Search Results (146)

Magnesium-based alloys remain poorly researched, particularly regarding their behavior and resistance under hydrodynamic loading conditions. Interest in these materials is driven by their low density, lower even than that of aluminum alloys, and their excellent pressure die-casting capability, leading to manufacturing components with high geometric accuracy and structural homogeneity. Due to their biodegradability and biocompatibility, recent research has focused on using them in reconstructive surgery devices, similar to Zn-Mg alloys. As the blood circulatory system can, at certain stages, be considered similar to a hydraulic system, it is subjected to hydrodynamic flow regimes, including cavitation erosion. In this context, the current research, conducted on the AM50 magnesium-based alloy, provides new insights into its behavior and structural resistance exposed to shock waves and microjets generated by cavitation. Cavitation tests were performed using a standard 20 kHz vibratory device on three material conditions: one semi-finished (initial) state and two aged, heat-treated states at 200 °C for 12 and 24 h. Analyses of the characteristic erosion curves, cavitation resistance parameters, and macro- and microstructural examinations of the eroded surfaces revealed that, compared with the semi-finished condition, the applied heat-treatment regimes increased the HV₅ hardness by 6.8–17% and the cavitation resistance by 27–61%. Full article

Driven by the increasing demand for material efficiency and reduced environmental impact in automotive foundry production, this study addresses the industrial problem of determining the allowable content of internal return material in high-pressure die casting of EN AC-47100 aluminum alloy while maintaining the required quality of automotive castings. The aim was to determine how return material content and selected process parameters affect ultimate tensile strength, Brinell hardness, and internal porosity. In the regression model with interaction terms, high explanatory ability was achieved for ultimate tensile strength and internal porosity, with R² values of 0.920 and 0.744, respectively. A full factorial experiment was performed using five levels of return material content, five levels of plunger velocity, and three levels of intensification pressure, resulting in 75 experimental settings. The data were analyzed using ANOVA, regression models with interaction terms, response surface methodology, and constrained multi-criteria optimization. Return material content was identified as the dominant factor affecting tensile strength and porosity. Increasing its proportion caused a systematic decrease in strength and an increase in internal porosity. Plunger velocity acted as a modifying factor, partially reducing porosity and improving strength response. The optimization showed that the maximum usable return material content was mainly limited by internal porosity. Under the most permissive scenario, a return material content of approximately 33.5% was achievable. The proposed scenario-based approach supports the selection of acceptable process settings that balance casting quality with return material utilization and provides a practical basis for increasing material circularity in industrial HPDC production without exceeding defined quality limits. Full article

Grain refinement is a crucial technological strategy for achieving microstructural homogenization and enhancing the mechanical performance of aluminum alloys. This study examines the synergistic effects of trace additions of NbB₂ and Ti on microstructural refinement and the enhancement of mechanical properties in high-pressure die-cast (HPDC) Al-Si series alloys. Through systematic investigations utilizing scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM) analyses, the mechanisms by which trace additions of NbB₂ and Ti contribute to the synergistic refinement and strengthening of mechanical properties in HPDC Al-Si alloys are elucidated. The incorporation of NbB₂ effectively refines both the externally solidified crystals (ESCs) and secondary α-Al_II grains. The combined addition of NbB₂ and Ti further amplifies this effect, resulting in optimal refinement outcomes in the Al-Si series alloy, characterized by an ESC grain size of 19.1 μm and an area fraction of 27.5%, as well as an α-Al_II grain size of 6 μm. TEM observations reveal the formation of a Ti-rich transition layer between NbB₂ and Al with the synergistic addition of Ti and NbB₂, which fills interface nucleation vacancies and enhances refinement performance. Full article

High-pressure casting technology is continuously evolving to achieve improved product quality. In the casting process using ADC12 alloy, defects such as porosity, shrinkage, cold shut, and others are frequently observed and may arise due to the complex interplay of heat and mass transfer, thermodynamic principles, and fluid flow rates. These types of defects can be predicted through computational simulation. By analyzing the simulation results of a given component, engineers can utilize them as a reference for establishing machine parameters. This approach enables the early identification of potential defects, allowing for the optimization of the relevant parameters. The integration of casting machines with process simulation thus serves as a complementary strategy for producing high-quality castings that meet customer requirements. Full article

