Search Results (1,254)

Spinning forming is a metal plastic processing technology used to manufacture thin-walled hollow axisymmetric parts. However, during the spinning process, issues such as excessive local loads can induce non-uniform plastic deformation, leading to poor forming quality. In this study, orthogonal experiments were conducted on V-groove specimens made of SPHE steel under different ultrasonic power (with constant static load and spinning passes) and different numbers of spinning passes (with constant static load and ultrasonic power). For each parameter set, three specimens were tested, and finite element analysis using Abaqus.2021 software was performed for verification. The study explored the influence of introducing ultrasonic-assisted spinning during spinning on the forming quality of the V-groove, as well as the effects of controlling ultrasonic power and spinning passes. By combining the ultrasonic-assisted spinning experiments with finite element simulation results, the effects and relative significance of different ultrasonic power and different spinning passes on forming quality were evaluated through analyses of V-groove depth, inclination angle, microhardness, microstructure, and roughness. The results show that ultrasonic-assisted spinning significantly improves the forming depth of the V-groove. Under 50% ultrasonic power, the groove depth increased from 434.54 μm under the reference condition to 598.09 μm. Meanwhile, the groove angle decreased from 63.27° to 60.77°, indicating improvements in groove sharpness and geometric accuracy. When the spinning passes reached 54, the groove depth increased from 299.84 μm to 560.68 μm. The findings demonstrate that ultrasonic power and the spinning passes can effectively regulate the geometric morphology of the V-groove and improve the forming quality in ultrasonic-assisted spinning. Full article

Aerospace load-bearing components require materials that exhibit high specific strength, excellent fatigue resistance, and superior environmental adaptability. Titanium alloys are indispensable for aerospace applications because of their exceptional mechanical properties, particularly their outstanding high specific strength, and their peak mechanical strength is typically achieved through solution heat treatment followed by artificial aging. This review systematically summarizes recent advances in the compositional design, microstructural evolution, and critical microstructure–property relationships of aerospace titanium alloys. It further highlights intrinsic effects of alloying elements on phase stability, dislocation behavior, and phase transformation pathways, and analyzes how lamellar, equiaxed, and bimodal microstructures regulate dislocation transfer, local strain partitioning, and damage evolution. The interactions and competition among deformation and phase-transformation mechanisms, including slip anisotropy, deformation twinning, stress-induced phase transformations, and ω-related processes, are critically assessed. However, unresolved challenges remain in quantitatively characterizing multi-mechanism coupling and local heterogeneity. To address these challenges, this review elucidates the transition rules of dominant mechanisms across different microstructures and proposes a high-precision digital composition–microstructure–property mapping framework to facilitate predictive and service-oriented alloy design. Full article

Due to the low stiffness characteristics, thin-walled parts are prone to force-induced deformation during the peripheral milling process, which severely restricts machining accuracy and efficiency. In existing studies, for curved thin-walled parts, the Finite Element Method (FEM) is usually adopted for deformation prediction. However, the traditional FEM usually requires a considerable amount of computing time, owing to the high model complexity and batch parameter evaluations. Therefore, this study proposes a method of constructing a surrogate model based on a small amount of FEM simulation data. Firstly, a peripheral milling cutting force model is established to obtain the instantaneous milling force. Secondly, a finite element model considering the material removal effect is constructed, and an iterative solution strategy is introduced to calculate the force-induced deformation. Finally, an Enhanced Latin Hypercube Sampling (ELHS) method is used to generate training samples, and the Elliptic Basis Function Neural Network (EBFNN) is selected as the surrogate model to establish a nonlinear mapping relationship between machining parameter combinations and force-induced deformation. This method enables rapid prediction of deformation at any machining position on curved thin-walled parts, reducing the computation time from hours to seconds while maintaining prediction accuracy. Full article

