Search Results (147)

We report a scalable route to hybrid aluminum matrix composites (AMCs) based on Al6060 (as-fabricated condition) reinforced with 2 wt.% TiB₂ and 1 wt.% microsilica, fabricated by ultrasonically assisted stir casting (UASC) followed by radial-shear rolling (RSR). Premixing and preheating of powders combined with acoustic cavitation/streaming during UASC ensured uniform, non-sedimentary particle dispersion and low-defect cast billets. X-ray diffraction of the as-cast composite shows fcc-Al with weak TiB₂ reflections and no reaction products; microsilica remains amorphous. Electron microscopy and EBSD after RSR reveal full erasure of cast dendrites, fine equiaxed grains, weakened texture, and a high fraction of high-angle boundaries due to the concurrent action of particle-stimulated nucleation (micron-scale TiB₂) and Zener pinning/Orowan strengthening (50–350 nm microsilica). Mechanical testing shows that, in the cast state—comparing cast monolithic Al6060 to the cast hybrid-reinforced composite—yield strength (YS) increases from 61.7 to 77.2 MPa and ultimate tensile strength (UTS) from 103.4 to 130.7 MPa, without loss of ductility. After RSR to Ø16 mm (cumulated true strain ≈ 0.893), the hybrid attains YS 101.2 MPa, UTS 150.6 MPa, and elongation ≈ 22.0%, i.e., comparable strength to rolled Al6060 (UTS 145.1 MPa) while restoring/raising ductility by ~9.7 percentage points. Microhardness follows the same trend, increasing from 50.2 HV0.2 to 73.1 HV0.2 when comparing the base cast condition with the rolled hybrid. The route from UASC to RSR thus achieves a favorable mechanical strength–ductility balance using an economical, eco-friendly oxide/boride hybrid reinforcement, making it attractive for formable AMC bar and rod products. Full article

This study addresses the challenge of simultaneously improving the electrical conductivity and strength of aluminum alloys. We innovatively combine powder metallurgy with melt stirring casting to fabricate graphite flake-added aluminum matrix composites through secondary remelting, electromagnetic stirring, and extruding. The influence of graphite flake content gradient (0–3.0 wt.%) on the mechanical properties and electrical conductivity was systematically investigated. Our results demonstrate that the composite with 0.2 wt.% graphite flakes (sample GM02) exhibits optimal comprehensive performance: tensile strength reaches 100.9 MPa (a 124% increase over pure Al), and electrical conductivity reaches 67.1% IACS (a 9.6% increase). Microstructural analysis reveals that low-content graphite flakes effectively suppressed electron scattering by forming semi-coherent interfaces. However, when graphite flake content exceeds 0.5 wt.%, a significant decrease in conductivity and plasticity (elongation below 10%) occurs due to increased Al₄C₃ phase formation, enhanced grain boundary scattering caused by grain refinement, and porosity defects induced by graphite flake agglomeration. This study provides a novel approach for the industrial production of high-performance, lightweight conductive components. Full article

The existing continuous caster layout curves cause plastic deformation of slabs during bending and straightening segments, while no effective deformation occurs in the basic arc segment, which tends to induce defects, such as cracks, and compromise slab quality. High-temperature creep deformation is generally regarded as detrimental to material performance. If the significant and inevitable creep deformation of a slab could be utilized to accomplish bending and straightening deformation during continuous casting, it would turn a potential harm into an advantage, ultimately enhancing both production efficiency and final product quality. Therefore, a new continuous bending and straightening curve based on the high-temperature creep property of a low-alloy steel slab was designed. The new curve cancelled the original basic arc segment and smoothly connected the bending and straightening segments, which not only substantially prolonged the effective bending and straightening deformation time but also extended the creep time. The locations within the slab corresponding to the temperature range of 1100 °C to 1200 °C were obtained from the simulated temperature field results. Comparing the calculated strain rates with the steady-state creep rates revealed that within the temperature range exhibiting favorable hot ductility, the bending and straightening deformation of the slab could be accomplished entirely through creep deformation. Full article

