Search Results (48)

To solve the problems of poor weld formation, difficult slag removal, and inferior joint microstructure and hardness in conventional narrow-gap submerged arc welding (NG-SAW), a swing arc NG-SAW process assisted by pre-embedding cold wires was proposed. Synergistically optimizing the welding energy parameters and additional cold wires ensured sound weld formation and enhanced slag detachability, while the efficiency of multilayer welding was improved by reducing the number of weld layers by 33.3%. The slag adhesion mechanism is clarified as follows: a high welding heat input facilitates elemental diffusion at the weld–slag interface, leading to the formation of a continuous and thick interlayer composed of (Fe,Mn)O and MgO-Al₂O₃-CaO phases. This interlayer strengthens the chemical bonding between slag and weld, thereby impeding slag removal. Microstructure evolution analysis of the multilayer welded joint revealed that the variable-angle design increases the groove volume and, combined with the heat-absorbing effect of the additional wires, accelerates molten pool cooling, thereby refining grains in both the weld metal zone and reheat-affected zone. Meanwhile, the tempering exerted by the heat-affected zone (HAZ) of the subsequent weld layer on the previous layer is attenuated. This promotes the gradual transformation of hard-brittle lath martensite in the coarse-grained heat-affected zone (CGHAZ) of the bottom layer into tougher tempered martensite/bainite in the CGHAZ of the upper layers. As a result, the hardness uniformity within the HAZ, the critical weak region of the joint, was enhanced by 54%, enabling synchronous improvement in microstructural homogeneity, hardness distribution, and overall welding efficiency. Full article

The growing need for lightweight, multifunctional, and high-performance structures in the automotive, aerospace, electronics, and medical industries has driven the development of advanced joining technologies for polymers and metal-polymer combinations. Among these, ultrasonic welding (USW) and friction stir spot welding (FSSW) have emerged as promising solid-state techniques capable of producing reliable joints with minimal thermal degradation and enhanced interfacial bonding. This review focuses on recent developments in USW and FSSW of thermoplastics, fiber-reinforced composites, and hybrid metal–polymer systems, with a particular emphasis on process mechanics, microstructural evolution, and joint performance. The mechanisms of heat generation, material flow behavior, and consolidation are discussed in relation to key process parameters, including applied pressure, rotational speed, vibration amplitude, plunge depth, and dwell time. Microstructural transformations such as polymer chain orientation, recrystallization, interfacial diffusion, and defect formation are analyzed to establish process–structure–property relationships. Mechanical performance metrics, including lap shear strength, fatigue resistance, impact behavior, and environmental durability, are critically compared across different materials and welding methods. Furthermore, recent advances in numerical and thermo-mechanical modeling, in situ process monitoring, and data-driven optimization are discussed to highlight pathways toward predictive and scalable manufacturing. Current industrial applications and existing limitations such as challenges in automation, thickness constraints, and hybrid material compatibility are also evaluated. Finally, key research gaps and future directions are identified to improve joint reliability, sustainability, and broader industrial adoption of advanced solid-state welding technologies. Full article