Reservoir water level fluctuations can reactivate landslides and cause severe losses. This study examines the Niulanjiang landslide, reactivated by the impoundment of the Xiluodu Hydropower Station in Southwest China, using field investigations, in situ displacement monitoring, and direct shear tests on soil–rock mixtures. The results show that the land-slide experienced a progressive failure process, evolving from long-term shear creep in the sliding zone to localized abrupt creep and finally to overall fracture sliding. The loose soil–rock mixture provided the structural basis for instability, whereas reservoir water level fluctuation was the dominant trigger. Rising water levels increased shear stress and promoted seepage-induced weakening, causing local failure of the sliding surface and gradual formation of a shear outlet. Laboratory tests indicate that rock block content and moisture content strongly affect mechanical behavior: higher rock block content enhances shear dilatancy and strain softening, while higher moisture content promotes shear contraction, plastic deformation, and linear reductions in cohesion and internal friction angle. The failure mechanism involves coupled strength degradation and increased seepage force. Initial instability occurred in the middle slope under hydrostatic–hydrodynamic pressure, then propagated rearward and forward, reducing front resistance and driving overall sliding toward the Niulanjiang River. These findings support early warning and mitigation of similar reservoir-induced landslides. Full article

To explore the effects of internal unloading and lateral stress on rockburst behavior in deep hard rock roadways, rockburst simulation tests were executed utilizing a self-developed internal unloading apparatus. A miniature camera was employed to monitor and record the rockburst evolution process of surrounding rock following internal unloading. Results demonstrate that the rockburst process primarily consists of four stages: the quiet stage, the buckling deformation stage, the rock fragment exfoliation stage, and the V-shaped notch formation stage. As the lateral stress increases from 15.2 MPa to 26.7 MPa, the vertical stress corresponding to the initial failure (σ_zi) increased from 64.00 MPa to 74.00 MPa, the fractal dimension of rock fragments decreases from 2.4033 to 2.3459, and the rockburst severity decreases. Under high lateral stress conditions, rock bearing capacity is comparatively high, making it less prone to rockbursts. However, more elastic strain energy accumulates inside the surrounding rock. Consequently, once a rockburst occurs, its intensity is notably greater than that subjected to low lateral stress. This suggests that increasing the lateral stress exerts a strengthening effect on the surrounding rock of the roadway. Numerical simulations were performed to study the crack evolution laws within the surrounding rock. Studies have revealed that internal unloading induces both shear and tensile cracks, but mainly tensile cracks. As the lateral stress increases, the number of shear and tensile cracks induced by internal unloading increases. The internal unloading triggers rock damage, leading to a strength-weakening effect. It becomes more pronounced as lateral stress increases. By comprehensively comparing the effects of internal unloading and lateral stress, the initial failure vertical stress increases with rising lateral stress, demonstrating an overall strength-strengthening effect induced by increasing lateral stress. Therefore, the strength-weakening effect resulting from internal unloading is weaker than that resulting from increasing lateral stress. Full article

The influence of ausforming temperature on the isothermal bainitic transformation behavior of 42CrMo steel was systematically investigated using thermo-mechanical simulation, dilatometric analysis, and electron backscatter diffraction (EBSD). The results show that ausforming significantly accelerates the bainitic transformation kinetics, whereas lower ausforming temperatures lead to a progressive reduction in the final bainite fraction. This apparently contradictory behavior originates from the competitive interaction between deformation-induced mechanical stabilization of austenite and dislocation-assisted heterogeneous nucleation of bainitic ferrite. Lower ausforming temperatures result in higher retained dislocation densities, which promote early-stage nucleation while simultaneously increasing resistance to transformation interface migration and hindering carbon redistribution. As a consequence, the bainitic ferrite microstructure is markedly refined, exhibiting reduced lath thickness and length. Crystallographic analysis reveals that the bainitic ferrite predominantly follows the Kurdjumov–Sachs orientation relationship with prior austenite, and that strong variant selection is induced by ausforming, particularly at lower deformation temperatures. The reduced variant multiplicity within individual prior austenite grains further contributes to the refinement and preferential orientation of the bainitic microstructure. These findings highlight the critical role of ausforming temperature in governing the coupled evolution of transformation kinetics, phase fraction, and crystallographic characteristics during bainitic transformation and provide guidance for microstructural control of bainitic steels through temperature-dependent thermo-mechanical processing. Full article