A damping spacer rod is a key protective device in ultrahigh voltage transmission lines, which not only keeps the distance of split wires and limits the whipping and collision caused by the relative motion between sub-wires, but also inhibits the vibration of wires. This study aims to solve the problem of typical faults, such as loose wire clamps, that are prone to occur in damping isolation rods during long-term operation in ultra-high voltage transmission lines. Taking the spacer rod FGZ-450/34B as the object, a new high-pressure casting process for spacer rod frames is explored. The spacer rods were simulated by using the ABAQUS finite element software to predict the stress distribution and identify the dangerous sections. Based on this, the mold process was optimized to avoid die-casting defects. Meanwhile, mechanical property tests were carried out on the products produced by the two types of molds. The research finds that by optimizing the mold process, the die-casting quality of the dangerous section of the spacer rod can be effectively improved, and the best high-pressure die-casting scheme has been obtained through comparison. This research achievement provides technical support for enhancing the anti-vibration performance, anti-loosening reliability, short-circuit current thermal shock resistance, and anti-ultraviolet aging performance of damping isolation rods. It is of great significance for ensuring the stable operation of ultra-high voltage transmission lines and improving the production process level of damping isolation rods. Full article

As the demand for lightweight and high-performance conductive materials grows in power transmission systems, aluminum alloy rods have emerged as a cost-effective and scalable alternative to copper conductors. This review systematically examines the development status and technological progress in the purification and casting–rolling processes used in the production of Electrical Round Aluminum Rods (ERARs). It explores current challenges in improving electrical conductivity and mechanical strength while addressing issues such as hydrogen and oxide inclusion removal, grain refinement, and impurity segregation. Key purification techniques—including flux refining, gas treatment, filtration, and rotary injection—are compared in terms of performance, cost, and environmental impact. The paper also analyzes different casting–rolling methods, including continuous casting and rolling, twin-roll casting, and extrusion processes, with attention to process optimization and equipment design. Furthermore, emerging applications of artificial intelligence (AI) in predictive modeling, defect detection, and process parameter optimization are highlighted, offering a novel perspective on intelligent and sustainable ERAR production. This paper aims to provide insights for facilitating the industrial-scale production and performance enhancement of ERAR materials. Full article

In the casting and rolling production process, surface longitudinal cracks are a typical casting defect. Tracing the causes of longitudinal cracks online and controlling the key parameters leading to their formation in a timely manner can enhance the stability of casting and rolling production. To this end, the influencing factors of longitudinal cracks were analyzed, a data integration storage platform was constructed, and a tracing model was established using empirical rule analysis, statistical analysis, and intelligent analysis methods. During the initial production phase of a casting machine, longitudinal cracks occurred frequently. The tracing results using the LightGBM-SHAP method showed that the relative influence of the narrow left wide inner heat flow ratio of the mold was significant, followed by the heat flow difference on the wide symmetrical face of the mold and the superheat of the molten steel, with weights of 0.135, 0.066, and 0.048, respectively. Based on the tracing results, we implemented online emergency measures. By controlling the cooling intensity of the mold, we effectively reduced the recurrence rate of longitudinal cracks. Root cause analysis revealed that the total hardness of the mold-cooling water exceeded the standard, reaching 24 mg/L, which caused scaling on the mold copper plates and uneven cooling, leading to the frequent occurrence of longitudinal cracks. After strictly controlling the water quality, the issue of longitudinal cracks was brought under control. The online application of the tracing method for the causes of longitudinal cracks has effectively improved efficiency in resolving longitudinal crack problems. Full article

Internal crack defects in high-strength low-alloy (HSLA) steels during continuous casting pose significant challenges to downstream processing and product reliability. However, due to the inherent class imbalance in industrial defect datasets, conventional machine learning models often suffer from poor sensitivity to minority class instances. This study proposes a predictive framework that integrates conditional tabular generative adversarial network (CTGAN) for synthetic minority sample generation and CatBoost for classification. A dataset of 733 process records was collected from a continuous caster, and 25 informative features were selected using mutual information. CTGAN was employed to augment the minority class (crack) samples, achieving a balanced training set. Feature distribution analysis and principal component visualization indicated that the synthetic data effectively preserved the statistical structure of the original minority class. Compared with the other machine learning methods, including KNN, SVM, and MLP, CatBoost achieved the highest metrics, with an accuracy of 0.9239, precision of 0.9041, recall of 0.9018, and F1-score of 0.9022. Results show that CTGAN-based augmentation improves classification performance across all models. These findings highlight the effectiveness of GAN-based augmentation for imbalanced industrial data and validate the CTGAN–CatBoost model as a robust solution for online defect prediction in steel manufacturing. 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