Background/Objectives: The medial meniscus is crucial for load transmission and knee stability. Meniscal tears disrupt joint biomechanics, increasing the risk of cartilage degeneration. However, few studies have quantitatively compared how different tear types affect stress and contact mechanics using finite element analysis (FEA). This study aims to analyze stress distributions for various meniscal tear types and develop a predictive model for meniscal stress behavior. This study investigates how stress distributions differ between healthy and torn medial menisci under identical loading conditions. The study examines which meniscal tear type produces the highest stress concentrations. The effects of different tear types on penetration, gap formation, pressure distribution, and sliding distance at the meniscus interface are also analysed. Materials and Methods: The FEA model of the knee joint, including femoral and tibial cartilage and the medial meniscus, was developed. Simulations were conducted for a healthy meniscus and for menisci with radial, horizontal and complex tears. Stress, penetration, gap, pressure, and sliding distance were calculated, and a mathematical model describing their relationships was established. Results: All torn menisci exhibited significantly higher stresses than the healthy meniscus (p < 0.001). Radial tears generated the highest stress concentrations (p < 0.001). Pressure was mainly influenced by meniscal geometry, while the gap remained nearly constant. Penetration increased slightly (p < 0.05). The predictive model demonstrated a strong correlation between meniscal stress and interface parameters (R² > 0.9). In a healthy meniscus, stress distribution is homogeneous (≈26 MPa). Stress concentration increases depending on the tear type: limited in a horizontal tear (≈26.5 MPa), significant in a vertical tear (≈30.8 MPa), and highest in a radial tear (≈40.6 MPa). These results indicate that as the tear progresses, the load-bearing capacity of the meniscus decreases, and stresses concentrate at the tear edges. Conclusions: Meniscal tears, especially radial ones, substantially alter knee biomechanics and elevate tissue stress. These biomechanical insights highlight the importance of early diagnosis and targeted rehabilitation strategies to prevent further cartilage damage and osteoarthritis progression. Full article

In the field of orthopedic surgery, particularly distraction osteogenesis (DO), the mechanical environment plays a decisive role in the quality of bone regeneration and the safety of the soft tissue envelope. The continuous monitoring and accurate prediction of distraction resisting forces (DRF) are critical for preventing soft tissue complications such as nerve ischemia, joint contractures, and mechanical failure of the lengthening device. However, current clinical practice relies heavily on subjective assessment or passive monitoring tools that lack predictive capabilities. To address this gap, this study proposes a comprehensive solution combining a custom mechanical acquisition system with a high-fidelity finite element (FE) prediction method. The system design features a novel “double-ring” sensor interface specifically engineered to decouple axial distraction forces from parasitic bending moments generated by asymmetric muscle tension. Furthermore, a patient-specific FE model utilizing the Ogden hyperelastic constitutive law was derived, explicitly based on the patient’s muscle volume from preoperative CT imaging, to predict the non-linear force evolution. The feasibility and accuracy of the system were validated in a pilot in vivo study using a single ovine model ($N=1$). To isolate the soft tissue resistance from callus formation, distraction was performed immediately postoperatively up to a total length of 4 cm. Experimental results demonstrated the system’s high linearity ($R^2>0.999$) and its ability to capture the characteristic viscoelastic relaxation of living tissues. The FE model successfully predicted the peak distraction forces, showing improved agreement with experimental data at larger distraction magnitudes. By integrating mechanical sensing with predictive modeling, this framework lays the foundation for future closed-loop, patient-specific control in distraction osteogenesis. Full article

Accurate object detection in underwater environments is severely challenged by light attenuation, wavelength-dependent color distortion, and scattering-induced turbidity, which create a substantial domain gap between terrestrial and underwater imagery. Conventional Generative Adversarial Network(GAN)-based translation models, such as CycleGAN, attempt to mitigate this gap but often suffer from instability and unrealistic color shifts due to their black-box design. To address these limitations, we propose JTA-GAN (Joint Turbidity–Attenuation GAN), a physics-informed generative framework that explicitly disentangles underwater image formation into scene radiance (J, derived from the physical imaging model), transmission (T), and ambient light (A). By enforcing a simplified physical imaging model within the generator architecture, JTA-GAN enables spatially coherent haze and attenuation synthesis without requiring ground-truth depth supervision. An asymmetric architecture stabilizes reverse mapping, while Learned Perceptual Image Patch Similarity(LPIPS)-based perceptual loss further improves reconstruction realism. Using the JTA-GAN network, we generated 65,153 physically plausible synthetic images for training You Only Look Once(YOLO)-based detectors. Evaluation on the SUIM benchmark demonstrates consistent performance improvements; specifically, YOLOv8s trained with synthetic data from JTA-GAN achieves 17.3% mAP(mean Average Precision), outperforming the land-only baseline (13.2%) and CycleGAN-based augmentation (10.8%). These results confirm that physics-informed generative modeling provides a theoretically grounded and effective solution for underwater domain adaptation under the high-turbidity and low-light conditions represented in the study. Full article

