Search Results (268)

To investigate the internal flow characteristics of particles during hydraulic lifting in deep-sea mining risers, this study developed a three-dimensional curved riser multiphase flow model based on the Eulerian–Eulerian framework and the RNG k-ε turbulence model. The effects of particle distribution and pressure loss in the curved section, as well as the influence of curvature radius, were analyzed. Results indicate that particle distributions take concave circular or crescent-shaped patterns, becoming more uniform with larger curvature radii. Pressure on the extrados is consistently greater than on the intrados, with pressure loss increasing in the bend and peaking at the midpoint. A larger curvature radius leads to greater total pressure loss but lower frictional loss. Additionally, the bend experiences a restoring force toward the vertical position, which increases as the curvature radius decreases. Full article

With the development of modern manufacturing industry, complex surface parts are more and more widely used in aerospace, automobile manufacturing, the shipbuilding industry, and many other fields; furthermore, their machining demand is growing explosively, and CNC machining technology has become the mainstream machining method of complex surface parts because of its high precision and high efficiency. However, CNC machining of complex surfaces faces many challenges, especially the generation and optimization of tool trajectories. Therefore, vector field-based tool path planning methods have emerged, aiming to improve the efficiency and accuracy of CNC machining of complex surfaces. This paper focuses on the tool trajectory optimization problem in CNC machining of complex surfaces and reviews the current research status of vector field-based tool path planning for surface machining. The study explores the concept of symmetry in the design of tool paths, highlighting the importance of symmetrical vector fields in achieving efficient and high-precision machining. By analyzing the symmetrical properties of complex surfaces and the corresponding vector fields, this paper discusses the current status, difficulties, and core problems of relevant methods, pointing out the direction of breakthroughs and the future development trend. The findings provide a reference and basis for the realization of efficient and high-precision CNC machining of complex surfaces. Full article

Automatic component recognition plays a crucial role in intelligent ship manufacturing, but existing methods suffer from low recognition accuracy and high computational cost in industrial scenarios involving small samples, component stacking, and diverse categories. To address the requirements of shipbuilding industrial applications, a Triplet Spatial Reconstruction Attention (TSA) mechanism that combines threshold-based feature separation with triplet parallel processing is proposed, and a lightweight You Only Look Once Ship (YOLO-Ship) detection network is constructed. Unlike existing attention mechanisms that focus on either spatial reconstruction or channel attention independently, the proposed TSA integrates triplet parallel processing with spatial feature separation–reconstruction techniques to achieve enhanced target feature representation while significantly reducing parameter count and computational overhead. Experimental validation on a small-scale actual ship component dataset demonstrates that the improved network achieves 88.7% mean Average Precision (mAP), 84.2% precision, and 87.1% recall, representing improvements of 3.5%, 2.2%, and 3.8%, respectively, compared to the original YOLOv8n algorithm, requiring only 2.6 M parameters and 7.5 Giga Floating-point Operations per Second (GFLOPs) computational cost, achieving a good balance between detection accuracy and lightweight model design. Future research directions include developing adaptive threshold learning mechanisms for varying industrial conditions and integration with surface defect detection capabilities to enhance comprehensive quality control in intelligent manufacturing systems. Full article

The frequency-domain free-surface Green’s function method is widely used in solving ship hydrodynamic problems, with its core challenge lying in the computation of the Green’s function and its partial derivatives. This study analyzes the relationship between the free-surface Green’s function and its derivatives, proposing a machine learning-based recursive prediction method termed the pulsating source recursive prediction method. The accuracy and efficiency of this method under various parameter settings are investigated, and its application to the hydrodynamic calculations of container ship S175 and a bulk carrier is demonstrated. Results show that the predicted Green’s function achieves an accuracy of 3–6 decimals, with computational efficiency surpassing numerical methods and matching analytical approaches. The hydrodynamic results are reliable, confirming the method’s practical value. Full article

Sonar is the primary tool used for detecting small targets at long distances underwater. Due to the influence of the underwater environment and imaging mechanisms, sonar images face challenges such as a small number of target pixels, insufficient data samples, and uneven category distribution. Existing target detection methods are unable to effectively extract features from sonar images, leading to high false positive rates and affecting the accuracy of target detection models. To counter these challenges, this paper presents a novel sonar small-target detection framework named DCE-Net that refines the YOLOv8 architecture. The Detail Enhancement Attention Block (DEAB) utilizes multi-scale residual structures and channel attention mechanism (AM) to achieve image defogging and small-target structure completion. The lightweight spatial variation convolution module (CoordGate) reduces false detections in complex backgrounds through dynamic position-aware convolution kernels. The improved efficient multi-scale AM (MH-EMA) performs scale-adaptive feature reweighting and combines cross-dimensional interaction strategies to enhance pixel-level feature representation. Experiments on a self-built sonar small-target detection dataset show that DCE-Net achieves an mAP@0.5 of 87.3% and an mAP@0.5:0.95 of 41.6%, representing improvements of 5.5% and 7.7%, respectively, over the baseline YOLOv8. This demonstrates that DCE-Net provides an efficient solution for underwater detection tasks. Full article

