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Tracking the microstructural evolution during high-pressure die casting of Al-Si alloys is challenging due to the rapid solidification, varying thermal conditions, and severe turbulence. The process involves a transition from slower cooling in the shot sleeve to rapid cooling in the die cavity, resulting in a bimodal dendritic microstructure and nucleation of new finer dendrite arms on fragmented externally solidified crystals. In this study, a two-dimensional phase-field model was employed to investigate the solidification behaviour of a hypoeutectic Al-7% Si alloy during high-pressure die casting. The model is based on thermodynamic formulations that account for temperature changes due to phase transformation heat, thermal boundary conditions, and solute diffusion in both liquid and solid phases. To replicate the observed bimodal microstructure, solid–liquid interface properties such as thickness, energy, and mobility were systematically varied to reflect the transition from the shot sleeve to the die cavity. The results demonstrated the model's ability to capture the growth of dendrites under shot sleeve conditions and nucleation and development of new dendrite arms under the rapid cooling conditions of the die cavity. [ABSTRACT FROM AUTHOR]

In addition to impurities in recycled aluminum alloys, non-metallic inclusions are a significant factor that deteriorates the material's castability and final mechanical properties. This, therefore, restricts the ability to transition from a primary to secondary aluminum alloy. In this study, the cleanliness of the recycled A357 alloy was evaluated through non-metallic inclusions' characterization, hydrogen content measurement, fluidity test, and casting defects identification. The non-metallic inclusions generated during the recycling process of A357 alloy were collected by the pressurized melt filtration technique. All of the inclusion types collected during filtration were examined and identified by analytical scanning electron microscopy (SEM). Extra additions of up to 2 wt.% swarf in these secondary A357 alloys were designed to simulate highly contaminated alloys. Different to the conventional melt cleaning technologies that mainly focus on complete removal of inclusions, this study developed a novel approach that combines the removal of easily removeable inclusions while preserving well-dispersed inclusions that do not adversely affect the mechanical properties. This study demonstrates that high shear melt conditioning (HSMC) technology can achieve well-dispersed small non-metallic inclusions, low hydrogen content, improved fluidity, and fewer casting defects. As a result, the melt quality of the recycled A357 alloys has achieved a quality comparable to that of primary A357 alloy. [ABSTRACT FROM AUTHOR]

The tectonic evolution of the Paleo‐Jinshajiang Ocean, and in particular the time of its closure, is debated. Here we present new constraints on the evolution of this region from an integrated paleomagnetic and geochronologic study of the Late Triassic Batang Group volcanic rocks in Qamdo, Eastern Qiangtang Terrane (EQT). Two zircon U‐Pb ages indicate that the volcanic rocks erupted at ∼227–222 Ma. New paleomagnetic results yield a robust Late Triassic paleopole of 57.6°N, 176.4°E (A95 = 7.8°), corresponding to a paleolatitude of 32.5 ± 7.8°N for the study area. Integrated with other lines of paleomagnetic and geological evidence, we show that the northward drift of the EQT placed it at the same paleolatitude as the Tarim Block by ∼227–222 Ma, which suggests that the Paleo‐Jinshajiang Ocean in the Qamdo region closed before that time, and likely around ∼230 Ma. Plain Language Summary: The closure of the Paleo‐Jinshajiang Ocean, which was one of the most important ancient oceans of Asia, closed when the Qiangtang Terrane (QT) collided with the terranes now located to the north of it. However, the evolution of this ocean, and especially the timing of its closure, are still debated. The drift history of the QT is a key to understanding the evolution of the Paleo‐Jinshajiang Ocean. We present here new constraints on the evolution of this region from an integrated paleomagnetic and zircon U‐Pb geochronologic study of Late Triassic volcanic rocks in Qamdo, Eastern QT. Two zircon U‐Pb geochronologic results indicate that the volcanic rocks erupted at ∼227–222 Ma. New paleomagnetic results yield a robust Late Triassic paleopole of 57.6°N and 176.4°E, and indicate that the study area was then located at a paleolatitude of 32.5 ± 7.8°N. In integrating these data with other lines of evidence, we show that a northward drift of the EQT since the early Permian brought it to the same paleolatitude as the Tarim Block by ∼227–222 Ma. This implies that the closure of the Paleo‐Jinshajiang Ocean in the Qamdo region occurred before 227–222 Ma, and likely around ∼230 Ma. Key Points: Volcanic rocks of the Late Triassic Batang Group are dated by U‐Pb on zircon to ∼227–222 MaPaleomagnetic data from these rocks yield a robust Late Triassic paleopole of 57.6°N, 176.4°E(A95 = 7.8°)Closure of the Paleo‐Jinshajiang Ocean occurred before 227–222 Ma, and likely around ∼230 Ma [ABSTRACT FROM AUTHOR]

