Search Results (282)

The correlation between fouling-driven corrosion and magnetic Barkhausen noise (MBN) in AH36 naval steel was investigated under real Mediterranean seawater conditions over a 12-month immersion period. A custom-designed MBN analyzer was used to monitor four MBN parameters at monthly intervals: RMS amplitude (MBN_RMS), peak amplitude (MBN_peak), peak field position (MBN_{peak pos.}), and full width at half maximum (MBN_FWHM). Complementary characterization included pit morphology analysis, X-ray diffraction (XRD) of corrosion products, and quantitative biofouling community profiling. Three distinct MBN evolution regimes were identified, corresponding to active pitting (T₀–T₃), transitional oxide formation (T₃–T₆), and mature corrosion equilibrium (T₆–T₁₂). Over the full exposure period, MBN_RMS decreased by 50.4% and MBN_{peak pos.} increased by 83.3%, consistent with domain wall pinning at pit stress concentrations and electromagnetic shielding by paramagnetic corrosion product layers (γ-FeOOH, β-FeOOH, α-FeOOH). Pearson correlation analysis revealed near-unity relationships between MBN_RMS and maximum pit depth (r = −0.982, p < 0.01), supporting its potential use as a quantitative non-destructive indicator of corrosion severity under comparable exposure conditions. Biofouling, particularly sulfate-reducing bacteria (SRB)-dominated communities and biogenic iron sulfides (mackinawite, greigite), was identified as a statistically significant secondary correlate of MBN signal intensity (r = −0.944 vs. SRB fraction). A composite diagnostic threshold of (MBN_RMS × MBN_peak)/MBN_FWHM ≈ 0.015 effectively discriminated active pitting from passive rusting. These findings provide a physically grounded framework for multiparametric MBN analysis as a non-destructive condition monitoring tool, with the caveat that the reported correlations are descriptive and require independent validation before deployment in regulatory inspection protocols. Full article

Dry electroencephalography (EEG) electrodes enable rapid, gel-free setups, which are crucial for point-of-care diagnostics, but often face challenges with comfort and signal quality—especially in a clinical context. Novel “flower” dry electrodes are a special type of reusable scalp electrodes for dry EEG, featuring a distinct flower-like shape with angled pins in three intertwined layers. While the new electrode design has been validated in an in vivo study on healthy volunteers, we tested its clinical applicability in a proof-of-concept study involving three patients diagnosed with epilepsy and delirium. The recordings were of high diagnostic quality, enabling the reliable identification of pathological patterns, such as generalized spike–wave complexes and intermittent delta activity, with a signal-to-noise ratio comparable to prior reports for sponge-based EEG systems (limited case series). The signal-to-noise ratio (SNR) proved to be sufficiently high for clinical diagnostic purposes, resulting in visually clear and interpretable EEG data that enabled effective assessment of patients’ neurophysiological signals. Consequently, our findings demonstrate that the comfortable flower-electrode design is a viable and effective tool for epilepsy diagnostics, extended recording, and clinical neurophysiology. It represents a significant step towards patient-centered and gel-free EEG technology, specifically in point-of-care and emergency applications, without compromising the diagnostic quality of the recordings. Full article

The complex flow behavior of the metal around the stirring tool during welding directly determines the microstructural evolution, defect formation, and mechanical properties of the welded joint, and thus becomes the core physical process affecting welding quality and process stability. In this study, to characterize the three-dimensional material flow behavior of AZ31 magnesium (Mg) alloy during friction stir welding (FSW), conventional metallographic sectioning was adopted as the primary observation method, and copper foil was used as the marker material. The flow trajectories of the materials after welding were investigated via three configurations of the marker material. The results indicate that three typical characteristic zones exist along the vertical direction, which are the shoulder-affected zone (SAZ), the pin-affected zone (PAZ), and the swirl zone from top to bottom. Specifically, the material in the SAZ is dominated by laminar flow; the PAZ exhibits complex mixed-flow characteristics; while the swirl zone shows an obvious rotational flow pattern. Based on the principles of material mechanics and fluid mechanics, a force-flow coupled “simple flow model around a rotating cylinder” was proposed, which defines three flow modes corresponding to the different characteristic zones within the weld. Full article