With the development of the shipbuilding industry, nonparametric prediction has become the mainstream method for predicting ship maneuvering motion. However, the lack of transparency and interpretability make the output process of the prediction results challenging to track and understand. An interpretable deep learning framework based on the NbeatsX model is presented for nonparametric ship maneuvering motion prediction. Its three-tier fully connected architecture incorporates trend, seasonal, and exogenous constraints to decompose motion data, enhancing temporal and contextual learning while rendering the prediction process transparent. On the KVLCC2 zig-zag maneuver dataset, NbeatsX achieves NRMSEs of 0.01872, 0.01234, and 0.01661 for surge speed, sway speed, and yaw rate, with SMAPEs of 9.21%, 6.40%, and 7.66% and R² values all above 0.995, yielding a more than 20% average error reduction compared with LS-SVM, LSTM, and LSTM–Attention and reducing total training time by about 15%. This method unifies high-fidelity forecasting with transparent decision tracing. It is an effective aid for ship maneuvering, offering more credible support for maritime navigation and safety decision-making, and it has substantial practical application potential. Full article

Impulse current measurement technology is widely used in various applications, including lightning protection monitoring in power systems, welding current measurement in aircraft and shipbuilding industries, as well as high-current measurement in pulsed power systems. With the advancement of industrial technology, the measurement range of impulse currents has continuously expanded, reaching levels as high as mega-amperes (MA). The calibration of the scale factor for impulse current measurement devices is determined through comparison with standard measurement devices. Developing high-accuracy impulse current measurement devices and accurately judging their characteristics are prerequisites for ensuring the precise calibration of impulse current values. This paper introduces two different types of high-impulse current measurement devices. Experimental studies were conducted on the scale factor and response characteristics of the sensors. The scale factor extension calibration method for sensors under high currents of more than 100 kA has also been introduced. Test results indicate that the developed impulse current measurement devices can serve as standard measurement devices for high impulse current measurement. Full article

With the natural evolution of the Arctic route and advancements in related technologies, the development of new green ice-class ships is becoming a key technological breakthrough for the global shipbuilding industry. As a special vessel form that must perform icebreaking operations and undertake long-distance ocean voyages, an ice-class ship requires sufficient icebreaking capacity to navigate ice-covered water areas. However, since such ships operate for most of their time under open water conditions, it is also crucial to consider their resistance characteristics in these environments. Firstly, this paper employs linear interpolation to extract wind, wave, and sea ice data along the route and calculates the proportion of ice-covered and open water area in the overall voyage. This provides data support for hull form optimization based on real sea state conditions. Then, a resistance optimization platform for ice-class ships is established by integrating hull surface mixed deformation control within a scenario analysis framework. Based on the optimization results, comparative analysis is conducted between the parent hull and the optimized hull under various environmental resistance scenarios. Finally, the optimization results are evaluated in terms of energy consumption using a fuel consumption model of the ship’s main engine. The optimized hull achieves a 16.921% reduction in total resistance, with calm water resistance and wave-added resistance reduced by 5.92% and 27.6%, respectively. Additionally, the optimized hull shows significant resistance reductions under multiple wave and floating ice conditions. At the design speed, calm water power and hourly fuel consumption are reduced by 7.1% and 7.02%, respectively. The experimental results show that the hull form optimization process in this paper can take into account both ice-region navigation and ice-free navigation. The design ideas and solution methods can provide a reference for the design of ice-class ships. Full article