In this study, CoCrFeNiMn high-entropy alloys (HEAs) with different aluminum (Al) contents were fabricated, and the effects of Al content on the microstructure evolution and mechanical properties were systematically explored. The microstructural characterization results indicated that the Al content exerted a crucial regulatory effect on the crystal structure of the alloy. With increasing Al content, shifts in the characteristic XRD peaks indicate lattice expansion of the alloy. Meanwhile, the phase structure continuously evolved from a single face-centered cubic (FCC) structure to an FCC/body-centered cubic (BCC) dual-phase structure, and then finally transformed into a BCC-dominated structure. Appropriate Al element addition could produce localized stress fields near dislocations and achieve prominent solid-solution strengthening, which effectively inhibited dislocation movement and further improved the yield strength, tensile strength, and hardness of the alloy. In contrast, excessive Al addition would break through the solid solubility limit of the alloy matrix, causing obvious phase separation and the precipitation of brittle B2-ordered NiAl-type intermetallic secondary phases. These brittle secondary phases easily induced crack initiation in the plastic deformation process, which significantly deteriorated the ductility, work-hardening ability, and impact toughness of the alloys. Full article

The southeastern flank of Mt. Etna is affected by the presence of active faults capable of adapting to deformation through both seismic slip and aseismic creep, posing challenges for seismic microzonation and for land-use planning. Structural surveys in the urban area of San Gregorio di Catania revealed a ~1 km long, N–S trending secondary fracture zone with an extensional component, inducing progressive damage to buildings and infrastructure. To characterize this scarcely visible structure, passive seismic single-station surveys processed with Horizontal-to-Vertical Spectral Ratio (HVSR) tecnique were integrated with Multichannel Analysis of Surface Waves (MASW). The HVSR data enabled the mapping of the spatial distribution of resonance frequencies, tracking an anomalous trend in the seismic bedrock geometry and depth directly correlatable with the presence of the secondary fracture zone. Directional analyses exhibit systematic preferential orientations of resonance peaks near the fracture corridor, confirming a rigorous structural control and a tectonic origin for the recorded anomalies. Furthermore, reconstructed 2D impedance contrast sections show distinct discontinuities and a local westward dislocation of the main seismo-stratigraphic interface across the deformation zone. The lack of correlated instrumental seismicity supports the interpretation that the displacement is primary accommodated via aseismic fault creep. Methodologically, these findings demonstrate that the passive seismic method provides a highly effective, non-invasive approach for identifying hard-to-detect tectonic structures that remain unobliterated by dense urbanization. Ultimately, these results offer critical, actionable constraints for seismic microzonation and urban land-use setback zoning. Full article

After cold rolling of high-strength interstitial-free (IF) steel, the ferrite grains undergo plastic deformation associated with the formation of substructures and intense cold-rolling texture, which affects the microstructure and texture in the subsequent annealing process and determines the formability of the final sheet. To clarify the mechanisms of microstructure and texture formation during cold rolling of IF steel, a polycrystalline model was constructed based on the measured microstructure and texture features. A crystal plasticity model, along with a remeshing technique, was developed for IF steel. The model can calculate the deformation of the polycrystal after 70% cold rolling reduction, in which the calculated microstructure and texture features are consistent with the results from electron backscatter diffraction (EBSD). The results show that the deformed microstructure and texture are closely related to the initial crystal orientation, the interaction between neighbouring grains, and the cold rolling reduction. Grains with an initial texture orientation near <001>//ND are more stable during deformation and tend to retain their orientations after cold rolling. In contrast, grains initially deviating from the γ-fiber tend to rotate towards the <111>//ND orientation, while near-γ-fiber grains mainly retain their γ-fiber characteristics with intragranular orientation spreading during cold rolling. Multiple slip systems induce the formation of ingrain shear bands. These results establish a grain-scale link between initial orientation, intragranular substructure formation, and cold rolling texture evolution, and provide a mechanistic basis for optimizing cold rolling texture control and improving the formability of high-strength IF steel sheets. Full article