High-titanium steel contains an elevated titanium content, which promotes the formation of abundant non-metallic inclusions in molten steel at high temperatures, including titanium oxides, sulfides, and nitrides. These inclusions adversely affect continuous casting operations and generate substantial internal/surface defects in cast slabs, ultimately compromising product performance and service reliability. Therefore, stringent control over the size, distribution, and population density of inclusions is imperative during the smelting of high-titanium steel to minimize their detrimental effects. In this paper, samples of high titanium steel (0.4% Ti, 0.004% N) casting billets were analyzed by industrial test sampling and full section comparative analysis of the samples at the center and quarter position. Using the Particle X inclusions, as well as automatic scanning and analyzing equipment, the number, size, location distribution, type and morphology of inclusions in different positions were systematically and comprehensively investigated. The results revealed that the primary inclusions in the steel consisted of TiN, TiS, TiC and their composite forms. TiN inclusions exhibited a size range of 1–5 µm on the slab surface, while larger particles of 2–10 μm were predominantly observed in the interior regions. Large-sized TiN inclusions (5–10 μm) are particularly detrimental, and this problematic type of inclusion predominantly concentrates in the interior regions of the steel slab. A gradual decrease in TiN inclusion number density was identified from the surface toward the core of the slab. Thermodynamic and kinetic calculations incorporating solute segregation effects demonstrated that TiN precipitates primarily in the liquid phase. The computational results showed excellent agreement with experimental data regarding the relationship between TiN size and solidification rate under different cooling conditions, confirming that increased cooling rates lead to reduced TiN particle sizes. Both enhanced cooling rates and reduced titanium content were found to effectively delay TiN precipitation, thereby suppressing the formation of large-sized TiN inclusions in high-titanium steels. Full article

The formation mechanism of black streak defects in hot-rolled steel sheets was investigated to address the influence of the process parameters on the surface quality during the production of 304 stainless steels. Macro-/microstructural characterization revealed that the defect regions contained necessary mold slag components (Ca, Si, Al, Mg, Na, K) which originated from the initial stage of solidification in the mold region of the continuous casting process, indicating obvious slag entrapment during continuous casting. On this basis, a three-dimensional coupled finite-element model for the molten steel flow–thermal characteristics was established to evaluate the effects of typical casting parameters using the determination of the critical slag entrapment velocity as the criterion. Numerical simulations demonstrated that the maximum surface velocity improved from 0.29 m/s to 0.37 m/s with a casting speed increasing from 1.0 m/min to 1.2 m/min, which intensified the meniscus turbulence. However, the increase in the port angle and the depth of the submerged entry nozzle (SEN) effectively reduced the maximum surface velocity to 0.238 m/s and 0.243 m/s, respectively, with a simultaneous improvement in the slag–steel interface temperature. Through MATLAB (version 2023b)-based reverse optimization combined with critical velocity analysis, the optimal mold slag properties were determined to be 2800 kg/m³ for the density, 4.756 × 10⁻⁶ m²/s for the kinematic viscosity, and 0.01 N/m for the interfacial tension. This systematic approach provides theoretical guidance for process optimization and slag design enhancement in industrial production. Full article

The formation of hot tearing during direct chill casting of aluminum alloys, specifically AA6111, is a significant challenge in the production of ingots for industrial applications. This study investigates the role of hydrostatic pressure and tensile stress in the formation of hot tearing during direct chill casting of rectangular ingots. Combining experimental results and finite element modeling with ABAQUS/CAE 2022, the mechanical behavior of the semi-solid AA6111 alloy was analyzed under different cooling conditions. “Hot” (low water flow) and “Cold” (high water flow) conditions were the two types of cooling conditions that produced cracked and sound ingots, respectively. The outcomes indicate that high tensile stress and localized negative hydrostatic pressure in the hot condition are the main factors promoting the initiation and propagation of cracks in the mushy zone, whereas the improvement of the cooling conditions reduces these defects. Full article

The production of AISI 304 stainless steel (a corrosion-resistant alloy prone to solidification defects from high alloy content) particularly benefits from twin-roll strip casting—a short-process green technology enabling sub-rapid solidification (the maximum cooling rate exceeds 1000 °C/s) control for high-performance steels. However, the internal phenomena within its molten pool remain exceptionally challenging to monitor. This study developed a multiscale numerical model to simulate coupled fluid flow, heat transfer, and solidification in AISI 304 stainless steel twin-roll strip casting. A quarter-symmetry 3D model captured macroscopic transport phenomena, while a slice model resolved mesoscopic solidification structure. Laboratory experiments had verified that the deviation between the predicted temperature field and the measured average value (1384.3 °C) was less than 5%, and the error between the solidification structure simulation and the electron backscatter diffraction (EBSD) data was within 5%. The flow field and flow trajectory showed obvious recirculation zones: the center area was mainly composed of large recirculation zones, and many small recirculation zones appeared at the edges. Parameter studies showed that, compared with the high superheat (110 °C), the low superheat (30 °C) increased the total solid fraction by 63% (from 8.3% to 13.6%) and increased the distance between the kiss point and the bottom of the molten pool by 154% (from 6.2 to 15.8 mm). The location of the kiss point is a key industrial indicator for assessing solidification integrity and the risk of strip fracture. In terms of mesoscopic solidification structure, low superheat promoted the formation of coarse columnar crystals (equiaxed crystals accounted for 8.9%), while high superheat promoted the formation of equiaxed nucleation (26.5%). The model can be used to assist in the setting of process parameters and process optimization for twin-roll strip casting. Full article

