Search Results (78)

E36 steel, widely used in shipbuilding and offshore structures, offers moderate strength and excellent low-temperature toughness. However, its welded joints are highly susceptible to fatigue failure. Cracks typically initiate at weld toes or within the heat-affected zone (HAZ), severely limiting the fatigue life of fabricated components. Traditional life prediction methods are complex, inefficient, and lack accuracy. This study proposes a machine learning (ML) framework for efficient fatigue life prediction of E36 welded joints. Welded specimens using SQJ501 filler wire on prepared E36 steel established a dataset from 23 original fatigue test data points. The dataset was expanded via Z-parameter model fitting, with data scarcity addressed using SMOTE. Pearson correlation analysis validated data relationships. After grid-optimized training on the augmented data, models were evaluated on the original dataset. Results demonstrate that the machine learning models significantly outperformed the Z-parameter formula (R² = 0.643, MAPE = 16.15%). The artificial neural network (R² = 0.972, MAPE = 4.45%) delivered the best overall performance, while the random forest model exhibited high consistency between validation (R² = 0.888, MAPE = 6.34%) and testing sets (R² = 0.897), with its error being significantly lower than that of support vector regression. 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

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

Thin steel plates with stiffeners are widely used in shipbuilding, aeronautics, and civil construction due to their lightness and structural strength. This study presents a numerical model developed using ANSYS Mechanical APDL with SHELL281 finite elements to evaluate the deflection of thin steel plates with trapezoidal-shaped box-beam stiffeners, known as hat-stiffened plates. The structure is analyzed under a uniformly distributed load perpendicular to the plate, with simply supported boundary conditions. The constructal design method combined with the exhaustive search technique is employed to optimize the geometry. A volume fraction of 30% is used, transferring material from the reference plate (without stiffeners) to the stiffeners, defining parameters such as number, height, and thickness—considered degrees of freedom. The stiffener angle is fixed at 120°. The results show that increasing stiffener height and reducing thickness generally improve structural performance by reducing deflections. The best configuration with transverse stiffeners reduced deflection by 97.15% compared to the reference plate, and by 79.27% compared to the best longitudinal configuration from previous studies. Therefore, transverse stiffeners were more effective than longitudinal ones. This study highlights the importance of stiffener orientation and geometry in the structural optimization of thin steel plates. Full article

This study constructed a DGC-t-MSV model by integrating dynamic correlation and Granger causality into the MSV framework. Using daily closing price data from 4 January 2022 to 21 November 2024, it empirically analyzed volatility spillover effects between China’s carbon market and traditional manufacturing from an industrial heterogeneity perspective. The findings are as follows: (1) The carbon market exhibits significant unidirectional volatility spillover effects on carbon-intensive industries, such as steel, chemicals, shipbuilding, and automobile manufacturing, with the carbon market acting as the spillover source. (2) Bidirectional volatility spillover effects exist between the carbon market and industries such as forest products, textiles, construction engineering, and machinery manufacturing, with the carbon market predominantly acting as a recipient. (3) The carbon market exhibits general dynamic correlations with traditional manufacturing industries, where the correlation strength is positively associated with industry-level carbon emissions. Notably, the correlations with the steel, chemicals, machinery manufacturing, construction engineering, and automobile manufacturing industries are significant, whereas those with the textile industry and the forest products industry are relatively weaker. Furthermore, the carbon market demonstrates substantially higher volatility than traditional manufacturing industries. This study innovatively explored volatility spillover effects between China’s carbon market and traditional manufacturing from an industrial heterogeneity perspective, providing policy implications for their coordinated development. Full article

The development of eco-friendly paint formulations is part of the transition process to more sustainable materials, which involves many industries such as offshore and shipbuilding, where the deterioration of steel in seawater is a key factor. This article aims to produce innovative coatings and test their protective action on DH 36 steel plates. SiO₂ and TiO₂ were modified with amino groups and iron sites to be used as filler for the design of ecological paint formulations The antimicrobial features of both NH₂ groups and iron ionic species were combined with the chemical and mechanical stability of silica and titania, with silica-based powders showing increased efficacy. The surface properties of the resulting coatings were examined by determination of thickness, water wettability, roughness, and cross-cut adhesion tests (before and after a degradation test in seawater according to ASTM D870-97 standards). Preliminary tests of the microbiological activity of the iron amino functionalized materials were carried out to monitor, as proof of concept, the growth of some bacterial strains through measurements of optical density. The findings indicate that these coatings not only provide effective corrosion protection but are promising for enhancing the durability and environmental performance of steel surfaces exposed to marine environments. Full article