The constitutive analysis model and hot processing map of the ZM6 alloy across various deformation conditions were investigated during hot compression experiments. True stress-strain curves within 300–450 °C and 0.0001–0.1 s⁻¹ were obtained from compression tests on a Gleeble-1500 platform. The results showed that higher strain rates (e.g., 0.1 s⁻¹) induced pronounced work hardening, whereas high temperatures (300–400 °C) combined with low strain rates (10⁻⁴ s⁻¹) promoted conditions conducive to dynamic recrystallization (DRX), leading to a softening tendency of steady-state flow stress. Additionally, a modified strain-compensated constitutive model was built for flow stress prediction. Material constants were plotted as fifth-order polynomial functions of strain (0.025–0.80) for precise stress predictions. The derived activation energy (Q = 182.38 kJ/mol) falls within the typical range for Mg-RE alloys. Leave-one-temperature-out cross-validation showed average AARE values of 7.2–9.8%, demonstrating the model’s interpolation capability and its sensitivity to extrapolation. Cross-validation within the training dataset showed reasonable consistency between experimental and predicted stresses (R > 0.997, AARE < 4.35%). Using the dynamic materials model, hot processing maps identified safe deformation zones and instability zones of the ZM6 alloy. Flow instability was observed at strain rates >0.01 s⁻¹, particularly at low temperatures (300–350 °C). Optimal processing windows appeared in high-energy dissipation (η > 30%) regions, e.g., 400–450 °C/10⁻⁴–10⁻³ s⁻¹. Optical microscopy confirmed that at high temperatures (≥400 °C) and low strain rates (≤0.001 s⁻¹), a uniform, fine-grained, fully recrystallized structure can be obtained, whereas low temperatures (350 °C) and high strain rates (0.1 s⁻¹) produce coarse elongated grains with limited DRX, consistent with the instability regime predicted by the processing maps. Under intermediate conditions (e.g., 400 °C, 0.01 s⁻¹), a bimodal grain distribution indicates incomplete recrystallization. Although EBSD analysis was not performed in this study, the optical microstructures directly validate the predicted safe and unstable windows. Together, all these findings provide preliminary model-based guidance for optimizing hot working parameters to balance microstructural stability and processing efficiency. Full article

To address the key challenges in GB-RAR monitoring of super-tall buildings—namely, complex noise interference (transient pulse disturbances coupled with high-frequency random fluctuations), the difficulty of distinguishing normal wind-induced vibrations from hazardous deformations, and the propensity of single-algorithm prediction models to converge prematurely—this paper proposes an integrated monitoring data processing workflow that combines status assessment and deformation early warning, using Wuhan Greenland Center as a case study. A denoising method combining Median Absolute Deviation outlier removal and Savitzky–Golay filtering was designed for preprocessing, quantitatively validated through signal-to-noise ratio analysis. Based on filtered data, a spatio-temporal trajectory model was established to visualize and evaluate building movement. Furthermore, a GB-RAR-oriented residual-driven warning framework was developed by coupling a PSO-GA-BP deformation prediction model with adaptive sliding-window thresholding and finite-state warning decisions. Simulation results demonstrate that the PSO-GA-BP model outperforms other neural network models in prediction accuracy, and the derived early warning system exhibits strong feasibility and sensitivity. This workflow proves suitable for GB-RAR deformation monitoring of super-tall buildings, offering valuable reference for future research. Full article

This study investigates the reliability of power-terminal solder joints in intelligent power modules (IPMs) subjected to thermal cycling, random vibration, and packaging/assembly-induced deformation. Fifty IPMs were tested under temperature cycling from −55 °C to 125 °C and random vibration from 20 to 2000 Hz, and the experimental observations were combined with finite element simulations of thermal, vibration, and deformation loads. The modules survived 200 temperature cycles in the free state, whereas functional abnormalities occurred after board-level assembly and subsequent environmental loading. Simulation results showed that random vibration produced limited solder-layer stress because the first structural mode was above the excitation range, while packaging and PCB deformation markedly increased the initial stress of the power-terminal solder joints. When local deformation reached approximately 0.5 mm, the calculated solder-pad stress reached or exceeded the shear-strength risk range, consistent with the failure tendency observed in highly deformed modules. Weibull analysis further indicated a fatigue-dominated failure process with an increasing failure rate. These findings suggest that deformation control, package stiffness improvement, and assembly flatness management are critical for improving the reliability of IPM power-terminal solder joints. Full article