A variety of cast product defects may occur in the continuous casting process. By establishing a Continuous Casting Quality Knowledge Graph (C2Q-KG) focusing on the causes of cast product defects, enterprises can systematically sort out and express the relations between various production factors and cast product defects, which makes the reasoning process for the causes of cast product defects more objective and comprehensive. However, reasoning schemes for general KGs often use the same processing method to deal with different types of relations, without considering the difference in the number distribution of the head and tail entities in the relation, leading to a decrease in reasoning accuracy. In order to improve the reasoning accuracy of C2Q-KGs, this paper proposes a model based on a two-branch reasoning network. Our model classifies the continuous casting triples according to the number distribution of the head and tail entities in the relation and connects a two-branch reasoning network consisting of one connection layer and one capsule layer behind the convolutional layer. The connection layer is used to deal with the sparsely distributed entity-side reasoning task in the triple, while the capsule layer is used to deal with the densely distributed entity-side reasoning task in the triple. In addition, the Graph Attention Network (GAT) is introduced to enable our model to better capture the complex information hidden in the neighborhood of each entity and improve the overall reasoning accuracy. The experimental results show that compared with other cutting-edge methods on the continuous casting data set, our model significantly improves performance and infers more accurate root causes of cast product defects, which provides powerful guidance for enterprise production. Full article

Metal injection molding (MIM) is a current technology used to produce products with complex shapes. Despite the accumulated worldwide experience in using this technology, manufacturers sometimes fail to launch new products of proper quality. Often, this is because defects can occur at the casting stage, the prevention of which is impossible through the use of standard design and technological solutions of molds design and the experimental selection of technological modes. This study aimed to analyze the causes of such defects in the green part and optimize the mold design to ensure defect-free casting, which was impossible for the manufacturer using standard solutions. The core method used in this study was simulation modeling of the casting process. A hypotheses were selected, and an analysis of the causes of defect occurrence in casting was conducted. Simulation modeling proved that defect occurrence was due to the formation of a free melt jet and subsequent air capture by this jet. Based on modeling, different gating and feeding system designs were analyzed, which made it possible to choose a variant that provided the uniform filling of gating cavities without forming jet flows and defects. The novelty of this study lies in its optimization of the mold design to prevent free melt jetting and similar defects in other MIM products by modeling feedstock molding processes. The presented results can help enrich the knowledge base of the mold design for MIM and ensure defect-free production. Full article

The intelligent development of continuous casting quality engineering is an essential step for the efficient production of high-quality billets. However, there are many quality defects that require strong expertise for handling. In order to reduce reliance on expert experience and improve the intelligent management level of billet quality knowledge, we focus on constructing a Domain-Specific Knowledge Graph (DSKG) for the quality engineering of continuous casting. To achieve joint extraction of billet quality defects entity and relation, we propose a Self-Attention Partition and Recombination Model (SAPRM). SAPRM divides domain-specific sentences into three parts: entity-related, relation-related, and shared features, which are specifically for Named Entity Recognition (NER) and Relation Extraction (RE) tasks. Furthermore, for issues of entity ambiguity and repetition in triples, we propose a semi-supervised incremental learning method for knowledge alignment, where we leverage adversarial training to enhance the performance of knowledge alignment. In the experiment, in the knowledge extraction part, the NER and RE precision of our model achieved 86.7% and 79.48%, respectively. RE precision improved by 20.83% compared to the baseline with sequence labeling method. Additionally, in the knowledge alignment part, the precision of our model reached 99.29%, representing a 1.42% improvement over baseline methods. Consequently, the proposed model with the partition mechanism can effectively extract domain knowledge, cand the semi-supervised method can take advantage of unlabeled triples. Our method can adapt the domain features and construct a high-quality knowledge graph for the quality engineering of continuous casting, providing an efficient solution for billet defect issues. Full article