To address the surface wear issues of tungsten alloys in die-casting mold applications—where low hardness coupled with severe service conditions involving high-pressure impact from molten metal, thermal cycling, and component counter-friction—this study employed three techniques: laser cladding, plasma spraying, and vacuum surface carburization. Three distinct strengthening coatings were prepared on a tungsten heavy alloy (WHA) substrate. X-ray diffraction (XRD), scanning electron microscopy (SEM), a Vickers hardness tester, and block-on-ring friction and wear tests were employed to characterize the phase composition, microstructure, hardness, and wear resistance of the coatings. The results indicate that all three coatings significantly enhanced the hardness of the substrate, albeit through different strengthening mechanisms. The hardness increase in the laser-clad coating is attributed to the combined strengthening effect of rapid solidification-induced fine grains and dispersed WC particles. The enhanced hardness of the plasma-sprayed coating is due to the intrinsic hardness of WC and its dense layered structure. The carburized layer exhibits the highest hardness, resulting from the continuous WC phase formed via in situ reaction and an interface-free gradient transition with the substrate, which eliminates interfacial weak zones. Under loads of 50 N and 100 N, the plasma-sprayed coating demonstrated the best wear resistance, with wear volumes of 0.16% and 0.18% of that of the substrate, and wear depths of 4.57% and 3.50% of that of the substrate, respectively. It also exhibited the optimal load adaptability, making it a preferred solution for surface strengthening of tungsten alloy die-casting molds. Full article

This work proposes a data-driven design framework for high-pressure die-cast (HPDC) aluminum alloys that integrates robust data refinement, machine learning (ML) modeling, explainability, and inverse design. A total of 1237 tensile-test records from T5-aged HPDC alloys were aggregated into a curated dataset of 382 unique composition–heat-treatment combinations. Four regression models—Ridge regression, Random Forest (RF), XGBoost (XGB), and a multilayer perceptron (MLP)—were trained to predict yield strength (YS), ultimate tensile strength (UTS), and elongation (EL). Tree-based ensemble models (XGB and RF) achieved the highest accuracy and stability, capturing nonlinear interactions inherent to industrial HPDC data. In particular, the XGB model exhibited the best predictive performance, achieving test R² values of 0.819 for UTS and 0.936 for EL, with corresponding RMSE values of 15.23 MPa and 1.112%, respectively. Feature-importance and SHapley Additive exPlanations (SHAP) analyses identified Mn, Si, Mg, Zn, and T5 aging temperature as the most influential variables, consistent with metallurgical considerations such as microstructural stabilization and precipitation strengthening. Finally, RF-based inverse design suggested new composition–process candidates satisfying UTS > 300 MPa and EL > 8%, a region scarcely represented in the experimental dataset. These results illustrate how interpretable ML can expand the feasible design space of HPDC aluminum alloys and support composition–process optimization in industrial applications. Full article

Recent global efforts to produce lightweight electrified vehicles have motivated the push toward advanced lightweight materials which led to the creation of novel alloys optimized for use in high-pressure die casting (HPDC). HPDC enables the fabrication of near-net-shape automotive parts, significantly reducing or eliminating additional machining steps. A key feature of HPDC is the extremely fast cooling that forces the alloy to solidify within only a few seconds. Because of these rapid cooling conditions, it becomes essential to accurately evaluate the thermophysical behavior of newly designed lightweight alloys during severe quenching. Precisely quantifying these material properties is crucial for properly controlling HPDC operations and for building reliable numerical models that simulate filling and solidification. The thermophysical characteristics of such alloys vary markedly with temperature, especially when the material undergoes the fast solidification typical of HPDC. Therefore, understanding how these properties change with temperature during intense cooling becomes a critical requirement in alloy development. To address this need, a dedicated experimental system was designed to solidify molten metal samples under controlled and variable cooling conditions by applying multiple impinging water jets. An inverse heat-transfer algorithm was formulated to extract temperature-dependent thermal conductivity and diffusivity of the alloy as it solidifies under rapid cooling. To verify the reliability of both the inverse model and the measurements, experiments were performed using pure Tin, a reference material with well-documented thermophysical properties. The computed thermophysical properties of Tin were benchmarked against values reported in the literature and demonstrated reasonable consistency, with a maximum deviation of 13.6%. Full article

