Search Results (138)

This study is based on the laser-induced thermal-crack propagation (LITP) technology, focusing on the issues of deviation and thermal damage during the transverse crack propagation process, with the aim of achieving high-purity, non-destructive, and high-precision cutting of glass. A 50 W, 1064 nm fiber laser is used for S-pattern scanning cutting of soda–lime glass. A moving heat source model is established and analyzed via MATLAB R2022a numerical simulation. Combined with the ABAQUS 2019 software, the relationships among temperature field, stress field, crack propagation, and deviation during laser-induced thermal crack cutting are deeply explored. Meanwhile, laser thermal fracture experiments are also carried out. A confocal microscope detects glass surface morphology, cross-sectional roughness and hardness under different heat flux densities (HFLs), determining the heat flux density threshold affecting the glass surface quality. Through a comprehensive study of theory, simulation, and experiments, it is found that with an increase in the HFL value of the material, the laser-induced thermal crack propagation can be divided into four stages. When the heat flux density value is in the range of 47.2 to 472 W/m², the glass substrate has good cross-sectional characteristics. There is no ablation phenomenon, and the surface roughness of the cross-section is lower than 0.15 mm. The hardness decreases by 9.19% compared with the reference value. Full article

Complete dentures are exposed to complex masticatory forces that may lead to material fatigue and eventual structural failure. Occlusal relationships, such as eugnathic and progenic, influence the distribution of these forces significantly. Understanding their biomechanical impact is essential for improving denture design and longevity. The aim of this study was to evaluate the mechanical behaviour of complete dentures under bite loads in eugnathic and progenic occlusal relationships, using both experimental testing and numerical simulations. The focus was placed on identifying the conditions that lead to initial damage and the patterns of stress distribution. The material properties of the denture base and artificial teeth were determined through experimental tensile and compressive testing on cylindrical PMMA specimens. The denture geometry was acquired via 3D tomography based on impressions of an edentulous patient. Experimental testing of the denture bite was conducted to determine the force thresholds at which the initial cracks occur. Numerical simulations were carried out using finite element analysis at bite loads of 100 N and 200 N in both occlusal types, incorporating the obtained material parameters. The experimental results showed that the first signs of denture damage occurred at 6400 N in eugnathic occlusion and 7010 N in progenic occlusion. The numerical simulations confirmed that, during occlusion, the pressure is redistributed across multiple contact points, with a broader distribution reducing the localised stress. This redistribution was more efficient in eugnathic occlusion, which reduced the risk of longitudinal cracking in acrylic teeth. In contrast, progenic occlusion showed higher susceptibility to fractures within the acrylic denture base, particularly between adjacent teeth. Both the experimental and numerical approaches demonstrated that occlusal relationships affect the mechanical resilience of complete dentures directly. The findings highlight that eugnathic occlusion offers biomechanical advantages in stress distribution, potentially reducing the risk of fracture. Incorporating occlusal analysis into denture design protocols can enhance clinical outcomes and improve prosthetic longevity. Full article

This paper focuses on the stability issues of geological and engineering structures and conducts research from two perspectives: the mechanism of slope landslides under micro-seismic action and the cyclic failure behavior of concrete materials. In terms of slope stability, through the combination of model tests and theories, the cumulative effect of circulating micro-seismic waves on the internal damage of slopes was revealed. This research finds that the coupling of micro-vibration stress and static stress significantly intensifies the stress concentration on the slope, promotes the development of potential sliding surfaces and the extension of joints, and provides a scientific basis for the prediction of landslide disasters. This helps protect mountain ecosystems and reduce soil erosion and vegetation destruction. The number of cyclic loads has a power function attenuation relationship with the compressive strength of concrete. After 1200 cycles, the strength drops to 20.5 MPa (loss rate 48.8%), and the number of cracks increases from 2.7 per mm³ to 34.7 per mm³ (an increase of 11.8 times). Damage evolution is divided into three stages: linear growth, accelerated expansion, and critical failure. The influence of load amplitude on the number of cracks shows a threshold effect. A high amplitude (>0.5 g) significantly stimulates the propagation of intergranular cracks in the mortar matrix, and the proportion of intergranular cracks increases from 12% to 65%. Grey correlation analysis shows that the number of cycles dominates the strength attenuation (correlation degree 0.87), and the load amplitude regulates the crack initiation efficiency more significantly (correlation degree 0.91). These research results can optimize the design of concrete structures, enhance the durability of the project, and indirectly reduce the resource consumption and environmental burden caused by structural damage. Both studies are supported by numerical simulation and experimental verification, providing theoretical support for disaster prevention and control and sustainable engineering practices and contributing to ecological environment risk management and the development of green building materials. Full article

