Search Results (51)

Stretch-bending straightening is used to ensure the desired flatness properties of packaging steel in the final stage of semi-finished product manufacturing. Not only is the flatness of the steel affected by the alternating bending load and the tensile load during the stretch-bending straightening process, but the mechanical properties also change depending on several factors. It was found out that the stretch-bending straightening parameters, the temper-rolling degree and the amount of interstitial elements have an influence on this change in mechanical properties. A follow-up ageing process, after stretch-bending straightening, also has a significant impact on this change. Based on these observations, a multivariate prediction model is developed describing the dependence between straightening parameters and resulting yield strength characteristics in non-aged and aged conditions for three different packaging steels. Full article

The scalability and processability of high-performance membranes remain significant challenges in membrane technology. This work focuses on optimizing the pilot-scale production of patterned polysulfone (PSf) ultrafiltration membranes using the spray-modified non-solvent-induced phase separation (s-NIPS) method on a roll-to-roll pilot line. s-NIPS has already been studied extensively at lab-scale to prepare patterned membranes for various applications including membrane bioreactors (MBR), reverse osmosis (RO) and forward osmosis (FO). Although studied at the lab scale, membranes prepared at a larger scale can significantly differ in performance; therefore, phase inversion parameters, including polymer concentration, molecular weight, and additive type (i.e., polyethylene glycol (PEG) or polyvinylpyrolidine (PVP)) and concentration, were systematically varied when casting on a roll-to-roll, 12″ wide pilot line to identify optimal conditions for achieving defect-free, high-performance, patterned PSf membranes. The membranes were characterized for their pure water permeance, BSA rejection, casting solution viscosities, and resulting morphology. s-NIPS patterned membranes exhibit 150–350% increase in water flux as compared to their reference flat membrane, thanks to very high pattern heights up to 825 µm and formation of finger-like macrovoids. This work bridges the gap between lab-scale and pilot-scale membrane preparation, while proposing an upscaled membrane with great potential for use in water treatment. Full article

Effective real-time control systems require fast and accurate models. The roll bending models presented in this paper are proposed for a real-time control system for the design of the rolling schedule. The roll bending, with other factors, defines the shape of the roll surface, its convexity, and finally the shape of the final product of the flat rolling, its convexity, and its flatness. This paper presents accurate finite element (FE) models for a four-high mill. The models serve to obtain accurate solutions to the problem of roll bending, taking into account the rolling force, width of the rolling sheet (strip), initial shape of the roll surface, and the anti-bending force. The results of the FE simulation are used to train three models developed on the basis of the neural network (NN) for the solution of one direct and two inverse tasks. The pre-trained NN model gives accurate results and is faster than the FE model (FEM). The calculation time on a personal computer for one case of 3D FEM is 1 to 2 min, for 2D FEM it is 1 s, and for NN it is less than 1 ms. The results can be immediately used by other models of the real-time control system. A novelty of the research presented in the paper is the creation of complex applications of the FE method and an NN as a reduced-order model (ROM) for prediction of roll bending and calculation of sheet (strip) convexity, rolling, and anti-bending forces to obtain the required convexity. Full article

Effective real-time control systems require fast and accurate models. The thermal profile models of the rolls presented in this paper are proposed for a real-time control system for the design of the rolling schedule. The thermal profile of the roll defines the shape of the roll surface, its convexity, and, finally, the shape of the final product of the flat rolling, its convexity, and flatness. This paper presents accurate semi-analytical and finite element (FE) models, which serve to obtain an accurate solution of the joint thermal and mechanical problem, that is, heat transfer and thermal expansion. The results of the FE simulation are used for training the developed thermal model based on the neural network (NN) and for the creation of a dynamic reduced order model (ROM) of the roll surface profile. The pre-trained NN model gives accurate results and is faster than the FE model, but the model is not very useful for fast calculations in a real-time control system, mainly because the temperature distribution inside the rolls is not explicitly used in further calculations. In contrast, the ROM is fast and accurate and provides surface-shaped results that can be immediately used by other models of the real-time control system. The results of the simulation of the real process are also shown. Calculations of the roll campaign (more than 9 h) by the FEM model last several hours, while by the ROM less than 20 s. Full article

