Hasil untuk "Ocean engineering"

Siti Ari Budhiyanti, Indun Dewi Puspita, Nurfitri Ekantari

Eel (Anguilla sp.) is a catadromous fish with high nutritional value, originating in freshwater and migrating to spawn, producing glass eel larvae. In Indonesia, processed eel products such as kabayaki, shirayaki, and smoked eel, which are popular in Japan, have not been widely developed. Comprehensive data on the nutritional composition and protein quality of these products are essential for product development and nutritional improvement. This study aims to determine the nutritional composition, amino acid profiles, and in vitro protein digestibility of Indonesian smoked eel, shirayaki, and kabayaki. Analyses included nutritional composition, amino acid profiles using high-performance liquid chromatography (HPLC), and in vitro protein digestibility for processed eel products. The results indicated that the processing method affected the nutritional value, albumin, minerals, and amino acids. Fresh eel had the highest protein content, followed by smoked eel, while there was no significant difference between shirayaki and kabayaki. The protein digestibility was highest in smoked (67.59%), but there was no significant difference among the others (63.30-64.44%). Calcium (Ca), magnesium (Mg), and potassium (K) contents were highest in smoked eel compared to fresh eel and decreased significantly in shirayaki and kabayaki, but for zinc (Zn), shirayaki and kabayaki tend to be higher than smoked eel. An analysis of essential amino acids showed no significant difference between the processing methods. Leucine had the highest concentration, followed by valine, threonine, and isoleucine, with concentrations ranging from 4.02% to 7.83%. The research found that the best processing method was smoked, and there was no significant difference between kabayaki and shirayaki.

Zhuwei Liu, Lin Li, Tingsan Song et al.

The high content of alkali and alkaline earth metals (AAEMs) in biomass fuels exacerbates slagging and corrosion during co-combustion with coal, thereby limiting industrial utilization. To address these challenges, this study proposes a green pretreatment combining Fenton and photocatalytic processes. Walnut shells (WS) were treated with g-C3N4-loaded calcium alginate microbeads under simultaneous simulated daylight irradiation and Fenton oxidation. Thermogravimetric analysis was employed to investigate the combustion characteristics of coal blended with pretreated and untreated WS. Results demonstrated a 170 % enhancement in the combustion performance index (S) at a heating rate of 20 °C/min. X-ray fluorescence (XRF) analysis revealed that the pretreatment reduced AAEMs content by 53.5 %, specifically decreasing K₂O and Na₂O concentrations in ash from 5.21 % to 0.87 %. Slagging indices analysis further confirmed mitigated fouling risks, showing a low slagging index of 0.158 and a fouling index of 0.129. Kinetic analysis using model-free methods indicated a 12.8 % increase in activation energy (E = 149.94 kJ/mol for pretreated walnut shells-coal blends compared to 132.91 kJ/mol for untreated blends), indicating a suppression of the catalytic effects of AAEMs on coal degradation. This work establishes a sustainable strategy for optimizing biomass-coal co-combustion systems with improved environmental compatibility and industrial applicability.

Kaifeng Peng, Beibei Si, Weiguo Jiang et al.

Rivers play import roles in ecological biodiversity, shipping trade, and carbon cycle. In our study, we developed an effective, robust, and accurate algorithm for national-scale river mapping, and produced the annual China river extent dataset (CRED) from 2016 to 2023. We assessed the reliability of the CRED based on test samples and data intercomparison. The results indicated that the overall accuracies of the CRED were greater than 88.4% from 2016 to 2023. The rivers of the CRED from 2017 to 2023 achieved good accuracy, with the user accuracies, producer accuracies and F1-score of rivers exceeding 80.4%, 85.0%, and 83.7%, respectively. In 2016, rivers of the CRED achieved medium accuracy, with F1-score of 78.4%. A further data comparison indicated that our CRED had good consistency with existing river-related datasets, with correlation coefficient (R) greater than 0.75. The area statistics indicated that the river area in China were 44948.78 km² in 2023. From 2016 to 2023, the river areas were characterized by an initial increase, followed by a decrease, and then a slight increase. Spatially, the decreased rivers were located mainly in Southeast China, whereas the increased rivers were distributed mainly in Central China and Northeast China. In general, the CRED explicitly delineated river extents and dynamics in China, which could provide a good foundation for improving river ecology and management.