Flexible pipe end fittings (EFs) transfer axial loads by embedding tensile armor within epoxy matrices. The integrity of bonding between the armor and resin profoundly influences the EF load-bearing capacity. This study investigated the debonding failure mechanism at the epoxy-resin–tensile-armor interface in flexible pipe end fittings through integrated experimental and numerical approaches. Combining tensile tests with digital image correlation (DIC) and cohesive zone modeling (CZM), the research quantified the impacts of interfacial defects and adhesive properties on structural integrity. Specimens with varying bond lengths (40–60 mm) and defect diameters (0–4 mm) revealed that defects significantly reduced load-bearing capacity, with larger defects exacerbating strain localization and accelerating failure. A dimensionless parameter, the defect-size-to-bond-length ratio ($\lambda =D/2L$), was proposed to unify defect impact analysis, demonstrating its nonlinear relationship with failure load reduction. High-toughness adhesives, such as Sikaforce^® 7752, mitigated defect sensitivity by redistributing stress concentrations, outperforming brittle alternatives like Araldite^® AV138. DIC captured real-time strain evolution and crack propagation, validating strain concentrations up to 3.2 at defect edges, while CZM simulations achieved high accuracy (errors: 3.0–7.2%) in predicting failure loads. Critical thresholds for λ (λ < 0.025 for negligible impact; λ > 0.05 requiring defect control or high-toughness adhesives) were established, providing actionable guidelines for manufacturing optimization and adhesive selection. By bridging experimental dynamics with predictive modeling, this work advances the design of robust deepwater energy infrastructure through defect management and material innovation, offering practical strategies to enhance structural reliability in critical applications. Full article

Integrating machine learning into additive manufacturing offers transformative opportunities to optimize material properties and design high-performance, fatigue-resistant structures for critical applications in aerospace, biomedical, and structural engineering. This study explores mechanistic machine learning techniques to tailor microstructural features, leveraging data from ultrasonic fatigue tests where very high cycle fatigue properties were assessed up to $1\times {10}^{10}$ cycles. Machine learning models predicted critical fatigue thresholds, optimized process parameters, and reduced design iteration cycles by over 50%, leading to faster production of safer, more durable components. By refining grain orientation and phase uniformity, fatigue crack propagation resistance improved by 20–30%, significantly enhancing fatigue life and reliability for mission-critical aerospace components, such as turbine blades and structural airframe parts, in an industry where failure is not an option. Additionally, the machine learning-driven design of metamaterials enabled structures with a 15% weight reduction and improved yield strength, demonstrating the feasibility of bioinspired geometries for lightweight applications in space exploration, medical implants, and high-performance automotive components. In the area of titanium and aluminum alloys, machine learning identified key process parameters such as temperature gradients and cooling rates, which govern microstructural evolution and enable fatigue-resistant designs tailored for high-stress environments in aircraft, biomedical prosthetics, and high-speed transportation. Combining theoretical insights and experimental validations, this research highlights the potential of machine learning to refine microstructural properties and establish intelligent, adaptive manufacturing systems, ensuring enhanced reliability, performance, and efficiency in cutting-edge engineering applications. Full article