The generation of digital aerial photogrammetry products using unmanned aerial vehicle-digital aerial photogrammetry (UAV-DAP) has become an essential task due to the increasing use of UAVs in the world of geomatics, thanks to their low cost and spatial resolution. Therefore, it is relevant to explore the performance of new digital cameras equipped in UAVs using electronic rolling shutters instead of ideal mechanical or global shutter cameras to achieve accurate and reliable photogrammetric products, if possible, while minimizing workload, especially for their application in projects that require a high level of detail. In this paper, we analyse performance using oblique images along the perimeter (3D perimeter) on a flat area, i.e., with slopes of less than 3%. The area was photogrammetrically surveyed with a DJI (Dà-Jiāng Innovations) Inspire 2 multirotor UAV equipped with a Zenmuse X5S rolling shutter camera. The photogrammetric survey was accompanied by a Global Navigation Satellite System (GNSS) survey, in which dual frequency receivers were used to determine the ground control points (GCPs) and checkpoints (CPs). The study analysed different scenarios, including the combination of forward and transversal strips and oblique images. After examining the ideal scenario with the least root mean square error (RMSE), six different combinations were analysed to find the best location for the GCPs. The most significant results indicate that the optimal calibration of the camera is obtained in scenarios including oblique images, which outperform the rest of the scenarios for achieving the lowest RMSE (2.5x the GSD in Z and 3.0x the GSD in XYZ) with optimum GCPs layout; with non-ideal GCPs layout, unacceptable errors can be achieved (11.4x the GSD in XYZ), even with ideal block geometry. The UAV-DAP rolling shutter effect can only be minimised in the scenario that uses oblique images and GCPs at the edges of the overlapping zones and the perimeter. Full article

This study analyzes a three-stage roll flattening process to improve the flatness of 1.5 GPa grade AHSS sheets. Unlike conventional leveler rolls, which mainly relieve residual stress through longitudinal tension-compression, the second roll has a sloped pattern to induce transverse deformation and redistribute local residual stresses. A twisted sheet was processed under different roll gap settings (1.3 mm, 1.1 mm, 0.9 mm, and 0.7 mm), and experimental measurements were compared with Abaqus Explicit simulations. At a 1.1 mm gap, the RMSE between experiment and simulation is 0.22 mm, showing the highest agreement. Both twist and crossbow defects are reduced by over 80%, achieving optimal flattening. At 1.3 mm, the simulation overestimates the second roll’s effect, causing excessive localized deformation. Reducing the gap to 0.9 mm or 0.7 mm increases discrepancies due to roll fixation differences. Experiments allow more central bending, amplifying crossbow, while simulations assume rigid rolls, underestimating curvature. Adjusting the second roll’s geometry to enhance transverse tension-compression and setting the gap to 1.1 mm effectively reduces defects. This method improves flatness while minimizing the number of rolls needed in high-strength steel sheet production. Full article

Modeling hot rolling remains a major challenge in computational solid mechanics. It demands the simultaneous consideration of geometric and material responses. Although the finite element method (FEM) is widely used, multi-pass simulations often treat each pass independently, leading to error accumulation, particularly in flat product rolling, where inter-pass interactions are crucial. Advanced models and remeshing techniques have been developed to address these issues, but substantial computational resources are required. In this study, a previously validated and simplified 3D FEM model was employed to simulate the initial stages of the hot rolling of large-scale AISI 430 ferritic stainless-steel slabs, using data from an industrial rolling schedule. Specifically, the simulations encompassed preheating and descaling, and seven passes of the roughing stage. Through these simulations, a transfer bar with an approximate length of 16,100 mm was obtained. The simulated thickness and rolling load values were compared with experimental data, demonstrating good agreement in most passes. Subsequently, the temperature, effective plastic strain, and equivalent stress distributions along the rolled material were extracted and analyzed. The results highlighted that the employed model adequately predicted the variations in the analyzed parameters throughout the volume of the rolled material during the different stages of the process. However, discrepancies were identified in the rolling load values during the final passes, which were attributed to the presence of phenomena not considered in the constitutive model used. This model will be refined in future studies to reduce the error in the rolling load estimation. Full article