Chein-Shan Liu, Chih-Wen Chang

Besides the closed-form expansion coefficients of a weak-form numerical differentiator (WFND), we introduce a cubic boundary shape function with the aid of two parameters for reducing the boundary errors of fourth-order numerical derivatives to zero. So that the accuracy of numerical derivatives obtained by the new WFND can be improved significantly. The fourth-order numerical derivation can be modeled as a linear beam equation subjecting to specified boundary conditions and displacements to recover an unknown forcing term. By means of boundary shape functions, two numerical collocation methods automatically satisfying the boundary conditions are developed. For a simply supported linear Euler–Bernoulli beam with an elastic foundation, the unknown spatially–temporally dependent force is retrieved. The displacement at a final time and strain on the right-boundary of the beam are over-specified to recover the external force using the method of superposition of boundary shape functions (MSBSF). When the displacement is determined to satisfy the prescribed right-boundary strain, we can recover an unknown spatially–temporally dependent force by inserting the displacement into the linear beam equation. An embedded method (EM) is developed to transform the linear beam model into a vibrating linear beam equation, and then we can develop a robust technique to compute the fourth-order derivative of noisy data by using the EM and MSBSF. The four proposed methods for evaluating the fourth-order derivatives of noisy data are efficient and accurate.

Swarnendu Sekhar Ghosh, Dipankar Mandal, Sandeep Kumar et al.

Accurate crop classification with synthetic aperture radar (SAR) data is a significant area of research and translating into practice from local to regional scale crop inventory mapping. With the growing accessibility to abundant data sources from both current and upcoming dual-polarimetric SAR missions, the capability to generate precise crop maps is set to enhance substantially. The geometric and dielectric properties of targets highly influence radar backscatter. Especially for agricultural crops, which exhibit dynamic changes in target properties and physiological structure throughout their phenology, discriminating between crops using SAR data remains a significant challenge. This study introduces a novel Gaussian process classifier model called the evidence modified Gaussian process classifier (EM-GPC) that employs a regression approach for multiclass crop classification with a modified evidence. We utilize dual-polarimetric SAR data acquired over two study sites to perform crop classification utilizing EM-GPC. At first, we perform a phenology-based single-date crop classification using ESAR C- and L-band SAR data acquired over the DEMMIN site in Germany. The performance evaluation of the EM-GPC model revealed robust accuracy during various crop phenological stages, showcasing its adaptability to temporal variations. Further, we perform a multidate crop classification using C-band RADARSAT-2 and L-band simulated NISAR product from UAVSAR data acquired over Manitoba, Canada. In this study, EM-GPC successfully classifies major crop types (wheat, canola, soybeans, corn, barley, oats, and rye). The efficacy of the proposed model establishes its capability for crop classification utilizing dual-polarimetric SAR data in operational settings.

Bo Rim Ryu, Phan Anh Duong, Hokeun Kang

To mitigate environmental issues and implement energy management strategies, hydrogen is emerging as the most promising and sustainable energy source to help achieve decarbonization targets and meet world energy demands. However, hydrogen poses significant storage and transportation challenges due to its low volumetric and gravimetric density. Hence, ammonia is a potential candidate for a hydrogen storage medium because it contains 17.65% hydrogen by weight, and its volumetric hydrogen density is 45% higher than that of liquid hydrogen. In the maritime sector, these available fuels of ammonia and hydrogen are utilized via internal combustion engines, fuel cells, and gas turbines, which are employed on board ships. This study investigates the possibility of using ammonia and hydrogen as fuels for Solid Oxide Fuel Cells (SOFCs). A combined SOFC-Gas Turbine (GT) system was proposed to generate power for marine propulsion plants. This system was designed and modeled with support from Aspen HYSYS V.12.1. Thermodynamics performances of the proposed system were analyzed using the first and second laws of thermodynamics. The energy efficiencies of direct ammonia and hydrogen SOFCs were 60.96 and 64.46%, respectively. The energy efficiencies of the combined systems increased by 12.37 and 13.97% when using ammonia and hydrogen as fuels, respectively, compared with that of single SOFC systems. The exergy destruction of the primary components with each fuel was examined. Furthermore, a parametric study was performed to select the most suitable fuel utilization factor for the system. This analysis proved that ammonia has the potential as a hydrogen carrier and that waste heat recovery is an effective method to improve the thermodynamic performance of an SOFC system.

Chao Ma, Chuanming Sheng, Jijian Lian et al.

Maorong Chen, Jiong Niu, Ming Li et al.