In the field of nondestructive evaluation (NDE) using ultrasonic guided waves, accurately assessing the aging failure of insulation coatings remains a challenging and prominent research topic. While the application of ultrasonic guided waves in material testing has been extensively explored in the existing literature, there is still a significant gap in quantitatively evaluating the aging failure of insulation coatings. This study innovatively proposes an NDE method for assessing insulation coating aging failure by integrating signal processing and machine learning technologies, thereby effectively addressing both theoretical and practical gaps in this domain. The proposed method not only enhances the accuracy of detecting insulation coating aging failure but also introduces new approaches to non-destructive testing technology in related fields. To achieve this, an accelerated aging experiment was conducted to construct a cable database encompassing various degrees of damage. The effects of aging time, temperature, mechanical stress, and preset defects on coating degradation were systematically investigated. Experimental results indicate that aging time exhibits a three-stage nonlinear evolution pattern, with 50 days marking the critical inflection point for damage accumulation. Temperature significantly influences coating damage, with 130 °C identified as the critical threshold for performance mutation. Aging at 160 °C for 100 days conforms to the time-temperature superposition principle. Additionally, mechanical stress concentration accelerates coating failure when the bending angle is ≥90°. Among preset defects, cut defects were most destructive, increasing crack density by 5.8 times compared to defect-free samples and reducing cable life to 40% of its original value. This study employs Hilbert–Huang Transform (HHT) for noise reduction in ultrasonic guided wave signals. Compared to Fast Fourier Transform (FFT), HHT demonstrates superior performance in feature extraction from ultrasonic guided wave signals. By combining HHT with machine learning techniques, we developed a hybrid prediction model—HHT-LightGBM-PSO-SVM. The model achieved prediction accuracies of 94.05% on the training set and 88.36% on the test set, significantly outperforming models constructed with unclassified data. The LightGBM classification model exhibited the highest classification accuracy and AUC value (0.94), highlighting its effectiveness in predicting coating aging damage. This research not only improves the accuracy of detecting insulation coating aging failure but also provides a novel technical means for aviation cable health monitoring. Furthermore, it offers theoretical support and practical references for nondestructive testing and life prediction of complex systems. Future studies will focus on optimizing model parameters, incorporating additional environmental factors such as humidity and vibration to enhance prediction accuracy, and exploring lightweight algorithms for real-time monitoring. Full article

The thermal through-silicon-via (TTSV) has a serious thermal stress problem due to the mismatch of the coefficient of thermal expansion between the Si substrate and filler metal. At present, the thermal stress characteristics and strain mechanism of TTSV are mainly concerned with increases in temperature, and its temperature range is concentrated between 173 and 573 K. By employing finite element analysis and a device simulation method based on temperature-dependent material properties, the impact of TTSV thermal stress on metal-oxide-semiconductor field-effect transistor (MOSFET) properties is investigated under cooling down from room temperature to the ultra-low temperature (20 mK), where the magnitude of thermal stress in TTSV is closely associated with the TTSV diameter and results in significant tension near the Cu-Si interface and consequently increasing the likelihood of delamination and cracking. Considering the piezoresistive effect of the Si substrate, both the TTSV diameter and the distance between TTSV and MOSFET are found to have more pronounced effects on electron mobility along [100] crystal orientation and hole mobility along [110] crystal orientation. Applying a gate voltage of 3 V, the saturation current for the 45 nm-NMOS transistor oriented along channel [100] experiences a variation as high as 34.3%. Moreover, the TTSV with a diameter of 25 μm generates a change in MOSFET threshold voltage up to −56.65 mV at a distance as short as 20 μm. The influences exerted by the diameter and distance are consistent across carrier mobility, saturation current, and threshold voltage parameters. Full article

A novel method to measure dynamic flow stress and corresponding strain rates obtained from Taylor tests using profiled samples with a reduced cylindrical head part was applied to study the dynamic characteristics of similar commercial 7075 and V95T1 aluminum alloys. The measured dynamic flow stress is verified using a classical Taylor’s approach with uniform cylinders and compared with the literature data. Our study shows that the dynamic flow stress of 7075 alloy, which is 786 MPa at strain rates of (4–8) × 10³ s⁻¹, exceeds the value of 624 MPa for V95T1 alloy at strain rates of (2–6) × 10³ s⁻¹ by 25%. The threshold impact velocity resulting in fracture of the 4 mm head part of the profiled samples is 116–130 m/s for 7075 alloy and only 108 m/s for V95T1 alloy. The fracture pattern is also different between the alloys with characteristic shear-induced cracks oriented at 45° to the impact direction in the case of V95T1 alloy and perpendicular to the breaking off head part in the case of 7075 alloy. On the other hand, the compressive fracture strain of V95T1 alloy, which is 0.29–0.36, exceeds that of 7075 alloy, which is 0.27–0.33, by approximately 8%. Thus, V95T1 aluminum alloy exhibits less strength but is more ductile, while 7075 aluminum alloy exhibits more strength but is simultaneously more brittle. Full article

