Transactions of Nonferrous Metals Society of China (中国有色金属学报)•2026•DOI: 10.1016/S1003-6326(26)67057-4
The ignition vulnerability of magnesium alloys restricts their deployment in high-temperature aerospace and railway applications. This study investigates the influence of calcium content (0, 0.6, 1.2, 1.8 wt.%) on the microstructure, mechanical properties, and ignition resistance of gravity-cast and hot-extruded Mg−6Zn−0.6Zr alloys. Calcium addition promotes the formation of Ca2Mg6Zn3 phases while suppressing MgZn2 precipitation in the as-cast condition. Homogenization dissolves most MgZn2 phases but retains numerous Ca2Mg6Zn3 particles. Subsequent extrusion fragments the Ca2Mg6Zn3 phases and precipitates nanoscale MgZn2 within the matrix. The synergy of fine grains and high-density precipitates substantially enhances strength. The Mg−6Zn−0.6Zr−1.2Ca alloy achieves optimal mechanical performance, with ultimate tensile strength of 380.1 MPa, yield strength of 360.1 MPa, and elongation of 10.4%. The ignition point increases from 556 °C for the Ca-free alloy to 824 °C for the 1.8 wt.% Ca alloy, attributed to the formation of a dense CaO−MgO oxide layer. These findings demonstrate that calcium alloying offers a cost-effective, rare-earth-free pathway to simultaneously improve mechanical integrity and ignition resistance in magnesium alloys.
Journal of Central South University•2026•DOI: 10.1007/s11771-026-6272-8
The development of coalbed methane in China is constrained by complex geological conditions characterized by low permeability, low saturation, low reservoir pressure, and high adsorption ("three lows and one high"), posing significant challenges to its efficient development. The liquid nitrogen-induced fracturing and permeability enhancement technology can effectively promote the expansion and connection of macroscopic and microscopic fractures, thereby improving the permeability of coal seams. In this study, industrial micro-CT scanning technology, the VRA-UNet method, and fractal dimension calculation methods are employed to conduct an in-depth analysis of the action mechanism of liquid nitrogen cold soaking on the fracture structure of coal bodies with different metamorphism degrees. The results indicate that liquid nitrogen cold soaking promotes the generation, expansion, and connection of new fractures inside coal bodies to form fracture networks. Via Matlab programming and VG Studio MAX image analysis software, fracture extraction and calculation are performed on CT-scanned coal samples; it is statistically found that the quantitative fracture indices of coal increase after liquid nitrogen cold soaking. Compared with the fracture spectrum peak proportions of raw coal samples, the fracture spectrum peak proportions of anthracite, bituminous coal, and lignite increase by 8.375%, 12.680%, and 79.939%, respectively after liquid nitrogen cold soaking. By combining the VRA-UNet method for coal fracture identification, the box-counting method is used to calculate that the fractal dimension of coal fractures after liquid nitrogen cold soaking is larger than that of raw coal samples. The research findings of this paper will provide theoretical and technical support for the efficient development of coalbed methane and the improvement of coal seam gas extraction rates.
Int. Journal of Mining Science and Technology (采矿与安全工程)•2025•DOI: 10.1016/j.ijmst.2025.05.001
Prolonged cyclic water intrusion has progressively developed joints in the hydro-fluctuation belt, elevating the instability risk of reservoir bank slopes. To investigate its impact on joint shear damage evolution, joint samples were prepared using three representative roughness curves and subjected to direct shear testing following cyclic water intrusion. A shear damage constitutive model considering the coupling effect of cyclic water intrusion and load was developed based on macroscopic phenomenological damage mechanics and micro-statistical theory. Results indicate: (1) All critical shear mechanical parameters (including peak shear strength, shear stiffness, basic friction angle, and joint compressive strength) exhibit progressive deterioration with increasing water intrusion cycles; (2) Model validation through experimental curve comparisons confirms its reliability. The model demonstrates that intensified water intrusion cycles reduce key mechanical indices, inducing a brittle-to-ductile transition in joint surface deformation — a behavior consistent with experimental observations; (3) Damage under cyclic water intrusion and load coupling follows an S-shaped trend, divided into stabilization (water-dominated stage), development (load-dominated stage), and completion stages. The research provides valuable insights for stability studies, such as similar model experiments for reservoir bank slopes and other water-related projects.