The purpose of this paper is to investigate the impact of the applied WC/C and CrN + WC/C protective coatings applied using various PVD methods as protection for cavitation generators operating in an environment of intense cavitation wear. In order to carry out planned tasks, special devices generating a cavitation environment have been designed and manufactured. As part of this study, an analysis of the surface of cavitation generators, both before applying the coatings and with the applied protective PVD coatings, and also before and after operation in a cavitation environment, was carried out using the following research techniques: stereoscopic microscopy, scanning electron microscopy, transmission microscopy, XRD, and confocal microscopy. Despite the use of corrosion-resistant steels as a result of the cavitation environment, this causes surface material wear, especially in the area of the through holes. This is due to the fact that there are no protective coatings inside the through hole. Moreover, it was found that, for the tested steel with multilayer CrN + WC/C coatings, there were significantly fewer cavitation defects both on the surface of the material and on the edge of through holes, which indicates that the use of these multilayer coatings can significantly extend the service life of structural elements operating in such environmental conditions. Based on the conducted research tests, it was proven that the applying protective coatings significantly reduce the wear of the surfaces of the tested cavitation generators, thus allowing the use of cheaper steels, not resistant to corrosion, e.g., P265GH steel, which is five times cheaper than austenitic steel. The P265GH steel is used for structural elements in the heating, petrochemical, energy, food, and chemical industries, as well as for structural elements in the aviation, shipbuilding, and many other industries, and, thus, it is possible to reduce the costs associated with the operation of this construction solution in industrial conditions. Full article

In the shipbuilding industry, the inefficiency of the successive approximation control method in CNC cold-bending machines has hindered productivity in steel bending manufacturing, particularly for rib profiles. This study proposes control methods for cold bending machines based on deep learning models to address this challenge, including CNN and Transformer-CNN (T-CNN), to predict the elastic spring-back rate of cold-processed metal profiles and generate precise control pulses for achieving target bending angles. Experimental validation using real-world datasets collected from a shipyard’s CNC cold bending machine demonstrates that the T-CNN model significantly reduces the number of steps required for each bending operation, achieving a 75% reduction in production time and substantially enhancing processing efficiency. By leveraging the strengths of CNNs and Transformer architectures, the T-CNN model excels at handling long sequence data and capturing global dataset characteristics. Results show that the T-CNN model outperforms traditional control methods and standard CNNs in prediction accuracy, stability, and efficiency, making it a superior choice for cold bending control. Full article

Nickel significantly increases the toughness of steel and makes it ideal for use in applications that require high impact and fracture resistance at low temperatures. These inherent advantages position nickel steel as indispensable material in various domains, with a pronounced presence in stationary Liquefied Natural Gas (LNG) tanks and in the shipbuilding industry, particularly for tanks in vessels intended for the transport of liquefied ethane and LNG. The presented study focuses on assessing the fracture toughness behaviour of nickel alloy steel 1.5662+QT640 under sub-zero and cryogenic temperatures. The fracture performance of the material was evaluated, specifically emphasizing the impact toughness and fracture toughness characteristics of the material. Moreover, it was discussed if the transferability of the experimental results to the well-known fracture mechanics-based concept of EN 1993-1-10, which relies on the master curve concept, is possible. The results show that the master curve concept is not applicable to the nickel alloy steel 1.5662+QT640 due to its exceptional fracture toughness behaviour at very low temperatures. Full article

In the shipbuilding industry, during the painting process, workers are exposed to various substances in paint, including organic solvents that can adversely affect their health. Most workplace exposures to organic solvents involve mixtures of organic compounds. Therefore, in this study, the hazard quotient (HQ) and hazard index (HI) were derived using data from the Workplace Environmental Monitoring Program in Korea for six organic solvents (xylene, n-butanol, ethylbenzene, isobutyl alcohol, toluene, and methylisobutyl ketone [MIBK]) commonly used in the steel shipbuilding industry. The non-carcinogenic risk was assessed using Monte Carlo simulations, and sensitivity analysis was performed using the Spearman rank correlation coefficient with the R program. The HI for neurotoxicity and developmental toxicity exceeded 1 in the 25th and 75th percentile, respectively. According to the sensitivity analysis, the HI for neurotoxicity was correlated with the concentration of xylene and its exposure duration, whereas that for developmental toxicity was correlated with the concentration of ethylbenzene and MIBK and their exposure duration. This study investigated the health risks posed by organic solvents among workers involved in the painting process of shipbuilding. Additional research on percutaneous exposure to organic solvents and a detailed process analysis are needed. Full article