The fracture evolution and the strength characteristics of a jointed rock mass under hydro-mechanical coupling are key issues that affect the safety and stability of underground engineering. In this study, a kind of transparent rock-like resin was adopted to investigate the crack initiation and propagation modes of the 3D flaw under hydro-mechanical coupling. The influences of the water pressure and the flaw dip angle on the fracture modes of the 3D flaw and the strength properties of the specimen were analyzed. The experiment results indicated that under the initiation and propagation modes, the 3D flaw presented two types of modes: the low-water-pressure type and the high-water-pressure type. The increase in the water pressure had a significant promoting effect on the crack initiation and propagation, which changed the overall failure mode of the specimen. With the increase in the flaw dip angle, the critical growth length of the wing crack decreased and the initiation moment of the fin-like crack showed a hysteretic tendency. The influences of the water pressure on the crack initiation stress and failure strength had thresholds. When lower than the threshold, the crack initiation stress increased slightly and the failure strength decreased gradually with the increase in the water pressure. Once the threshold was exceeded, both the crack initiation stress and the failure strength decreased significantly with the increase in the water pressure. With the increase in the flaw dip angle, both the crack initiation stress and the failure strength showed a first decreasing and then increasing tendency. The lowest crack initiation stress and the failure strength were found for the specimen containing the 45° flaw, while the highest were found for the specimen containing the 75° flaw. This study helps to deepen the understanding of the fracture mechanism of the engineering rock mass under hydro-mechanical coupling and has certain theoretical and applied value in engineering design and construction safety. Full article

Avian eggs are products of consumer demand, with modern methodologies for their morphometric analysis used for improving quality, productivity and marketability. Such studies open up numerous prospects for the introduction of artificial intelligence (AI) and deep learning (DL). We first consider the state of the art of DL in the poultry industry, e.g., image recognition and applications for the detection of egg cracks, egg content and freshness. We comment on how algorithms need to be properly trained and ask what information can be gleaned from egg shape. Considering the geometry of egg profiles, we revisit the Preston–Biggins egg model, the Hügelschäffer’s model, universal egg models, principles of egg universalism and “The Main Axiom”, proposing a series of postulates to evaluate the legitimacy and practical application of various mathematical models. We stress that different models have pros and cons, and using them in combination may yield more useful results than individual use. We consider the classic egg shape index alongside other alternatives, drawing conclusions about the importance of indices in the context of applying DL going forward. Examining egg weight, volume, surface area and air cell calculations, we consider how DL might be applied, e.g., for egg storage. The value of DL in egg studies is in pre-incubation egg sorting, the optimization of storage periods and incubation regimes, and the index representation of dimensional characteristics. Each index can thus be combined to provide a synergy that is on the threshold of many scientific discoveries, technological achievements and industrial successes facilitated through AI and DL. Full article

The resistance to near-threshold fatigue crack growth and its correlation with the microstructure of the Ti-5Al-3Mo-3V-2Zr-2Cr-1Nb-1Fe alloy were investigated. K-decreasing fatigue crack propagation rate tests were conducted on compact tension samples (ASTM standard) with a stress ratio R of 0.1 and a frequency of 15 HZ in a laboratory atmosphere. At a similar strength level of 1200 MPa, the sample with a fine basket-weave microstructure (F-BW) displayed the slowest near-threshold fatigue crack propagation rate compared with the samples with equiaxed (EM) and basket-weave (BW) microstructures. The fatigue threshold value (ΔK_th) was 4.4 MPa·m^1/2 for F-BW, 3.6 for BW, and 3.2 for EM. The fracture surfaces and crack profiles were observed by scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) to elucidate the mechanism of fatigue crack propagation in the near-threshold regime. The results revealed that the near-threshold crack growth in the three samples was primarily transgranular. The crack always propagated parallel to the crystal plane, with a high Schmid factor. In addition, the near-threshold fatigue crack growth behavior was synergistically affected by the crack tip plastic zone and crack bifurcation. The increased fatigue crack propagation resistance in F-BW was attributed to the better stress/strain compatibility and greater number of interface obstacles in the crack tip plastic zone. Full article