Friction stir welding (FSW) is a novel welding technique that produces a solid-state weld by generating frictional heat and plastic deformation at the weld spot with a revolving, non-consumable welding tool. Despite processing a wide range of industrial materials, FSW has concentrated on welding aluminum and its alloys because of its high strength-to-weight ratio and uses in the shipbuilding, aerospace, and other fabrication industries. Important FSW process factors that determine the mechanical qualities of the weldment are the tool tilt angle, tool traverse feed, tool pin profile, tool rotational speed (TRS), tool traverse speed (TTS), tool pin profile (TPP), and shoulder plunge depth. Variations in the required process parameters cause defects, which lower the weld quality of FSWed aluminum alloys (AA). Therefore, keeping an eye on and managing the FSW process is crucial to preserving the caliber of the weld joints. The current study aims to investigate the changes in the mechanical characteristics and microstructure of the FSWed AA5052-H111 and AA6061-T6 joints. To perform the FSW experiments, we varied TRS, TTS, and TPP on plates that were 5 mm thick and had a butt joint structure. Following welding, the microstructure of the weld zones was examined to observe how the grains had changed. The joint’s tensile strength reached a maximum of 227 MPa for the square-shaped TPP, and the micro-Vickers hardness test results showed a maximum of 102 HV at the weld nugget zone (WNZ). Full article

Since the beginning of the last decade, digital technological achievements have ushered the economies of developed countries into the fourth industrial revolution, transforming industries into smart ones, referred to as “Industry 4.0”, enabling them to innovate as a prerequisite for sustainable development and economic growth. At the same time, the European Union’s institutions are adopting strategies and programs to transform the European industry into a climate-neutral one, aiming to achieve this by 2050. The authors, participating in the introduction of Lean tools and digital technologies into one of the European shipyards using the “CULIS” (Connect Universal Lean Improvement System) methodology, recognize the high potential of its contribution to the European Commission’s guidelines for transitioning the economy to a sustainable one, and for this purpose, they present it in this paper. Namely, the methodology in question not only theoretically results in a “quick” implementation of tools and doctrines—with an approximately 36-month total duration of the process—but also encompasses as many as three transformations: Lean, digital, and green; an analysis of a methodology with such characteristics significantly adds to the originality of this study. The current stage of the observed shipyard’s “triple” transformation process already results in significant improvements—e.g., an increase in productivity by around 21% or a reduction in sales process costs by 38%. However, given its ongoing pilot phase, (further) analyses of improvements in (European) shipbuilding competitiveness and profitability that can be achieved through digital Lean management of projects’ realization process are implied. Full article

Shipyards are significant industrial sources of environmental pollution, releasing substantial amounts of heavy metals, petroleum hydrocarbons, and organic solvents into soil and groundwater during shipbuilding and maintenance operations. Such contamination not only affects the shipyard premises but also poses serious environmental threats to nearby communities, raising concerns about the long-term sustainability of the shipbuilding industry. Given the increasing global emphasis on sustainable industrial practices, addressing shipyard-related pollution has become a critical environmental challenge. This review aims to provide a comprehensive understanding of the pollution issues associated with shipyards and explore effective remediation strategies. It focuses on contamination in both soil and groundwater, and covers pollution generated throughout the shipbuilding and maintenance lifecycle. First, it examines previous studies to identify the major contaminants and pollution sources typically found at shipyard sites. Next, the paper reviews recent advances in soil and groundwater remediation technologies, including physical, chemical, and biological methods tailored to the unique challenges of shipyard environments. Finally, the review discusses current limitations in remediation practices and outlines potential directions for future research and technological development. Full article

In this study, a strategy was adopted to promote the formation of NiAl precipitates with the aim of enhancing strength by incorporating a 0.2 wt.% Al into a traditional ultra-low carbon bainitic (ULCB) steel alloy. By integrating thermo-mechanical control processing (TMCP) and a tailored tempering process, a new-generation steel with an outstanding combination of properties has been successfully developed for shipbuilding and marine engineering equipment. It features a yield strength of 880 MPa, a yield ratio of 0.84, and an impact toughness of 175 J. The precipitation characteristics of nanoscale particles in this steel, including NiAl intermetallics and carbides, were systematically investigated. The results show that the alloy with low Al addition formed NiAl precipitates during tempering. The high-density distributions of NiAl, (Mo, V)C, and (Ti, V, Nb)C precipitates, which exhibit slow coarsening kinetics, played a dominant role in enhancing the strength of the tempered steel. In addition to precipitation, the microstructure before and after tempering was also analyzed. It was observed that a granular bainite morphology was favorable for decreasing the yield ratio. Additionally, the formation of reverse-transformed austenite during tempering was critical for retaining toughness despite substantial strength gains. Finally, theoretical modeling was employed to quantitatively assess the contributions of these microstructural modifications to yield strength enhancement of thermo-mechanical controlled processing (TMCP) and tempered steel. This study establishes a fundamental basis for subsequent industrial-scale development and practical engineering applications of novel products. Full article