As tunnel engineering continues to advance toward deeper, longer, and more complex projects, the risks encountered during the construction phase have evolved into a combination of various disaster types and the accumulation of multiple contributing factors. Traditional empirical and semi-empirical risk management methods are increasingly revealing shortcomings in terms of timeliness, accuracy, and the ability to process multi-source data. In recent years, driven by advancements in computing power and sensor technology, artificial intelligence algorithms (AI algorithms) such as machine learning and deep learning have been rapidly adopted in tunnel construction risk management. This paper retrieved relevant literature from the Web of Science database covering the period from 2010 to 2025. After rigorous screening, 96 highly relevant papers were selected for bibliometric analysis. This paper systematically reviews research progress from two perspectives: algorithmic models and engineering applications. The review indicates that, in terms of algorithmic models, traditional machine learning, convolutional neural network, recurrent neural network, generative adversarial network, Transformer, and graph neural network constitute a multi-level technical framework encompassing feature representation, risk perception, and intelligent decision-making. In terms of applications, AI algorithms have been widely integrated into typical scenarios such as geological hazard identification and prediction, surrounding rock stability and deformation prediction, rock burst assessment and early warning, lining defect detection and structural safety assessment, construction-induced ground settlement prediction, and tunnel gas and fire hazard prediction, significantly enhancing risk identification and early warning capabilities. However, several challenges remain, including the scarcity of high-quality datasets, the prevalence of noisy, incomplete, and heterogeneous monitoring data, insufficient coupling between model interpretability and engineering mechanisms, limited cross-project transferability, and the lack of integrated management systems for multi-hazard lifecycle control. Based on this, this paper proposes future research directions in areas such as data infrastructure development, integration of mechanism constraints, and multi-hazard collaborative modeling, aiming to provide guidance for the further development of intelligent risk management in tunnel construction. Full article

The nanoindentation analysis of zirconium carbide (ZrC) has been studied through molecular dynamics simulations, focusing on various factors such as temperature, stoichiometric ratio, and crystal orientation. The findings show that as temperature increases, both the critical pop-in load and the maximum load decrease, while atomic strain, von Mises stress, and residual indentation depth increase. High temperatures facilitate the nucleation and propagation of 1/2<110> dislocations, which enhance the material’s ability to undergo plastic deformation. Both indentation hardness and Young’s modulus decrease linearly as temperature rises or the concentration of C vacancy increases. For stoichiometric ZrC, as the temperature rises from 10 K to 2100 K, the hardness decreases from 45.04 GPa to 20.36 GPa, and Young’s modulus drops from 396.28 GPa to 254.45 GPa. At 10 K, when the C/Zr ratio is reduced to 0.5, the hardness and Young modulus decrease to 25.32 GPa and 192.09 GPa, respectively. This reduction is attributed to the weakening of Zr-C bonds, which also reduces stress concentration. At elevated temperatures, the impact of C vacancies on the nanoindentation process diminishes due to the thermal softening of the substrate, which lessens the effects of vacancy-induced softening. Regarding anisotropy, Young’s modulus at room temperature decreases from 383.39 GPa on the (001) plane to 335.93 GPa on the $(1\stackrel{\mathrm{-}}{1}0)$ plane, and it reduces further to 303.31 GPa on the $(1\stackrel{\mathrm{-}}{1}1)$ plane; hardness shows a similar decreasing trend. This trend is primarily due to differences in slip systems, surface energies, and the angles between the plane normal and the Zr-C bond axis located directly beneath the surface atoms. Overall, these results may provide theoretical support for the processing and application of ZrC. Full article

Developing low-cost, Co-free high-entropy alloys (HEAs) that retain both high strength and useful ductility at cryogenic temperatures remains challenging because hard strengthening phases usually intensify strain localization and accelerate plastic instability. In this work, a Fe-enriched Al₁₁Cr₁₄Fe₅₀Ni₂₅ HEA was designed and processed by heavy cold rolling followed by short-time annealing at 900 °C for 10 min to construct a hierarchical heterogeneous microstructure. The alloy consists of an FCC-dominated matrix and an ordered B2 phase distributed in recrystallized and unrecrystallized domains over multiple length scales. Tensile testing shows that the alloy achieves a yield strength of 953 MPa, an ultimate tensile strength of 1160 MPa, and an elongation of 21.1% at 298 K, while these values increase to 1268 MPa, 1686 MPa, and 28.6%, respectively, at 77 K. Load–unload–reload analysis at 77 K reveals that the hetero-deformation-induced stress reaches about 804 MPa at a true strain of 25%, contributing more than 52% of the total flow stress. The superior cryogenic strength–ductility synergy is attributed to strain partitioning between soft FCC and hard B2 phases and between recrystallized and unrecrystallized regions, which promotes geometrically necessary dislocation accumulation, back-stress strengthening, and sustained work hardening. This study demonstrates that hierarchical heterostructure design provides an effective route for developing cost-conscious Co-free HEAs for cryogenic structural applications. Full article