Industrial process heat typically requires large amounts of fossil fuels. Solar energy, while abundant and free, has low energy density, and so large collector areas are needed to meet thermal needs. Land costs in developed areas are often prohibitively high, making rooftop-based concentrating solar power (CSP) attractive. However, limited rooftop space and the low energy density of solar power are usually insufficient to meet a facility’s demands. Maximizing annual CSP energy generation within a bounded rooftop space is necessary to mitigate fossil fuel consumption. This is a different optimization objective than minimizing the Levelized Cost of Energy (LCOE) in typical open-land, utility-scale heliostat layout optimization. Innovative designs are necessary, such as compact, energy-dense central receiver systems with non-flat heliostat field topographies that use spatially efficient Tilt–Roll heliostats or multi-rooftop and multi-height distributed urban systems. A novel ray-tracing simulation tool was developed to evaluate these unique scenarios. For compact systems, optimized annual energy production occurred with maximum heliostat spatial density, and the best non-flat heliostat field topography found is a shallow section of a parabolic cylinder with an East–West focal axis, yielding a 10% optical energy improvement. Tightly packed Tilt–Roll heliostats showed a double improvement in optical energy at the receiver compared to Azimuth–Elevation heliostats. Full article

A growing need to reduce the environmental impact and cost of manufacturing stainless steels has led to the development of ferritic stainless steel as an alternative to austenitic and duplex steels. The development of new stainless steels involves the optimization of their hot rolling processes, with the aim of minimizing the occurrence of defects and improving productivity. In this context, numerical simulation using the finite element method (FEM) is presented as a key tool to reduce the time and cost associated with traditional trial-and-error optimization methods. Previous work oriented towards the simulation of stainless steels has been focused on the study of small samples, on the performance of laboratory-scale tests, and on the use of 2D FEM models. In this study, a three-dimensional FEM model is proposed to simulate the hot rolling process of large-scale AISI 430 ferritic stainless-steel slabs using an industrial rolling schedule employed in the actual manufacturing process of flat products. Model optimization is performed in order to reduce the computational cost of the simulations, based on the simulation of the first pass of the hot rolling process of AISI 430 stainless steel. The results show that model optimization reduces the computational time by 90.2% without compromising the accuracy of the results. Thus, it was found that the results for thickness and rolling load showed a good correlation with the experimental values. In addition, the simulations performed allowed for the analysis of the distribution of temperature and effective plastic strain. Full article

Owing to its enhanced production efficiency, roller hemming has become the mainstream process for forming and joining metal sheets in the automotive industry. This study investigates the roller hemming process of a specific car door panel through a combination of experimental analysis and finite element analysis (FEA) on both straight-edge and curved-edge flat surfaces. Consequently, the mechanical properties of the door panel, including tensile strength, yield strength, modulus of elasticity, and Poisson’s ratio, were estimated through tensile testing and then underwent finite element modeling. The simulation results demonstrated the varying distribution of stress during the rolling hemming process, with the highest stress concentration observed in the bending area. Additionally, creepage and growing results were acquired from both simulation and experimental data to validate the precision of the numerical model. A comparison was made between the experimental and simulation results of the external forces exerted by the roller on the panel. In both straight- and curved-edge sections, the external force during final hemming exceeded that during pre-hemming, as revealed by experimental measurements of both normal and tangential external forces, surpassing their corresponding simulated values. Full article

The finishing mill is a critical link in the hot rolling process, influencing the final product’s quality, and even economic efficiency. The distribution box of the finishing mill plays a vital role in power transmission and distribution. However, harsh operating conditions can frequently lead to distribution box damage and even failure. To diagnose faults in the distribution box promptly, a fault diagnosis network model is constructed in this paper. This model combines depthwise separable convolution and Bi-LSTM. Depthwise separable convolution and Bi-LSTM can extract both spatial and temporal features from signals. This structure enables comprehensive feature extraction and fully utilizes signal information. To verify the diagnostic capability of the model, five types of data are collected and used: the pitting of tooth flank, flat-headed sleeve tooth crack, gear surface crack, gear tooth surface spalling, and normal conditions. The model achieves an accuracy of 97.46% and incorporates a lightweight design, which enhances computational efficiency. Furthermore, the model maintains approximately 90% accuracy under three noise conditions. Based on these results, the proposed model can effectively diagnose faults in the distribution box, and reduce downtime in engineering. Full article