Helical idler gear transmission systems can adapt to high-speed, heavy-load working environments and are thus widely used in aerospace, shipbuilding, and other heavy industry sectors. Root crack is one of the common fault types. Prior studies generally only considered cracks at a single working flank, lacking comparative analysis between the crack at the working flank and the non-working flank. This paper examines the dynamic response of helical idler gears with root cracks at different working flanks, comparing dynamic response differences between working and non-working flank cracks. First, a comprehensive dynamics model of the helical idler gear system is established. Second, the influence of root crack location (the working flank or the non-working flank) on time-varying meshing stiffness is considered based on potential energy method, and a flexible model is established by finite element method for the faulty gear. Finally, solution results of the rigid-flexible coupling dynamics model are analyzed. The dynamic response signal characteristics of root cracks at the working flank and the non-working flank are analyzed in time domain, frequency domain and time frequency domain, respectively. Corresponding experiments are designed based on the FZG experimental platform, and the experimental results are in good agreement with the simulation results, which verified the accuracy of the model. Full article

In recent years, protecting stainless steel from corrosion has become crucial, particularly in harsh environments. The present study focuses on improving the photocathodic corrosion resistance of 304 stainless steel (304SS) by fabricating TiO₂/CuO composite coatings using the spin coating technique with varying CuO weight percentages. Structural characterization through X-ray diffraction (XRD) confirmed the presence of the anatase phase of TiO₂ and the successful integration of CuO. Raman spectroscopy demonstrated redshifts in the TiO₂ characteristic peaks, suggesting changes in bond lengths attributed to CuO incorporation. These findings were further corroborated by Fourier-transform infrared (FTIR) spectroscopy. Surface characterization showed uniform, porous coatings with pore sizes ranging from 75 to 200 nm, which contributed to improved barrier properties. UV–visible diffuse reflectance spectroscopy (UV-DRS) demonstrated enhanced visible light absorption in the heterostructures. Mott–Schottky analysis confirmed improved charge carrier density and favorable band alignment, facilitating efficient charge separation. The electrochemical performance was evaluated in 3.5% NaCl solution under dark and light environments. The results demonstrated that the TiO₂/CuO heterostructure significantly enhanced electron transfer and suppressed electron-hole recombination, providing adequate photocathodic protection. Notably, under illumination, the TiO₂/CuO (0.005 g) coating achieved a corrosion potential of −255 mV vs SCE and reduced the corrosion current density to 0.460 × 10⁻⁶ mA cm⁻². These findings suggest that TiO₂/CuO coatings offer a promising, durable, and cost-effective solution for corrosion protection in industries such as oil, shipbuilding, and pipelines. Full article

316L stainless steel is widely employed in various industrial sectors, including shipbuilding, offshore plants, high-temperature/high-pressure (HTHP) piping systems, and hydrogen infrastructure, due to its excellent mechanical stability, superior corrosion resistance, and robust resistance to hydrogen embrittlement. This study presents 316L stainless steel alloys fabricated via hot isostatic pressing (HIP), conducted at 1300 °C and 100 MPa for 2 h, incorporating Cr₂N powder and an optimized Ni/Mn ratio based on the nickel equivalent (Ni_eq). During HIP, Cr₂N decomposition yielded a uniformly refined, dense austenitic microstructure, with enhanced corrosion resistance and mechanical performance. Corrosion resistance was evaluated by potentiodynamic polarization in 3.5 wt.% NaCl after 1 h of OCP stabilization, using a scan range of −0.25 V to +1.5 V (Ag/AgCl) at 1 mV/s. Optimization of the Ni/Mn ratio effectively improved the pitting corrosion resistance and mechanical strength. It is cost-effective to partially substitute Ni with Mn. Of the various alloys, C13Ni-N exhibited significantly enhanced hardness (~30% increase from 158.3 to 206.2 HV) attributable to nitrogen-induced solid solution strengthening. E11Ni-HM exhibited the highest pitting corrosion resistance given the superior PREN value (31.36). In summary, the incorporation of Cr₂N and adjustment of the Ni/Mn ratio effectively improved the performance of 316L stainless steel alloys. Notably, alloy E11Ni-HM demonstrated a low corrosion current density of 0.131 μA/cm², indicating superior corrosion resistance. These findings offer valuable insights for developing cost-efficient, mechanically robust corrosion-resistant materials for hydrogen-related applications. Further research will evaluate alloy resistance to hydrogen embrittlement and investigate long-term material stability. Full article