Background/Objectives: Human pythiosis, caused by Pythium insidiosum, is associated with severe morbidity and high mortality when diagnosis is delayed. Culture-based diagnosis is time-consuming and may be insensitive in clinical specimens, highlighting the need for rapid point-of-care serodiagnostic tools. Here, we developed and clinically evaluated the Anti-Pin Antibody Test Strip, a whole-blood-compatible lateral flow immunoassay (LFIA) for detecting anti-P. insidiosum antibodies. Methods: Secretory protein antigens of P. insidiosum were prepared and conjugated to gold nanoparticles for LFIA development. Analytical performance was assessed by determining the limit of detection (LOD) using serial dilutions of pythiosis serum and by evaluating cross-reactivity with sera from patients with other infections. Interference testing examined common anticoagulants and adverse sample conditions (hemolysis, lipidemia, and icterus). Clinical performance was evaluated using 258 serum samples, comprising 48 pythiosis-positive and 210 pythiosis-negative specimens confirmed by immunoblotting and/or culture. Test results were read at 5 min. Results: The assay LOD was a serum titer of 1:1000. No cross-reactivity was observed across the tested infectious and immunologic panels, and no interference was detected from anticoagulants or adverse sample conditions. Whole-blood testing showed no red blood cell interference. In clinical evaluation, sensitivity was 100.00% (48/48), specificity was 95.24% (200/210), and accuracy was 96.12%, with a PPV of 82.76% and an NPV of 100.00%. Conclusions: The Anti-Pin Antibody Test Strip provides rapid (5 min), operationally simple serodiagnosis and may support screening/triage of suspected pythiosis, particularly where laboratory methods are limited. Full article

Considering consumer health, consistency in processes, and developing trust among the public, food manufacturing facilities are expected to adhere to strict regulatory policies. Along with these expectations, machinery capabilities, especially considering reliability, maintainability, and hygienic designs, would play a significant role in delivering quality products and developing efficient processes. This paper focuses on a belt-style depositor machine, whose primary purpose is to deposit product pieces onto product passing below it. First, the key issues with the current machine are pinpointed. Next, alternative designs are provided aimed at testing, evaluating, and building belt-driven depositing machines. The original design experienced persistent belt tracking issues, frequent maintenance interruptions, and sanitation concerns due to its complex, heavy components. The project applied the Define, Measure, Analyze, Design, and Verify (DMADV) framework to test alternative belt configurations and implement improvements that significantly reduced maintenance time, improved tracking reliability, and enhanced hygienic design. Lab and real-world tests compared three prototypes, namely the V-Rib, Crowned Roller, and Pin Drive. The prototypes were compared against defined performance targets. The final system, built around a self-tracking V-Rib belt with modular components and reduced tool disassembly, demonstrated a 75% reduction in belt change time, and improved product consistency and compliance with sanitation standards. This redesign offers a replicable model for upgrading depositor systems across production lines. Full article

To reduce mold costs in composite forming, multi-point tooling technology has been integrated into the hot diaphragm forming process. However, this approach still faces several challenges, including time-consuming prepreg layup, high energy consumption, and poor surface quality. This study proposes a heating pad-assisted multi-point thermoforming process: the prepreg is embedded in the thermal functional layers, placed on the lower mold, and formed via the downward movement of the upper mold to accomplish mold closure. Instead of the conventional rectangular array, this study adopted multi-point tooling with a hexagonal pin arrangement. Compared to traditional configurations, this hexagonal layout increases the punch support area by 9.8%, while its dense punch arrangement improves the accuracy of the molded curved surface. Taking a saddle-shaped surface as the target, a prototype part was fabricated. Subsequent analysis of the part’s surface quality identified three defects: dimples, fiber distortion, and ridge protrusions. The surface dimples were eliminated by adjusting the distance between the upper and lower molds. Notably, ridge protrusion is a defect unique to the hexagonal pin arrangement. We conducted a detailed analysis of its causes and solutions, finding that this defect arises from the combined effect of the pin arrangement and the saddle-shaped surface. Through a series of height compensation experiments, the maximum deviation at the ridges was reduced from 0.46 mm to approximately 0.35 mm, which is consistent with the deviation of defect-free areas. This work demonstrates that the multi-point hot-pressing process provides a potential, efficient, and low-cost method for manufacturing double-curvature composite components, whose effectiveness has been verified through the saddle-shaped case study. Full article