Flat-rolled steel sheets are one of the major products of the metal industry. Strip steel’s production quality is crucial for the economic and safety aspects of humanity. Addressing the challenges of identifying the surface defects of strip steel in real production environments and low detection efficiency, this study presents an approach for strip defect detection based on YOLOv5s, termed SDD-YOLO. Initially, this study designs the Convolution-GhostNet Hybrid module (CGH) and Multi-Convolution Feature Fusion block (MCFF), effectively reducing computational complexity and enhancing feature extraction efficiency. Subsequently, CARAFE is employed to replace bilinear interpolation upsampling to improve image feature utilization; finally, the Bidirectional Feature Pyramid Network (BiFPN) is introduced to enhance the model’s adaptability to targets of different scales. Experimental results demonstrate that, compared to the baseline YOLOv5s, this method achieves a 6.3% increase in mAP₅₀, reaching 76.1% on the Northeastern University Surface Defect Database for Detection (NEU-DET), with parameters and FLOPs of only 3.4MB and 6.4G, respectively, and FPS reaching 121, effectively identifying six types of defects such as Crazing and Inclusion. Furthermore, under the conditions of strong exposure, insufficient brightness, and the addition of Gaussian noise, the model’s mAP₅₀ still exceeds 70%, demonstrating the model’s strong robustness. In conclusion, the proposed SDD-YOLO in this study features high accuracy, efficiency, and lightweight characteristics, making it applicable in actual production to enhance strip steel production quality and efficiency. Full article

Ring Rolling is a near-net manufacturing process with some measurable dimensional inaccuracies in its products. This fact is exaggerated even more under the scope of high-precision manufacturing, where these imprecisions render such products unfitting for the strict dimensional requirements of high-precision applications (e.g., bearings, casings for turbojets, etc.). In order to remedy some of the dimensional inaccuracies of Ring Rolling, the novel approach of Reverse Ring Rolling is proposed and investigated in the current analysis. The conducted research was based on a numerical simulation of a flat Ring Rolling process, previously presented by the authors. Since the final dimensions of the ring from the authors’ previous work diverged from those initially expected, the simulation of a subsequent Reverse Ring Rolling process was performed to reach the target dimensions. The calculated deformational results revealed a great agreement in at least two of the three crucial dimensions. Additionally, the evaluation of the calculated stress, strain, temperature and load results revealed key aspects of the mechanisms that occur during the proposed process. Overall, it was concluded that Reverse Ring Rolling can effectively function as a corrective process, which can increase the dimensional accuracy of a seamless ring product with little additional post-processing and cost. Full article

In this study, the effect of niobium addition and a specific preheating process on the microstructure and tensile properties of 52CrMoV4 steel used in leaf springs was investigated. Flat and leaf spring materials were used to accomplish this aim. The flat materials under investigation were kept in a furnace for 90 min at 900 °C. A homogeneous microstructure was aimed for with the use of this pre-annealing heat treatment in addition to the standard process before rolling used to create NbC. Leaf spring production was carried out with flat materials that possessed various Nb contents, with or without pre-heating. Grain size measurement and tensile tests were performed on the flat and leaf springs. Additionally, scanning electron microscopy images were captured from the fractured surfaces after the tensile tests were carried out. The current study highlights the importance of Nb addition as an alloying element and the effect of the selected pre-annealing process in optimizing the grain structure and enhancing the tensile properties of leaf springs. The leaf spring with a Nb ratio of 0.0376 that was pre-annealed exhibited a finer grain structure (G = 11.3), greater tensile properties (YS = 1550 N/mm² and UTS = 1688.6 N/mm²), and deeper tear valleys and larger dimples, indicating higher energy consumption during fracturing, according to the SEM images produced, in contrast with the other materials studied. Full article

Focusing on the problem of strip shape quality control in the finishing process of hot rolling, a shape model based on metal flow and stress release with the application of varying contact rolling parameters is introduced. Combined with digital twin technology, the digital twin framework of the shape model is proposed, which realizes the deep integration between physical time–space and virtual time–space. With the utilization of the historical data, the parameters are optimized iteratively to complete the digital twin of the shape model. According to the schedule, the raw material information is taken as the input to obtain the simulation of the strip shape, which shows a variety of export shape conditions. The prediction absolute error of the crown and flatness are less than 5 μm and 5 I-unit, respectively. The results prove that the proposed shape simulation model with strong prediction performance can be effectively applied to hot rolling production. In addition, the proposed model provides operators with a reference for the parameter settings for actual production and promotes the intelligent application of a shape control strategy. Full article