations were performed for protection nets with permeability in the range of 0.681 to 0.802. The flow field perturbations, changes in washout pit morphology, and changes in washout depth development due to the protective netting were also analyzed. It was found that the protection net can effectively reduce the flow velocity around the pile, cut down the intensity of the submerged water in front of the pile, and provide scouring protection. Finally, the analysis and summary of the protection efficiency of the different protection nets revealed that the protection efficiency within the nets was consistently the highest. On the outside of the net, the protection efficiency is poor at a small permeability rate but increases with an increasing permeability rate.
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(This article belongs to the Special Issue New Era in Offshore Wind Energy)
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