Friction stir welding (FSW) of high-strength aluminum alloys, including EN AW 7020-T651, encounters significant challenges under weld line gap conditions, leading to compromised joint integrity. This study develops a predictive, data-driven framework to assess and optimize the gap bridgeability performance of FSW joints with weld line gaps ranging from 0 to 4 mm in 2 mm thick plates. A structured experimental matrix was implemented, systematically varying rotational speed, welding speed, axial force, and tool shoulder diameter. To promote stable material flow and consistent weld quality under varying gap conditions, a multi-pin tool was employed throughout the welding trials. This configuration supported defect-free weld formation across a broad process window and contributed to improved weld soundness under gap conditions. Weld quality was evaluated using a comprehensive, multi-criteria approach that required (i) defect-free joints verified by visual and cross-sectional (metallographic) inspection, (ii) an ultimate tensile strength of at least 230 MPa, and (iii) a novel metric termed weak area percentage (WAP). Derived from micro-hardness mapping, WAP quantified the proportion of the heat-affected zone (HAZ) exhibiting hardness below 96 HV, providing a more robust and spatially sensitive measure of mechanical integrity than conventional average hardness values. Two machine learning models, Logistic Regression and Random Forest, were trained to classify weld acceptability. The Random Forest model demonstrated superior performance, achieving 92.5% classification accuracy and an F1-score of 0.90. Feature importance analysis identified the interaction terms “welding speed × gap size” and “rotational speed × gap size” as the most influential predictors of weld quality. Full article

Sea fog is a major meteorological hazard that severely disrupts maritime transportation and economic activities in the South China Sea. As China’s next-generation geostationary meteorological satellite, Fengyun-4B (FY-4B) supplies continuous observations that are well suited for sea fog monitoring, yet a satellite-specific recognition method has been lacking. A key obstacle is the radiometric inconsistency between the Advanced Geostationary Radiation Imager (AGRI) sensors on FY-4A and FY-4B, compounded by the cessation of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) observations, which prevents direct transfer of fog labels. To address these challenges and fill this research gap, we propose a machine learning framework that integrates cross-satellite radiometric recalibration and physical mechanism constraints for robust daytime sea fog detection. First, we innovatively apply a radiation recalibration transfer technique based on the radiative transfer model to normalize FY-4A/B radiances and, together with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud/fog classification products and ERA5 reanalysis, construct a highly consistent joint training set of FY-4A/B for the winter-spring seasons since 2019. Secondly, to enhance the model’s physical performance, we incorporate key physical parameters related to the sea fog formation process (such as temperature inversion, near-surface humidity, and wind field characteristics) as physical constraints, and combine them with multispectral channel sensitivity and the brightness temperature (BT) standard deviation that characterizes texture smoothness, resulting in an optimized 13-dimensional feature matrix. Using this, we optimize the sea fog recognition model parameters of decision tree (DT), random forest (RF), and support vector machine (SVM) with grid search and particle swarm optimization (PSO) algorithms. The validation results show that the RF model outperforms others with the highest overall classification accuracy (0.91) and probability of detection (POD, 0.81) that surpasses prior FY-4A-based work for the South China Sea (POD 0.71–0.76). More importantly, this study demonstrates that the proposed FY-4B framework provides reliable technical support for operational, continuous sea fog monitoring over the South China Sea. Full article