Ship Mechanics (船舶力学)•2025•DOI: 10.3969/j.issn.1007-7294.2025.06.009
As a typical steel, the fatigue of marine high-strength steels has been emphasized by scholars. In this paper, the fatigue performance and crack growth mechanism of a high-strength steel for ships are investigated by experimental methods. First, the fatigue threshold test and fatigue crack growth rate test of this high-strength steel under different stress ratios were carried out. The influence of stress ratio on the fatigue properties of this steel was analyzed. Secondly, scanning electron microscope was used to analyze the crack growth specimen section of this steel. The crack growth and failure mechanism of this steel were revealed. Finally, based on the above research results, the stress ratio effect of high-strength steel was investigated from the perspectives of crack closure and driving force. Considering the fatigue behavior in the near-threshold stage and the destabilization stage, a fatigue crack growth behavior prediction model of high-strength steel was established. The accuracy of the model was verified by test data. Moreover, the applicability of the modified model to various materials and its excellent predictive ability were verified through comparison with literature data and existing models.
Chinese Journal of Mechanical Engineering•2025•DOI: 10.1186/s10033-025-01336-1
Autonomous driving technology is constantly developing to a higher level of complex scenes, and there is a growing demand for the utilization of end-to-end data-driven control. However, the end-to-end path tracking process often encounters challenges in learning efficiency and generalization. To address this issue, this paper designs a deep deterministic policy gradient (DDPG)-based reinforcement learning strategy that integrates imitation learning and feedforward exploration in the path following process. In imitation learning, the path tracking control data generated by the model predictive control (MPC) method is used to train an end-to-end steering control model of a deep neural network. Another feedforward exploration behavior is predicted by road curvature and vehicle speed, and adds it and imitation learning to the DDPG reinforcement learning to obtain decision-making experience and action prediction behavior of the path tracking process. In the reinforcement learning process, imitation learning is used to update the pre-training parameters of the actor network, and a feedforward steering technique with random noise is adopted for strategy exploration. In the reward function, a hierarchical progressive reward form and a constrained objective reward function referring to MPC are designed, and the actor-critic network architecture is determined. Finally, the path tracking performance of the designed method is verified by comparing various training results, simulations, and HIL tests. The results show that the designed method can effectively utilize pre-training and feedforward prior experience to obtain optimal path tracking performance of an autonomous vehicle, and has better generalization ability than other methods. This study provides an efficient control scheme for improving the end-to-end control performance of autonomous vehicles.
Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报)•2025•DOI: 10.1007/s12613-024-2983-8
The evolution of the microstructure and mechanical properties of WE43 magnesium alloy during multipass hot rolling was investigated. Results revealed that multipass hot rolling promoted the formation of small second phases, which was conducive to multiple dynamic recrystallization, consequently improving the microstructure homogeneity and refining the average grain size from 34.3 μm in the initial material to 8.83 μm. Meanwhile, the rolling deformation rotated abundant c-axis of the grains in the normal direction, resulting in a strong fiber texture. The yield strength in the rolling direction (RD) was improved from 164 MPa in the initial material to 324 MPa in the Pass 3 sheet due to fine-grained strengthening, second-phase strengthening, and texture modification. In addition, the distribution maps of the deformation mechanism indicated that the yield strength anisotropy between the RD and the transverse direction (TD) can be attributed to the effects of the texture component on the dominant mechanism. The dominant deformation mechanism during the tensile test was the prismatic slip caused by the strong basal texture of the RD, whereas it had a lesser proportion of prismatic slip under the influence of the weak basal texture of the TD. Compared to the basal slip, the higher critical resolved shear stress of the prismatic slip resulted in a higher increase in yield strength along the RD at approximately 51 MPa than that along the TD (RD: increase of 160 MPa; TD: increase of 109 MPa).
Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报)•2025•DOI: 10.1007/s12613-024-3045-y
The corrosion degradation of organic coatings in tropical marine atmospheric environments results in substantial economic losses across various industries. The complexity of a dynamic environment, combined with high costs, extended experimental periods, and limited data, places a limit on the comprehension of this process. This study addresses this challenge by investigating the corrosion degradation of damaged organic coatings in a tropical marine environment using an atmospheric corrosion monitoring sensor and a random forest (RF) model. For damage simulation, a polyurethane coating applied to a Fe/graphite corrosion sensor was intentionally scratched and exposed to the marine atmosphere for over one year. Pearson correlation analysis was performed for the collection and filtering of environmental and corrosion current data. According to the RF model, the following specific conditions contributed to accelerated degradation: relative humidity (RH) above 80% and temperatures below 22.5°C, with the risk increasing significantly when RH exceeded 90%. High RH and temperature exhibited a cumulative effect on coating degradation. A high risk of corrosion occurred in the nighttime. The RF model was also used to predict the coating degradation process using environmental data as input parameters, with the accuracy showing improvement when the duration of influential environmental ranges was considered.