This study investigated the effect of pre-deformation on the corrosion fatigue crack propagation (CFCG) of Al-Mg-Zn alloy in a corrosive environment. Tensile tests at different pre-deformation levels and molecular dynamics simulations analyzed changes in dislocation density. Corrosion fatigue experiments were conducted in a 3.5% NaCl solution at room temperature, and crack propagation morphology was characterized using electron backscatter diffraction (EBSD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The results showed that tensile strength increased by 2.63% and 10.00% for 5% and 10% pre-deformation, respectively. The crack propagation threshold values were L₂ (6.36 MPa·m^1/2) > L₀ (6.05 MPa·m^1/2) > L₁ (5.13 MPa·m^1/2), attributed to increased dislocation density and material strength. At 5% pre-deformation, dislocation pile-ups created stress concentrations that facilitated crack propagation. In contrast, the non-uniform dislocation distribution at 10% pre-deformation enhanced both material strength and resistance to crack growth. Full article

Cyclic failure problems in layered ductile iron are evident in a wide range of elements in transportation and mining equipment and depend on production technology and operating conditions. The aim of this study was to analyze the effect of residual stresses on the behavior of cyclic and static failure. The stress intensity factor, crack initiation, propagation patterns, static tension diagrams, and fracture behavior of compact tension (CT) specimens were determined. The samples used in this study were made from base cast iron, some of which were subjected to a special localized heat treatment. Experimental and analytical methods were used to conduct this study. The experiments were performed using original testing methods that adhered to the American Society for Testing and Materials (ASTM) regulations. The deformations of the partially heat-treated specimens due to residual stresses were determined using the grid method. The limiting stress intensity coefficient and the failure threshold under cyclic loading were determined in accordance with ASTM recommendations for various crack depths and openings. The results show that the heat treatment process readily produces residual stresses of different magnitudes, stress redistribution, different structures, and layer positions. Residual stresses affect the crack initiation and propagation. The stress intensity factor depends on the depth of the crack, the position of the layers, and the magnitude of the residual stresses. Full article

As the extraction of oil and gas progresses into deeper and ultra-deep geological formations, the enhancement of rock-breaking efficiency in drill bits has emerged as a critical factor in ensuring energy security. Among the various techniques employed, vibratory percussion drilling technology is widely recognized for its ability to improve both the efficiency and speed of penetrating hard rock formations. This study examined the effects of varying loading conditions on the characteristics of rock fracture and damage, maintaining a constant cutting speed and lead angle. By designing a small polycrystalline diamond compact (PDC) drill bit and incorporating simulation results, the research sought to analyze the influence of axial impact components on the efficiency of breaking dolomite samples, as well as the effects of impact frequency and amplitude on drilling pressure and rock-breaking energy. The findings revealed that an increase in the axial impact amplitude significantly enhanced rock-breaking efficiency, elevated von Mises stress, and increased principal compressive stress. An increase in impact frequency effectively reduced the overall stress and frictional work. These results underscored that the stress analysis revealed that the peak stress increased at lower impact amplitudes, with notable changes occurring at an amplitude of 1.5, leading to a 100% increase in Mises peak stress compared with an amplitude of 1.0. Axial impact drilling promoted deep crack formation and the development of a tensile damage zone beneath the cutter, indicating its effective rock-breaking capabilities. Axial impact drilling significantly reduced the threshold drilling pressure compared with conventional rotation, with an impact amplitude of 0.3 mm decreasing the static load by 44.1%. Additionally, increasing the axial impact amplitude enhanced the rate of penetration (ROP) while maintaining a constant static load, resulting in remarkable efficiency improvements. The results of the study are expected to provide theoretical guidance for the mechanism of impact rock breaking and the design of impact rock-breaking tool parameters. Full article

In this study, changes in the basic physical properties, mineral composition, mass, and microstructure of layered sandstone were evaluated following heat treatment at 200–800 °C. Dynamic impact compression tests were performed using a split-Hopkinson pressure bar test system (SHPB), and digital image correlation (DIC) was used to monitor the dynamic failure processes of the involved specimens. Results indicate that high-temperature treatment reduces the mass, wave velocity and peak stress of layered sandstone; increases the porosity, pore length, and pore aperture. The rates of decrease in the wave velocity and peak stress considerably increase with increasing temperature above a threshold of 400 °C. This is because at temperatures above 400 °C, thermal cracks will form both between and within particles. As the number of cracks increases, they will propagate and connect with each other, forming a network of cracks. DIC results show that as the heat treatment temperature rises, the range of the strain-concentration areas, which are formed by sandstone failures, substantially expands. However, the increase in the heat treatment temperature only negligibly influences the propagation direction of primary sandstone cracks, which mainly propagate along the weak bedding planes. Full article