The linear heating and formation of steel plates is one of the most critical technologies in shipbuilding. Excellent technology not only provides good hydrodynamics for the hull but also affects the whole hull construction cycle and cost. In the heating and formation of a steel plate, the material, size, and thickness of the steel plate; heating temperature; heating position; and many other factors affect the formation of a steel plate. It is a very difficult process to know the influence relationship between various factors. In this study, a steel plate model is established by the Gaussian regression method, which can predict the steel plate deformation according to the selected steel plate material, size and thickness, heating temperature, and heating position. The accuracy of the model was evaluated, and the Gaussian process regression model has a better accuracy compared to other machine learning algorithm models. Finally the model visualization; designing the UI; selecting the steel plate material, size, and thickness; and inputting the heating temperature, the deformation magnitude, and stress magnitude of the steel plate can be obtained. The model can provide guidance to field workers for the heating and formation of hull steel plates and achieve efficient and fast formation of target steel plates. Full article

This paper comprehensively examines three structural steel grades’ microstructural features and mechanical properties, evaluating their suitability for shipbuilding applications. The steels analyzed include quench and tempered (Q and T) steel, thermomechanical controlled processed (TMCP) steel, and hot rolled (HR) steel. A microstructural characterization was performed using optical microscopy (OM), scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD). The analysis was complemented by extensive mechanical testing including assessments of hardness, tensile, and Charpy impact tests across a range of temperatures. Additionally, corrosion behavior was evaluated using the potentiodynamic polarization test. The findings revealed that Q and T grade steel exhibited the most refined microstructure, characterized by a complex mixture of ferrite, tempered martensite, upper bainite, and Fe₃C phases. In contrast, the TMCP grade steel demonstrated a balanced microstructure of polygonal ferrite and pearlite. Meanwhile, the HR grade steel contained polygonal ferrite and aligned pearlite. The tensile testing results demonstrated that the Q and T grade steel had superior hardness, yield strength (YS), and ultimate tensile strength (UTS), although it exhibited the lowest elongation % (El %). The TMCP grade steel met all ABS standards for marine steels, displaying optimal YS, UTS, and El %. Despite the superior YS of the HR grade steel, it did not meet the necessary criteria for UTS. Charpy impact tests revealed that the TMCP grade steel exhibited the highest impact energy absorption across a range of temperatures. As a result, the TMCP grade steel emerged as the optimal choice for ship construction, fulfilling all ABS requirements with a balanced combination of strength, ductility, and impact energy absorption. Additionally, the potentiodynamic polarization results revealed that the Q and T grade steel demonstrated the highest corrosion resistance. Following Q and T steel, the HR grade steel ranked second in corrosion resistance, with TMCP steel closely behind, showing only a slight difference. Full article

The maintenance of the surface of steel structures is crucial for ensuring the quality of shipbuilding cranes. Various types of wall-climbing robots have been proposed for inspecting diverse structures, including ships and offshore installations. Given that these robots often operate in outdoor environments, their performance is significantly influenced by wind conditions. Consequently, understanding the impact of wind loads on these robots is essential for developing structurally sound designs. In this study, SolidWorks software was utilized to model both the wall-climbing robot and crane, while numerical simulations were conducted to investigate the aerodynamic performance of the magnetic wall-climbing inspection robot under wind load. Subsequently, a MATLAB program was developed to simulate both the time history and spectrum of wind speed affecting the wall-climbing inspection robot. The resulting wind speed time-history curve was analyzed using a time-history analysis method to simulate wind pressure effects. Finally, modal analysis was performed to determine the natural frequency and vibration modes of the frame in order to ensure dynamic stability for the robot. The analysis revealed that wind pressure predominantly concentrates on the front section of the vehicle body, with significant eddy currents observed on its windward side, leeward side, and top surface. Following optimization efforts on the robot’s structure resulted in a reduction in vortex formation; consequently, compared to pre-optimization conditions during pulsating wind simulations, there was a 99.19% decrease in induced vibration displacement within the optimized inspection robot body. Modal analysis indicated substantial differences between the first six non-rigid natural frequencies of this vehicle body and those associated with its servo motor frequencies—indicating no risk of resonance occurring. This study employs finite element analysis techniques to assess stability under varying wind loads while verifying structural safety for this wall-climbing inspection robot. Full article

Accurate cost estimates are essential for staying in business in a competitive shipbuilding industry. With new technologies and the energy transition creating an ever-changing landscape, traditional cost estimation methods based on product specifications can no longer keep pace. The need for improvement especially arises for Engineering-To-Order projects, considering that the profit margins are narrow. The use of process information in the estimation process could increase the reliability and flexibility of these estimations. This article presents a concept that utilizes graph theory to include process information in the cost estimations applied to steel buildings. This concept is specifically suited for the early stages of Engineering-To-Order projects. Full article