Additive manufacturing (AM) is a significant contributor to Industry 4.0. However, one considerable challenge is usually encountered by AM due to the bed size limitations of 3D printers, which prevent them from being adopted. An appropriate post-joining technique should be employed to address this issue properly. This study investigates the influence of key friction stir butt welding (FSBW) factors (FSBWFs), such as tool rotational speed (TRS), tool traverse speed (TTS), and pin profile (PP), on the weldability of 3D-printed PLA–Chromium (PC) composites (3PPCC). A filament containing 10% by weight of chromium reinforced in PLA was used to prepare samples. The material extrusion additive manufacturing process (MEX) was employed to prepare the 3D-printed PCC. A Taguchi-based design of experiments (DOE) (L9 orthogonal array) was employed to systematically assess weld hardness (WH), weld temperature (WT), weld strength (WS), and weld efficiency. As far as the 3D-printed samples were concerned, two distinct infill patterns (linear and tri-hexagonal) were also examined to evaluate their effect on joint performance; however, all other 3D printing factors were kept constant. Experimentally validated findings revealed that weld efficiency varied significantly with PP and infill pattern, with the square PP and tri-hexagonal infill pattern yielding the highest weld efficiency, i.e., 108%, with the corresponding highest WS of 30 MPa. The conical PP resulted in reduced WS. Hardness analysis demonstrated that tri-hexagonal infill patterns exhibited superior hardness retention, i.e., 46.1%, as compared to that of linear infill patterns, i.e., 34%. The highest WTs observed with conical PP were 132 °C and 118 °C for both linear and tri-hexagonal infill patterns, which were far below the melting point of PLA. The lowest WT was evaluated to be 65 °C with a tri-hexagonal infill, which is approximately equal to the glass transition temperature of PLA. Microscopic analysis using a coordinate measuring machine (CMM) indicated that optimal weld zones featured minimal void formation, directly contributing to improved weld performance. In addition, scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) were also performed on four deliberately selected samples to examine the microstructural features and elemental distribution in the weld zones, providing deeper insight into the correlation between morphology, chemical composition, and weld performance. Full article

Automated anomaly detection in transportation infrastructure is essential for enhancing safety and reducing the operational costs associated with manual inspection protocols. This study presents an improved neuromorphic vision system, which extends the prior SIFT-SNN (scale-invariant feature transform–spiking neural network) proof-of-concept by incorporating temporal feature aggregation for context-aware and sequence-stable detection. Analysis of classical stitching-based pipelines exposed sensitivity to motion and lighting variations, motivating the proposed temporally smoothed neuromorphic design. SIFT keypoints are encoded into latency-based spike trains and classified using a leaky integrate-and-fire (LIF) spiking neural network implemented in PyTorch. Evaluated across three hardware configurations—an NVIDIA RTX 4060 GPU, an Intel i7 CPU, and a simulated Jetson Nano—the system achieved 92.3% accuracy and a macro F1 score of 91.0% under five-fold cross-validation. Inference latencies were measured at 9.5 ms, 26.1 ms, and ~48.3 ms per frame, respectively. Memory footprints were under 290 MB, and power consumption was estimated to be between 5 and 65 W. The classifier distinguishes between safe, partially dislodged, and fully dislodged barrier pins, which are critical failure modes for the Auckland Harbour Bridge’s Movable Concrete Barrier (MCB) system. Temporal smoothing further improves recall for ambiguous cases. By achieving a compact model size (2.9 MB), low-latency inference, and minimal power demands, the proposed framework offers a deployable, interpretable, and energy-efficient alternative to conventional CNN-based inspection tools. Future work will focus on exploring the generalisability and transferability of the work presented, additional input sources, and human–computer interaction paradigms for various deployment infrastructures and advancements. 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