Understanding the strain rate behavior of rock materials is key to geomechanical engineering. However, in numerical tools such as the Particle Flow Code (PFC), the chosen bonded-particle contact model also fundamentally dictates the mechanical response. A systematic comparison of how quasi-static strain rates affect different contact models, Parallel-Bonded (PBM), Soft-Bonded (SBM), and Flat-Jointed (FJM), using a common calibration baseline, has been lacking. This study addresses that gap by first calibrating all three models against identical laboratory data from the siltstone of Paleozoic-aged Trakya formation in Cebeciköy-Istanbul, Türkiye. Subsequently, numerical uniaxial loading simulations were conducted on the calibrated models at three distinct quasi-static strain rates (0.01, 0.005, and 0.001 s⁻¹) to compare their stress–strain response, crack evolution, and failure patterns. The results demonstrate that while the initial elastic stiffness was largely insensitive to the applied strain rates across all models, the post-peak behavior and failure mechanism remained fundamentally distinct and model dependent. PBM consistently produced an abrupt, localized brittle failure, SBM exhibited more gradual softening with distributed tensile damage, and FJM displayed the most widespread, mixed-mode failure pattern. It is concluded that within the quasi-static loading conditions, the intrinsic formulation of the chosen contact model is a more dominant factor in controlling the failure style, damage localization, and post-peak characteristics than the specific strain rate applied. Full article

During active brazing of alumina ceramics, active elements react with the ceramic to form a reaction layer, which has significant influence on the mechanical property of the brazed joint. However, the composition and formation mechanism of this layer remain unclear among researchers. To fill this gap, different brazing temperatures (900–1100 °C) and heating rates (2.5 °C/min and 10 °C/min) were used to braze 95% Al₂O₃ ceramics and a Kovar 4J34 alloy using a Ag-Cu-2Ti active brazing filler, and the microstructure and mechanical properties of the joints were investigated. The results show that the joint could be divided into five layers: Al₂O₃, ceramic-side reaction layer, filler layer, Kovar-side reaction layer, and Kovar. The ceramic-side reaction layer could be further divided into a Ti-O-rich layer and an intermetallics (IMC)-rich layer, and the Kovar-side reaction layer consists of TiFe₂ particles, Ag-Cu eutectic, and the remaining Kovar. A belt-like TiFe₂+TiNi₃ IMC could be found in the filler layer. Increasing the brazing temperature enlarged the belt-like TiFe₂+TiNi₃ IMC in the filler layer and increased the thickness of the IMC-rich layer in the ceramic-side reaction layer, but had no significant effect on the thickness of the Ti-O-rich layer in the ceramic-side reaction layer. A lower heating rate (2.5 °C/min) was found to suppress the formation of the IMC-rich layer and shift the fracture location in shear tests from the ceramic-side reaction layer to the filler layer, indicating that the strength of the ceramic-side reaction layer was enhanced by controlling the formation of the IMC-rich layer. A maximum shear strength of 170 ± 61 MPa was obtained at a heating rate of 2.5 °C/min and a brazing temperature of 940 °C. Full article

Direct copper-plated ceramic (DPC) substrates have emerged as a favored solution for power device packaging due to their unique technical advantages. AuSn, characterized by its high hermeticity and environmental adaptability, represents the optimal sealing technology for DPC substrates. Through the application of vacuum sintering techniques and adjustment of peak temperatures (325 °C, 340 °C, and 355 °C), the morphology and composition of interfacial compounds were systematically investigated, along with an analysis of their formation mechanisms. A gradient aging experiment was designed (125 °C/150 °C/175 °C × oxygen/argon dual atmosphere × 600 h) to elucidate the synergistic effects of environmental temperature and atmosphere on the growth of intermetallic compounds (IMCs). The results indicate that the primary reaction in the sealing weld seam involves Ni interacting with Au-Sn to form (Ni, Au)₃Sn₂ and Au₅Sn. However, upon completion of the sealing process, this reaction remains incomplete, leading to a coexistence state of (Ni, Au)₃Sn₂, Au₅Sn, and AuSn. Additionally, Ni diffuses into the weld seam center via dendritic fracture and locally forms secondary phases such as δ(Ni) and ζ’(Ni). These findings suggest that the weld seam interface exhibits a complex, irregular, and asymmetric microstructure comprising multiple coexisting compounds. It was determined that Tpeak = 325 °C to 340 °C represents the ideal welding temperature range, where the weld seam morphology, width, and Ni diffusion degree achieve optimal states, ensuring excellent device hermeticity. Aging studies further demonstrate that IMC growth remains within controllable limits. These findings address critical gaps in the understanding of the microstructural evolution and interface characteristics of asymmetric welded joints formed by multi-material systems. Full article