This study investigates the melt-flow behavior of the AlSi₉Cu₃ alloy during high-pressure die casting using a combined experimental and numerical approach. A transparent die and a high-speed camera were used to capture the transient motion of the melt front, while a validated computational model reproduced the filling dynamics under identical boundary conditions. The influence of the gating-system geometry—particularly the gate thickness, flow-path length, and inlet cross-section—was analyzed with respect to filling velocity, filling time, and flow stability. To quantify hydraulic losses that arise in practical die-casting conditions, an empirical correction coefficient k₂ was introduced. Its value was obtained by regression analysis based on ten repeated measurements of filling time for each configuration. The deviation between the simulated and experimental velocities did not exceed 5%, demonstrating the reliability of the numerical model within the tested parameter range. The results show that the optimized gating design reduces flow instability, suppresses air entrapment zones, and yields a more uniform velocity distribution across the cavity. The empirical relations derived involving k₂ provide a practical tool for preliminary design of gating systems, enabling faster optimization without extensive trial-and-error procedures. The methodology presented in this work offers a validated basis for improving gating-system performance in high-pressure die casting of aluminum alloys. Full article

Large functionally integrated casting and electrification are rapidly changing the high-pressure die-casting industry. The requirements for these new castings differ from those of the previous ones. Load-bearing capability, fatigue, ductility, and crashworthiness all increase, and the foundry’s readiness for this varies and is challenging. At the same time, the carbon footprint needs to be reduced, meaning that recycled, secondary aluminium usage is required, making the challenge of attaining the required component performance significantly more difficult. The current paper examined the conditions and requirements to manage and reach the required targets, both from a material standpoint as well as from a climate impact and resource-efficiency perspective. Full article

Acquiring reliable thermal data during the high-pressure die-casting (HPDC) process remains a significant challenge due to its complexity and rapidly evolving thermal environment. In industrial settings, the influence of process parameters is typically evaluated after solidification by examining the final casting quality, as direct temperature measurements within the die during operation are difficult to obtain. Additionally, most casting simulation tools lack accurate correlations for the interfacial heat transfer coefficient (IHTC) as a function of process parameters. To address this limitation, a laboratory-scale hot chamber die-casting (HCDC) apparatus was developed to replicate the fluid flow and the thermal conditions of industrial HPDC operation while enabling direct thermal measurements inside the die cavity using embedded thermocouples. The molten metal temperature was estimated using the lumped capacitance method, and the IHTC was determined through a custom inverse heat conduction algorithm incorporating an adaptive forward time-stepping scheme. This algorithm was validated by solving the forward heat conduction problem using the ANSYS 2025 R1 Transient Thermal solver. The experimentally obtained IHTC values showed good agreement with those measured during industrial HPDC trials, with a maximum deviation of about 14% in the peak value, while the full width at half maximum (FWHM) differed by less than 12%. These results confirm that the developed HCDC setup can reliably reproduce industrial thermal conditions and generate high-quality thermal data that can be used in numerical casting simulations. Full article

The significant increase in the importance of silumin recycling in the context of sustainable development is driven by tangible ecological and economic benefits. However, the primary technological challenge associated with using scrap is the accumulation of iron, which promotes the formation of undesirable sludge particles, degrading the alloy’s mechanical properties. This paper presents a description of the phase transformations in an AlSi7Mg alloy with increased iron and manganese content. Analysis of data from Differential Scanning Calorimetry (DSC) revealed the primary crystallisation of sludge particles (SP) and the pre-eutectic precipitation of the α-Al₁₅(Fe,Mn)₃Si₂ phase, which replaced the β-Al₅FeSi phase. The remaining constituents of the AlSi7Mg alloy structure—α(Al) solid solution dendrites, the α(Al)+β(Si) eutectic, and the Mg₂Si phase—crystallise regardless of the iron, manganese, and chromium content. It was established that the increase in the crystallisation temperature of SP, rich mainly in the elements mentioned above, is directly proportional to the increase in the value of the sludge factor (SF) and ranges from 620 °C (for SF~1.3%) to approx. 645 °C (for SF~3.1%). SEM studies revealed that the combined increase in iron and manganese content not only raises the precipitation temperature of SP but also alters its morphology from single polyhedra to compact, “cluster-like” structures. To avoid the presence of sludge particles in the AlSi7Mg alloy, which have an unfavourable morphology and reduce the yield of the melting process, the SF for high-pressure die-casting should not exceed 2.0%. Full article