During the extrusion of novel nickel-based powder superalloy bars, the die is subjected to elevated temperatures, high pressures, and severe friction, which readily lead to abrasive wear and thermal-fatigue damage. These failures deteriorate the quality of the extruded products and significantly shorten the service life of the die. Frequent repair and replacement of the tooling ultimately increase the overall manufacturing cost. This study investigates the friction and wear behavior of H13 and 5CrNiMo hot-work tool steels under extreme transient high-temperature conditions by combining finite element simulation with tribological testing. The temperature and stress distributions of the billet and key tooling components during extrusion were analyzed using DEFORM-3D. In addition, pin-on-disk friction and wear tests were conducted at 1000 °C to examine the friction coefficient, wear morphology, and subsurface grain structural evolution under various loading conditions. The results show that the extrusion die and die holder experience the highest loads and most severe wear during the extrusion process. For 5CrNiMo tool steel, the wear mechanism under low loads is dominated by mild abrasive wear and oxidative wear, whereas increasing the load causes a transition toward adhesive wear and severe oxidative wear. In contrast, H13 tool steel exhibits a transition from abrasive wear to severe oxidative wear. In 5CrNiMo steel, friction-induced recrystallization, grain refinement, and softening lead to the formation of a mechanically mixed layer, which, together with a stable third-body layer, markedly reduces and stabilizes the friction coefficient. H13 steel, however, undergoes surface strain localization and spalling, resulting in persistent fluctuations in the friction coefficient. The toughness and adhesion of the oxide film govern the differences in wear mechanisms between the two steels. Owing to its higher Cr, V, and Mo contents, H13 forms a dense but highly brittle oxide scale dominated by Cr and Fe oxides at 1000 °C. This oxide layer readily cracks and delaminates under frictional shear and thermal cycling. The repeated spalling exposes the fresh surface to further oxidation, accompanied by recurrent adhesion–delamination cycles. Consequently, the subsurface undergoes alternating intense shear and transient load variations, leading to localized dislocation accumulation and cracking, which suppresses the progression of continuous recrystallization. Full article

Friction stir spot welding (FSSW) is a novel variant of Friction Stir welding (FSW), developed by Mazda Motors and Kawasaki Heavy Industries to join similar and dissimilar materials in a solid state. It is an economic and environmentally friendly alternative to resistance spot welding (RSW). The FSSW technique, however, includes some structural defects imbedded within the weld joint, such as keyhole formation, hook crack, and bond line oxidation challenging the joint strength. The unique properties of nanomaterials in the reinforcement of metal matrices motivated researchers to enhance the FSSW joints’ strength. Previous studies successfully fabricated nano-reinforced FSSW joints. At different volumetric ratios of nano-reinforcement, nanoparticles may agglomerate due to inefficient stirring of the welding tool pin, forming stress concentration sites and brittle phases, affecting tensile and fatigue strength under static and cyclic loading conditions, respectively. This work investigated how the welding tool pin affects stirring efficiency by controlling the distribution of a nano-reinforcing material within the joint stir zone (SZ), and thus the tensile and fatigue strength of the FSSW joints. Sheets of AA6061-T6 of 1.8 mm thickness were used as a base material. In addition, graphene nanoplatelets (GNPs) with lateral sizes of 1–10 µm and thicknesses of 3–9 nm were used as nano-reinforcements. GNP-reinforced FSSW specimens were prepared and successfully fabricated. Optical microscope (OM) and field emission scanning electron microscope (FE-SEM) methods were employed to visualize the GNPs’ incorporation into the SZs of the FSSW joints. Micrographs of as-welded specimens showed lower formations of scattered, clustered GNPs achieved by the threaded pin tool compared to continuous agglomerations observed when the cylindrical pin tool was used. Tensile test results revealed a significant improvement of about 30% exhibited by the threaded pin tool compared to the cylindrical pin tool, while fatigue test showed an improvement of 46–24% for the low- and high-cycle fatigue, respectively. Full article

The paper presents the analysis of the influence of the location and characteristics of supports on the static response of two-layer beams. The possibility of tangential movement at the supports was considered. Multilayer beams, which combine the advantages of different materials, are widely used in construction. The authors’ previous research showed that the stiffness of the connection between layers significantly affects the behaviour of the system. This paper demonstrates that the supports’ position is another crucial factor that influences the beams’ response, which is an issue that has not been previously considered in the literature. A two-layer system was modelled using the Euler–Bernoulli beam theory. Consistent normal displacements and tangential forces at the layer interface, which were proportional to the relative slip, were assumed. From the equilibrium equations and considered assumptions, three coupled displacement equations were derived and then solved using finite Fourier transforms. They were applied to solve beams, the two ends of which cannot move in the direction perpendicular to the beam’s axis, with at least one of the beam ends being a pinned support. To verify the method’s accuracy, several numerical examples were analysed. It was shown that both the support position and the possibility of tangential displacement at the supports have a significant impact on the static response. Additionally, the crucial role of the stiffness of the interlayer connection was confirmed. The developed approach provides a practical tool for assessing two-layer beam systems and highlights the importance of considering support conditions in the design and analysis of such structures. Full article