The echo of shipborne high-frequency surface wave radar (HFSWR) is modulated by six-degrees-of-freedom (6-DOF) motion, affecting the detection of the target and the remote sensing of ocean surface dynamics parameters. Commonly, motion compensation methods of shipborne HFSWR describe each aspect of the 6-DOF motion as the superposition of sinusoidal motion, which results in the effect of motion compensation affected by the precision of 6-DOF motion parameters. A motion compensation method based on dual reference radio frequency (RF) signals is proposed in this paper, without depending on a sinusoidal motion model to describe the 6-DOF motion. By using the motion compensation parameters, which are relevant to the motion attitude and calculated from the information of dual reference RF signals located onshore, the method realizes the compensation of shipborne HFSWR echo modulated by platform 6-DOF motion. This paper proposes the extraction of reference RF signals from radar echo and analyzes the influence of the location of the reference RF signals’ emission source on the motion compensation method. The result shows that a good motion compensation effect is achieved in eliminating the influence of 6-DOF motion modulation. In addition, a traversal of different reference RF signals’ emission source locations is conducted, and the simulation results show that the method proposed in this paper has universality.

Zhiwei Liao, Fei Zhao, Gedong Jiang et al.

Abstract Dynamic movement primitives (DMPs) as a robust and efficient framework has been studied widely for robot learning from demonstration. Classical DMPs framework mainly focuses on the movement learning in Cartesian or joint space, and can't properly represent end-effector orientation. In this paper, we present an extended DMPs framework (EDMPs) both in Cartesian space and 2-Dimensional (2D) sphere manifold for Quaternion-based orientation learning and generalization. Gaussian mixture model and Gaussian mixture regression (GMM-GMR) are adopted as the initialization phase of EDMPs to handle multi-demonstrations and obtain their mean and covariance. Additionally, some evaluation indicators including reachability and similarity are defined to characterize the learning and generalization abilities of EDMPs. Finally, a real-world experiment was conducted with human demonstrations, the endpoint poses of human arm were recorded and successfully transferred from human to the robot. The experimental results show that the absolute errors of the Cartesian and Riemannian space skills are less than 3.5 mm and 1.0°, respectively. The Pearson’s correlation coefficients of the Cartesian and Riemannian space skills are mostly greater than 0.9. The developed EDMPs exhibits superior reachability and similarity for the multi-space skills’ learning and generalization. This research proposes a fused framework with EDMPs and GMM-GMR which has sufficient capability to handle the multi-space skills in multi-demonstrations.

Qian Tao, Qian Wu, Zhaohuan Zhang et al.

Antimicrobial-resistant (AMR) foodborne bacteria causing bacterial infections pose a serious threat to human health. In addition, the ability of some of these bacteria to form biofilms increases the threat level as treatment options may become compromised. The extent of antibiotic resistance and biofilm formation among foodborne pathogens remain uncertain globally due to the lack of systematic reviews. We performed a meta-analysis on the global prevalence of foodborne pathogens exhibiting antibiotic resistance and biofilm formation using the methodology of a Cochrane review by accessing data from the China National Knowledge Infrastructure (CNKI), PubMed, and Web of Science databases between 2010 and 2020. A random effects model of dichotomous variables consisting of antibiotic class, sample source, and foodborne pathogens was completed using data from 332 studies in 36 countries. The results indicated AMR foodborne pathogens has become a worrisome global issue. The prevalence of AMR foodborne pathogens in food samples was greater than 10% and these foodborne pathogens were most resistant to β-lactamase antibiotics with Bacillus cereus being most resistant (94%). The prevalence of AMR foodborne pathogens in human clinical specimens was greater than 19%, and the resistance of these pathogens to the antibiotic class used in this research was high. Independently, the overall biofilm formation rate of foodborne pathogenic bacteria was 90% (95% CI, 68%–96%) and a direct linear relationship between biofilm formation ability and antibiotic resistance was not established. Future investigations should document both AMR and biofilm formation of the foodborne pathogen isolated in samples. The additional information could lead to alternative strategies to reduce the burden cause by AMR foodborne pathogens.

Lei Wang, Jun-Geon Je, Caoxing Huang et al.

In this study, the anti-inflammatory activity of sulfated polysaccharides isolated from the green seaweed <i>Codium fragile</i> (CFCE-PS) was investigated in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages and zebrafish. The results demonstrated that CFCE-PS significantly increased the viability of LPS-induced RAW 264.7 cells in a concentration-dependent manner. CFCE-PS remarkably and concentration-dependently reduced the levels of inflammatory molecules including prostaglandin E₂, nitric oxide (NO), interleukin-1 beta, tumor necrosis factor-alpha, and interleukin-6 in LPS-stimulated RAW 264.7 cells. In addition, in vivo test results indicated that CFCE-PS effectively reduced reactive oxygen species, cell death, and NO levels in LPS-stimulated zebrafish. Thus, these results indicate that CFCE-PS possesses in vitro and in vivo anti-inflammatory activities and suggest it is a potential ingredient in the functional food and pharmaceutical industries.