RT-DETR (Real-Time DEtection TRansformer) has recently emerged as a promising model for object detection in images, yet its performance on small objects remains limited, particularly in terms of robustness. While various approaches have been explored, developing effective solutions for reliable small object detection remains a significant challenge. This paper introduces an adapted variant of RT-DETR, specifically designed to enhance robustness in small object detection. The model was first designed on one dataset and subsequently transferred to others to validate generalization. Key contributions include replacing components of the feed-forward neural network (FFNN) within a hybrid encoder with Hebbian, randomized, and Oja-inspired layers; introducing a modified loss function; and applying multi-scale feature fusion with fuzzy attention to refine encoder representations. The proposed model is evaluated on the Al-Cast Detection X-ray dataset, which contains small components from high-pressure die-casting machines, and the PCB quality inspection dataset, which features tiny hole anomalies. The results show that the optimized model achieves an mAP of 0.513 for small objects—an improvement from the 0.389 of the baseline RT-DETR model on the Al-Cast dataset—confirming its effectiveness. In addition, this paper contributes a mini-literature review of recent RT-DETR enhancements, situating our work within current research trends and providing context for future development. Full article

The adhesive bonding of high-pressure die-cast (HPDC) aluminum alloy AlSi10MnMg is extensively applied in the aerospace and automotive sectors. Surface pretreatment of HPDC aluminum prior to bonding is crucial for enhancing bonding strength and durability, as it regulates surface roughness, and chemical properties. Traditional multi-step surface treatments including chromic acid anodizing for HPDC AlSi10MnMg are hazardous, complex, and often fail to balance adhesive bonding durability and corrosion protection, limiting their industrial applicability. This study examined the impact of various chemical treatments on the adhesive bonding performance of an AlSi10MnMg aluminum alloy. The treated surfaces were bonded using a structural adhesive, and bonding performance was evaluated via wedge tests under pristine conditions and after accelerated aging. A scanning electron microscope (SEM) was used to study the surface morphology, chemical composition, and corrosion characteristics of the treated surfaces. Energy dispersive spectroscopy (EDS), electrochemical impedance spectroscopy (EIS), and potentiodynamic polarization measurements were employed. Excellent adhesion characteristics, dominated by the cohesive failure of the adhesive, were observed in H₂O₂-treated samples. The H₂O₂-treated samples exhibited the shortest initial crack length, indicating a superior baseline bonding quality, and showed minimal crack propagation (only slight extension) after aging under extreme environmental conditions (70 °C and 100% relative humidity for 4 weeks). Electrochemical measurements revealed that the SG200-treated sample achieved the lowest corrosion current density (0.25 ± 0.03 μA/cm²) with an excellent corrosion resistance, while sol–gel-treated samples generally suffered from a poor adhesion, with interfacial failure. This study proposes a simplified, single-step chemical treatment using an H₂O₂ solution that effectively achieves both a strong adhesive bonding and an excellent corrosion resistance, without the drawbacks of conventional methods. It offers a viable alternative to conventional multi-step hazardous surface treatments. Full article

The increasing adoption of High-Pressure Die Casting (HPDC) technology in the production of automotive body structure components is driven by its potential for efficiency and performance. This technology, however, involves complex physical phenomena with numerous parameters that significantly influence casting quality. In this study, three key die casting parameters—plunger or shot speed, vacuum application, and intensification pressure (IP)—have been evaluated following a Design of Experiment (DoE) approach. The results demonstrate that IP application is instrumental in reducing porosity within the cast specimens, thereby enhancing their mechanical strength and elongation. Furthermore, the combined application of vacuum and IP yields further improvements in elongation by minimizing porosity. These findings are particularly relevant for silicon-free alloys, which eliminate the need for post-casting heat treatments to achieve the required mechanical properties. By optimizing HPDC processes, manufacturers can reduce rejection rates, lower production costs, and improve the overall efficiency of their operations, contributing to the production of high-quality and cost-effective components for the automotive industry. Full article