Cutting force modelling for micro machining is of great importance for better understanding of the cutting mechanics in the process. As precision machining of metal matrix composites (MMCs) is much more complex than machining homogeneous materials, the accurate prediction of cutting force is critical to control the cutting performance and tooling life. This paper presents an improved theoretical dynamic cutting force model in MMCs micro milling process by using straight flute PCD end mills. The theoretical model is modified and improved based on the conventional milling force modelling while taking account of various factors including tooling geometries, the material microstructure, size effect and chip formation in the cutting process. An innovative expression on dynamic cutting force in micromachining MMCs is presented through the multiscale modelling and analysis. The cutting force coefficients are further defined through instantaneous cutting force signals analysis. Simulation results under varied cutting process variables are presented against a series of MMCs micro milling trials, which indicate that the improved dynamic cutting force model can predict the cutting force accurately and reveal more details on the cutting force variations in the process due to the material inhomogeneous nature. In addition, the optimal process variables can be readily explored through the dynamic force modelling and simulations so as to further improve the cutting performance. [ABSTRACT FROM AUTHOR]

The effects of cutting dynamics and the particles' size and density cannot be ignored in micro milling of metal matrix composites. This article presents the improved dynamic cutting force modelling for micro milling of metal matrix composites based on the previous analytical model. This comprehensive improved cutting force model, taking the influence of the tool run-out, actual chip thickness and resultant tool tip trajectory into account, is evaluated and validated through well-designed machining trials. A series of side milling experiments using straight flutes polycrystalline diamond end mills are carried out on the metal matrix composite workpiece under various cutting conditions. Subsequently, the measured cutting forces are compensated by a Kalman filter to achieve the accurate cutting forces. These are further compared with the predicted cutting forces to validate the proposed dynamic cutting force model. The experimental results indicate that the predicted and measured cutting forces in micro milling of metal matrix composites are in good agreement. [ABSTRACT FROM AUTHOR]

Metal matrix composites (MMCs) are increasingly applied in various engineering industries because of their distinct physical and mechanical properties. While the precision machining of MMCs is less understood due to their complex microstructure and poor machinability, a comprehensive scientific understanding on their machining mechanics and the associated surface generation mechanisms is of great importance particularly for industrial scale applications of MMCs. This paper presents a simulation and experimental-based holistic investigation on cutting mechanics, material removal and surface roughness in ultraprecision machining of MMCs. B4C/Al2024 is selected as the targeted MMC material in this research. The thermal-mechanical-tribological integrated modelling and analysis are presented to investigate the effects of cutting speed, feed rate and depth of cut (DOC) on the material removal, chip formation mechanics and surface generation process. The simulation results indicate that the machined surface roughness in precision machining of particle reinforced MMCs can be reduced by increasing the cutting speed and decreasing the depth of cut. The surface flow waviness decreases, which contributes to a higher surface quality, while machining with a smaller feed rate. The well-designed machining trials are conducted under the same cutting conditions and process variables as those in simulations, which perform a good agreement with simulation results. [ABSTRACT FROM AUTHOR]

Aimed at the influences of various complicated factors for water inrush from a coal seam floor during coal seam mining, the prediction of the maximal water bursting discharge from a coal seam floor is regarded as a problem of pattern identification with nonlinear, high dimensions, and finite samples. Based on information fusion theory and regarding the prediction of maximal water bursting discharge from a coal seam floor as a process of multisource information fusion and state estimation, an evaluation system of the main controlling factors for predicting the maximal water bursting discharge from a coal seam floor was established. An evaluation model for forecasting the maximal water bursting discharge from a coal seam floor was also structured according to multiple nonlinear regression theory. Considering the major coal mines of Xinwen coalfield as the research background, six factors are selected as the basic discriminant factors, i.e., aquifer thickness, unit water inflow, water pressure, aquiclude thickness, fault influencing factor, and depth of a coal seam floor destroyed by rock pressure. Deng's grey relational theory was used to analyze the correlation degrees between each main controlling factor and the maximal water bursting discharge from a coal seam floor. A structural equation model was adopted to reveal the internal connecting links among the key influencing factors and determine the weights of each main controlling factor for predicting the maximal water bursting discharge from a coal seam floor. An SPSS scatter plot and MATLAB functional programming were applied to fit the correlativity curves between each main controlling factor and the maximal water bursting discharge from a coal seam floor in the Xinwen Mining Area. The optimal unitary nonlinear regression models between the maximal water bursting discharge from the coal seam floor and each main control factor were established. A multiple nonlinear regression–modified model for predicting the maximal water bursting discharge from the coal seam floor was acquired using a multiple nonlinear regression analysis with the combined weights of each main control factor. Compared with the bivariant multiple regression equation and the measured data, the results showed that the average values of forecasting errors predicted by the multiple nonlinear regression–modified model and bivariant multiple regression equation are 10.53% and 16.76%, respectively, which indicates that the multiple nonlinear regression–modified model and the bivariant multiple regression equation have higher prediction accuracy and relatively smaller error ranges, with comparatively better application value in the prediction of maximal water bursting discharge from a coal seam floor. [ABSTRACT FROM AUTHOR]