Changyun Wei, Yijun Wei, Ze Ji

Abstract Cutter Suction Dredgers (CSDs) are a special type of ships designed for construction and maintenance projects of ocean and offshore engineering. During the dredging operation, CSDs can excavate nearly all kinds of soil on the sea bed, and then the dredged materials with coarse particles need to be sucked up by a slurry pump and transported to a disposal area through a long-distance pipeline. In order to avoid sedimentation of slurry in pipeline transportation, the flow rate must be maintained within a reasonable range. Otherwise, the pipeline can be blocked when the slurry density is too high. In this paper, we present a Model Predictive Control (MPC) approach to manipulate the flow rate of slurry in pipeline transportation for a CSD. To demonstrate the advantages of our proposed approach, we also implement three Proportional–Integral–Derivative (PID) controllers (i.e., conventional PID, Fuzzy-PID, and LQR-PID) to make a direct comparison. Moreover, in order to evaluate the effectiveness of our proposed approach in real scenarios, we have, in particular, built a slurry pipeline transportation platform. Both the simulation and experimental results show that our proposed MPC approach is more effective than other PID controllers in controlling the flow rate in the slurry pipeline transportation problem. The proposed approach can provide a guideline for the automated control of the slurry pump for a CSD.

Wengui Xu, Y. Chou, Zih‐Ying Yang et al.

1 Institute of Imaging and Biomedical Photonics, National Chiao Tung University and National Yang Ming Chiao Tung University, 301 Gaofa 3rd Road, Tainan 71150, Taiwan 2 Department of Photonics, National Cheng Kung University, Tainan, Taiwan 3 Institute of Lighting and Energy Photonics, National Chiao Tung University and National Yang Ming Chiao Tung University, 301 Gaofa 3rd Road, Tainan 71150, Taiwan 4 College of Photonics, National Chiao Tung University and National Yang Ming Chiao Tung University, 301 Gaofa 3rd Road, Tainan 71150, Taiwan 5 Department of Photonics, National Chiao Tung University and National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan 6 Institute of Optoelectronic Sciences, National Taiwan Ocean University, Keelung 20224, Taiwan 7 Department of Mechanical and Mechatronic Engineering, National Taiwan Ocean University, Keelung 20224, Taiwan

Mohamed R. Ali, W. Ma, R. Sadat

Abstract This work aims to present nonlinear models that arise in ocean engineering. There are many models of ocean waves that are present in nature. In shallow water, the linearization of the equations requires critical conditions on wave capacity than it make in deep water, and the strong nonlinear belongings are spotted. We use Lie symmetry analysis to obtain different types of soliton solutions like one, two, and three-soliton solutions in a (2+1) dimensional variable-coefficient Bogoyavlensky Konopelchenko (VCBK) equation that describes the interaction of a Riemann wave reproducing along the y-axis and a long wave reproducing along the x-axis in engineering and science. We use the Lie symmetry analysis then the integrating factor method to obtain new solutions of the VCBK equation. To demonstrate the physical meaning of the solutions obtained by the presented techniques, the graphical performance has been demonstrated with some values. The presented equation has fewer dimensions and is reduced to ordinary differential equations using the Lie symmetry technique.

Chang Seop Kwon, Seong Mo Yeon

In this study, a parametric investigation is performed using CFD for towing stability and loads according to the forward and aft slope angles of a barge-shaped FPSO. The forward slope angle is considered in a range of 30–60° and the aft slope is examined in a range of 20–50°. As a result of a comparative study based on CFD towing simulations, it is found that the yaw motion is damped out and stabilized when the aft slope is more than 40° regardless of the forward slope angle. The vortex contours in the y-axis plane near the aft slope are analyzed and it is observed that the vortex developed at the bottom knuckle is bent upward along the aft slope when the aft slope is less than 40°, and completely fallen from the bottom knuckle when the aft slope is more than 40°. Based on the results, a guide to forward and aft slope angles of a barge-shaped FPSO is presented from a practical point of view considering towing stability as well as towing load.

Isabel C. Romero, Jeffrey P. Chanton, Gregg R. Brooks et al.