This study joins a 20 mm thick 5000-series aluminum alloy using hot-wire insertion combined with narrow-gap laser welding to evaluate the feasibility and welding characteristics of this technique. The findings indicate that weld formation is primarily influenced by the laser energy density and material deposition rate. A strategy for improving weld beads is introduced incorporating a reoriented laser spot during the final pass on narrow-gap joints. This approach improves penetration and produces defect-free joints. The optimal processing conditions result in complete joint formation with four welding passes. Microstructural analysis reveals that the aluminum matrix morphology evolves according to the local thermal history during welding. Measurements show that the weld region is slightly harder than the base metal, whereas slightly lower hardness is observed at the fusion line and inter-pass boundaries, which correlates with the microstructure result. Full article

Prefabricated components inevitably generate numerous assembly joints during installation, with each 1 mm increase in joint width correlating to a 15–20% elevation in the annual occurrence frequency of the frost formation risk. In the Inner Mongolia Region, the water migration at wall connection interfaces during winter significantly exacerbates freeze–thaw damage due to persistent thermal gradients. A coupled heat–moisture transfer model incorporating gas–liquid–solid phase transitions was developed, with the liquid moisture content and temperature gradient as dual driving forces. A validation against internationally recognized BS EN 15026:2007 benchmark cases confirmed the model robustness. The prefabricated sandwich insulation walls reconstructed with region-specific volcanic ash materials underwent a comparative evaluation of temperature and relative humidity distributions under varied winter conditions. Furthermore, we analyze and assess the potential for freezing at connection points and identify the specific areas at risk. Synergistic effects between assembly gaps and indoor–outdoor environmental interactions on wall performance degradation were systematically assessed. The results indicated that, across all working conditions, both the temperature and relative humidity at each wall measurement point underwent periodic variations influenced by the outdoor environment. These fluctuations decreased in amplitude from the exterior to the interior, accompanied by a noticeable delay effect. Specifically, at Section 2, the wall temperatures at points B2–B8 were higher compared to those at A2–A8 of Section 1. The relative humidity gradient remained relatively stable at each measurement point, while the temperature fluctuation amplitude was smaller by 2.58 ± 0.3 °C compared to Section 1. Under subfreezing conditions, Section 1 demonstrates a marked reduction in relative humidity (Cases 1-3 and 2-3) compared to reference cases, which is indicative of internal ice crystallization. Conversely, Section 2 maintains higher relative humidity values under identical therma. These findings suggest that prefabricated building joints significantly impact indoor and outdoor wall temperatures, potentially increasing the indoor heat loss and accelerating temperature transfer during winter. Full article

Reasonable welding methods are of great significance for optimizing the microstructure and ensuring the mechanical properties of welded joints. In this study, ultra-narrow gap welding (UNGW) and submerged arc welding (SAW) were employed to weld Q355E high-strength low-alloy (HSLA) steel thick plates, and the microstructure and mechanical properties of the welded joints were systematically characterized. The UNGW welded joint exhibits superior comprehensive mechanical properties: a room-temperature tensile strength of 664 MPa with 43.1% elongation at fracture, along with higher microhardness and enhanced impact performance at −40 °C, all of which significantly outperform SAW welded joints. This advantage primarily stems from the faster cooling rate during UNGW, which promotes the formation of beneficial acicular ferrite in the joint microstructure. This study provides theoretical support and technical guidance for welding HSLA steel thick plates. Full article