This study examines the through-thickness microstructure and crystallographic texture evolution in friction-stir-welded (FSWed) AA5052-H32 and AA6061-T651 aluminum alloys using a tri-flats threaded pin tool. Optical microscopy and electron backscatter diffraction (EBSD) were employed to characterize grain morphology, boundary misorientation, and texture components across the weld thickness. Both alloys exhibited progressive grain refinement and increased high-angle grain boundary fractions from the top to the bottom of the stir zone due to combined thermal and strain gradients. The FSWed AA5052 displayed dominant {111}<110> and Y + γ fiber components at the upper and mid regions, whereas AA6061 showed more randomized textures. At the bottom region, both alloys developed rotated Goss {011}<01-1> and weak A ({112}<110>) and α fiber components. These results clarify how alloy strengthening mechanisms—solid-solution versus precipitation hardening—govern texture evolution under different strain-path and heat input conditions. The findings contribute to optimizing process parameters and material selection for structural-scale FSW aluminum joints in industrial applications such as bridge decks, transportation panels, and marine structures. Full article

This study proposes a novel framework for quantifying curved grain boundaries that overcomes key limitations of existing methods. Unlike Fourier-based approaches that require labor-intensive sequential analysis of individual boundaries and selectively represent only high-amplitude regions, or spline-based methods that demand complex parameter selection for interpolation points, the proposed framework integrates curvature variance filtering with U-chord curvature calculation to enable automated, comprehensive, and noise-resistant characterization of grain boundary morphology. The curvature variance filtering adaptively determines smoothing parameters based on local curve properties, while the U-chord curvature method ensures rotational invariance and robustness against digitization errors. Four heat treatment processes were applied to GH4169 alloy, producing distinct grain boundary morphologies with mean curvature (MC) values ranging from 0.0625 to 0.1252. Controlled cooling alone (Process A) yielded predominantly straight boundaries (91.06% straight, 0.12% serrated), while re-dissolution treatment (Process D) produced the highest serration degree (58.81% straight, 3.53% serrated). The quantitative analysis reveals that dispersed δ-phase precipitation creates discrete pinning points, forming serrated boundaries with sharp curvature peaks, whereas dense, parallel δ-phase arrays at specific angles produce coordinated wavy undulations. This framework provides a reliable quantitative tool for optimizing heat treatment protocols to achieve target grain boundary configurations in nickel-based superalloys. Full article

Modern weeding technologies include chemical weeding, non-contact methods such as laser weeding, and conventional mechanical inter-row cultivation characterized by soil loosening and weed uprooting. For maize, mechanical inter-row cultivation is key to cutting herbicide use and enhancing the soil–crop environment. This study developed a vision-guided intelligent inter-row cultivator with electric lateral shifting—its frame fabricated from Q235 low-carbon structural steel and assembled mainly via bolted and pinned joints—that computes real-time lateral deviation between the implement and crop rows through maize plant recognition and crop row fitting and uses delay compensation to command a servo-electric cylinder for precise ±15 cm inter-row adjustments corresponding to 30% of the 50 cm row spacing. To test the system’s dynamic response, 1–15 cm-commanded lateral displacements were evaluated at 0.31, 0.42, and 0.51 m/s to characterize the time-displacement response of the servo-electric shift mechanism; field tests were conducted at 0.51 m/s with three 30 m passes per maize growth stage to collect row-guidance error and root-injury data. Field results show that at an initial offset of 5 cm, the mean absolute error is 0.76–1.03 cm, and at 15 cm, the 95th percentile error is 7.5 cm. A root damage quantification method based on geometric overlap arc length was established, with rates rising with crop growth: 0.12% at the V2 to V3 stage, 1.46% at the V4 to V5 stage, and 9.61% at the V6 to V8 stage, making the V4 to V5 stage the optimal operating window. Compared with chemical weeding, the system requires no herbicide application, avoiding issues related to residues, drift, and resistance management. Compared with laser weeding, which requires high tool power density and has limited effective width, the tractor–implement system enables full-width weeding and shallow inter-row tillage in one pass, facilitating integration with existing mechanized operations. These results, obtained at a single forward speed of 0.51 m/s in one field and implement configuration, still require validation under higher speeds and broader field conditions; within this scope they support improving the precision of maize mechanical inter-row cultivation. Full article