Following the Deepwater Horizon oil spill (DWHOS), the formation of an unexpected and extended sedimentation event of oil-associated marine snow (MOSSFA: Marine Oil Snow Sedimentation and Flocculent Accumulation) demonstrated the importance of biology on the fate of contaminants in the oceans. We used a wide range of compound-specific data (aliphatics, hopanes, steranes, triaromatic steroids, polycyclic aromatics) to chemically characterize the MOSSFA event containing abundant and multiple hydrocarbon sources (e.g., oil residues and phytoplankton). Sediment samples were collected in 2010–2011 (ERMA-NRDA programs: Environmental Response Management Application – Natural Resource Damage Assessment) and 2018 (REDIRECT project: Resuspension, Redistribution and Deposition of Deepwater Horizon recalcitrant hydrocarbons to offshore depocenter) in the northern Gulf of Mexico to assess the role of biogenic and chemical processes on the fate of oil residues in sediments. The chemical data revealed the deposition of the different hydrocarbon mixtures observed in the water column during the DWHOS (e.g., oil slicks, submerged-plumes), defining the chemical signature of MOSSFA relative to where it originated in the water column and its fate in deep-sea sediments. MOSSFA from surface waters covered 90% of the deep-sea area studied and deposited 32% of the total oil residues observed in deep-sea areas after the DWHOS while MOSSFA originated at depth from the submerged plumes covered only 9% of the deep-sea area studied and was responsible for 15% of the total deposition of oil residues. In contrast, MOSSFA originated at depth from the water column covered only 1% of the deep-sea area studied (mostly in close proximity of the DWH wellhead) but was responsible for 53% of the total deposition of oil residues observed after the spill in this area. This study describes, for the first time, a multi-chemical method for the identification of biogenic and oil-derived inputs to deep-sea sediments, critical for improving our understanding of carbon inputs and storage at depth in open ocean systems.

M. Mrokowska, A. Krztoń-Maziopa

In this study, xanthan gum is used as a model exopolymer to demonstrate potential effects of non-Newtonian properties of natural aquatic systems on settling dynamics of particles. Rheological measurements combined with settling experiments using visualization methods revealed that instantaneous velocity fluctuations and a flow pattern formed around a particle are the effects of solution viscoelasticity and shear-thinning properties and that the average settling velocity depends on the exopolymer concentration and particle size. Our study showed that in the considered conditions a disk-shaped particle settles preferably in vertical position with a negative wake behind. The understanding of these processes is essential in technology and engineering and is necessary to improve prediction accuracy of large-scale sedimentation processes and biogeochemical cycles in the ocean involving settling of minerals, marine snow, microplastics, and locomotion of microorganisms.

Guilin Liu, Baiyu Chen, Song Jiang et al.

Wave height and wave period are important oceanic environmental factors that are used to describe the randomness of a wave. Within the field of ocean engineering, the calculation of design wave height is of great significance. In this paper, a periodic maximum entropy distribution function with four undetermined parameters is derived by means of coordinate transformation and solving conditional variational problems. A double entropy joint distribution function of wave height and wave period is also derived. The function is derived from the maximum entropy wave height function and the maximum entropy periodic function, with the help of structures of the Copula function. The double entropy joint distribution function of wave height and wave period is not limited by weak nonlinearity, nor by normal stochastic process and narrow spectrum. Besides, it can fit the observed data more carefully and be more widely applicable to nonlinear waves in various cases, owing to the many undetermined parameters it contains. The engineering cases show that the recurrence level derived from the double entropy joint distribution function is higher than that from the extreme value distribution using the single variables of wave height or wave period. It is also higher than that from the traditional joint distribution function of wave height and wave period.

Qingyun Li, Zhibin Yu, Yubo Wang et al.

The high human labor demand involved in collecting paired medical imaging data severely impedes the application of deep learning methods to medical image processing tasks such as tumor segmentation. The situation is further worsened when collecting multi-modal image pairs. However, this issue can be resolved through the help of generative adversarial networks, which can be used to generate realistic images. In this work, we propose a novel framework, named TumorGAN, to generate image segmentation pairs based on unpaired adversarial training. To improve the quality of the generated images, we introduce a regional perceptual loss to enhance the performance of the discriminator. We also develop a regional <inline-formula><math display="inline"><semantics><msub><mi>L</mi><mn>1</mn></msub></semantics></math></inline-formula> loss to constrain the color of the imaged brain tissue. Finally, we verify the performance of TumorGAN on a public brain tumor data set, BraTS 2017. The experimental results demonstrate that the synthetic data pairs generated by our proposed method can practically improve tumor segmentation performance when applied to segmentation network training.