Magnetic pulse welding (MPW) is a promising solid-state joining process that utilizes electromagnetic forces to create high-speed, impact-like collisions between two metal components. This welding technique is widely known for its ability to join dissimilar metals, including aluminum, steel, and copper, without the need for additional filler materials or fluxes. MPW offers several advantages, such as minimal heat input, no distortion or warping, and excellent joint strength and integrity. The process is highly efficient, with welding times typically ranging from microseconds to milliseconds, making it suitable for high-volume production applications in sectors including automotive, aerospace, electronics, and various other industries where strong and reliable joints are required. It provides a cost-effective solution for joining lightweight materials, reducing weight and improving fuel efficiency in transportation systems. This contribution concerns an application for the automotive sector (body-in-white) and specifically examines the welding of AA6082-T6 aluminum alloy with HC420LA cold-rolled micro-alloyed steel. One of the main aspects for MPW optimization is the determination of the process window that does not depend on the equipment used but rather on the parameters associated with the physical mechanisms of the process. It was demonstrated that process windows based on contact angle versus output voltage diagrams can be of interest for production use for a given component (shock absorbers, suspension struts, chassis components, instrument panel beams, next-generation crash boxes, etc.). The process window based on impact pressures versus impact velocity for different impact angles, in addition to not depending on the equipment, allows highlighting other factors such as the pressure welding threshold for different temperatures in the impact zone, critical transition speeds for straight or wavy interface formation, and the jetting/no jetting effect transition. Experimental results demonstrated that optimal welding conditions are achieved with impact velocities between 900 and 1200 m/s, impact pressures of 3000–4000 MPa, and impact angles ranging from 18–35°. These conditions correspond to optimal technological parameters including gaps of 1.5–2 mm and output voltages between 7.5 and 8.5 kV. Successful welds require mean energy values above 20 kJ and weld specific energy values exceeding 150 kJ/m². The study establishes critical failure thresholds: welds consistently failed when gap distances exceeded 3 mm, output voltage dropped below 5.5 kV, or impact pressures fell below 2000 MPa. To determine these impact parameters, relationships based on Buckingham’s π theorem provide a viable solution closely aligned with experimental reality. Additionally, shear tests were conducted to determine weld cohesion, enabling the integration of mechanical resistance isovalues into the process window. The findings reveal an inverse relationship between impact angle and weld specific energy, with higher impact velocities producing thicker intermetallic compounds (IMCs), emphasizing the need for careful parameter optimization to balance weld strength and IMC formation. Full article

K417G superalloy is widely applied in gas turbine components such as blades, vanes, and nozzles. In this work, the oxidation behavior and mechanism of K417G alloy prepared by wide-gap brazing were investigated in air at 800, 900, 1000, and 1100 °C. Microstructures of the bonded joints differ in the wide-gap braze region (WGBR) and base metal (BM). The surface and cross-sectional morphology, composition, and structure of specimens were analyzed by XRD, SEM, and EDS after oxidation tests. The experimental data demonstrate that the WGBR (wide-gap brazed region) exhibits markedly superior oxidation resistance compared to the BM (base material) under elevated-temperature conditions exceeding 1000 °C. This performance disparity is quantitatively validated by oxidation kinetics analysis, where the weight gain curve of the WGBR demonstrates parabolic oxidation kinetics, as evidenced by its significantly lower parabolic rate constant relative to the BM. The oxide layers of the BM and WGBR are similar after oxidation at high temperatures of 800–900 °C, and they consist of an outermost layer of NiO, a middle mixed layer of Cr₂O₃, and an innermost layer of dendritic Al₂O₃. However, when the temperature is between 1000 and 1100 °C, the NiO on the surface of the BM spalls of due to thermal expansion coefficient mismatch in coarse-grained regions, resulting in oxidation mainly divided into outer layer Cr₂O₃ and inner layer Al₂O₃ and TiO₂. Under high-temperature oxidation conditions (1000–1100 °C), a structural transition occurs in the oxide scale of the BM, with the underlying mechanism attributable to grain-coarsening-induced oxide scale destabilization. Specifically, the coarse-grained structure of the BM (characteristic grain size exceeding 50 μm) is exhibited. Therefore, the WGBR demonstrates outstanding oxidation resistance, as evidenced by the formation of a continuous Al₂O₃ scale with parabolic rate constants of about 1.38 × 10⁻³ mg²·cm⁻⁴·min⁻¹ at 1100 °C. Full article