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Deep learning-based thermal motion estimation and lay-up reconstruction framework towards machine-independent real-time AFP process monitoring and inspection
No full textAutomated Fiber Placement (AFP) continues to advance composite manufacturing, yet real-world throughput and quality assurance remain constrained by labor-intensive inspection and the absence of automated, in-situ monitoring solutions. Existing methods are partial–confined to local, frame-level analysis lacking global motion context required for comprehensive lay-up inspection, or reliant on machine-coupled data that introduces synchronization errors and hinders generalizability. We present a novel, machine-independent framework for real-time, motion-aware AFP monitoring and inspection. We introduce ThermoRAFT-AFP, a custom deep learning-based motion estimation core, tailored with AFP-specific augmentations and process-aware runtime optimizations to enable stable and precise thermal flow tracking. These estimates power a two-stage reconstruction pipeline that first stitches course-wise thermal mosaics, then assembles them into ply-level, high-fidelity, and interpretable laminate visualizations–recovering global motion context. We validate the framework on a large-scale, diverse AFP thermal dataset comprising over 13,000 frames with varying lay-up conditions, speed profiles, and defect types. A comprehensive analysis of motion accuracy, runtime efficiency, and deployment robustness shows that ThermoRAFT-AFP achieves state-of-the-art subpixel accuracy with a mean RMSE below 5 mm/s and relative cumulative drift under 0.1%, all while operating at 25 fps on a commodity CPU. The system maintains robust performance under severe thermal noise and reliably generalizes across diverse process conditions. Qualitative evaluation against realistic AFP case studies highlights the framework's capabilities for thermal anomaly visualization and tracking, inter-layer thermal behavior propagation analysis, and enabling operator-informed decision-making. These findings establish a reliable foundation for next-generation intelligent AFP process monitoring and quality inspection systems
Role of catalyst layer composition in the degradation of low platinum-loaded proton exchange membrane fuel cell cathodes: an experimental analysis
No full textThis study investigates the impact of catalyst layer (CL) composition on the performance and durability of proton exchange membrane fuel cells (PEMFCs). Membrane electrode assemblies (MEAs) are manufactured using six different cathode CLs (CCLs) by varying the platinum (Pt)-loading, Pt-to-carbon weight percentages (Pt/C wt.%), mass fraction of bare carbon particles, carbon support material, and CL thicknesses. Each MEA is subjected to comprehensive electrochemical characterization procedures followed by one of the two different accelerated stress tests (ASTs) to analyze the impacts of Pt-dissolution and carbon corrosion degradation mechanisms separately. Experimental results show that the Pt/C wt.% and CL thickness have a dominant role in the rate of Pt-dissolution. While the addition of bare carbon particles decreases the rate of Pt-dissolution degradation, lower Pt/C wt.% causes higher performance loss. The carbon corrosion degradation is more pronounced in high Pt-loaded CLs since Pt particles catalyze the carbon oxidation reaction, whereas for constant Pt-loaded CLs, higher Pt utilization leads to increased degradation and CCL thinning, as observed through post-mortem scanning electron microscopy (SEM). No significant relation is found between the carbon corrosion rate and the CL thickness
A novel inverse method for advanced monitoring of lubrication conditions in sliding bearings through adaptive genetic algorithm
No full textThis study introduces an inverse lubrication analysis (ILA) method, a novel approach for simulating the lubrication state of sliding bearings under various load conditions. By integrating experimental pressure data from sliding bearings with an adaptive genetic optimization algorithm, this method precisely calculates the eccentricity, attitude angle, and global pressure distribution of the lubrication film. Unlike traditional forward lubrication analysis (FLA) methods, which indirectly estimate the lubrication film status through loads, the ILA method utilizes direct pressure measurements, ensuring accurate and timely raw data for inverse calculations. This approach rapidly and accurately converts measured data into key parameters, closely aligning simulation results with experimental data. The lubrication states of the experimental sliding bearing under loads of 100 N, 200 N, 300 N, and 400 N were successfully predicted, highlighting the method's reliability in real-world applications. This study provides a new approach and perspective for health monitoring and fault diagnosis of sliding bearings, especially under extreme conditions
Annealing impact on mechanical performance and failure analysis assisted with acoustic inspection of carbon fiber reinforced poly-ether-ketone-ketone composites under flexural and compressive loads
No full textThis study investigates the effect of the annealing treatment for carbon fiber reinforced Polyether-ketone-ketone (CF/PEKK) composite structures under flexural and compressive loadings through reference, pre-damaged, and annealed sample sets. Significant recovery of pre-existing damage is observed after the annealing process, following both flexural and compressive loading. Acoustic emission (AE) inspection is employed to monitor the failure behavior and assess the impact of pre-damage and annealing on CF/PEKK composite. Initially, AE inspection reveals that the reference CF/PEKK material exhibits a notable fiber-related failure with 85% of cumulative AE counts under flexural load, whereas matrix-related failures are more pronounced with 92% cumulative AE counts under compressive load. Pre-damages in the matrix alter the cumulative count percentages and initiation time that are related to matrix, interface, and fiber-related failures, under flexural and compressive loadings. After annealing, each cumulative AE count percentages are comparable to reference sample values, due to changes in microstructure and relieving of residual stresses. The annealing effect is further validated through dynamic scanning calorimetry (DSC) analysis results with increased glass transition temperature (Tg) and degree of crystallization (Xc). Overall, these findings indicate that annealing treatment effectively restores structural integrity and improves the mechanical performance of CF/PEKK composites. Highlights: Annealing aims for damage recovery in CF/PEKK under flexural and compressive loads. Significant damage recovery in CF/PEKK is seen after annealing. Annealing raises Tg and crystallinity, and enhances CF/PEKK structural integrity
Ameliorating tensile and fracture performance of carbon fiber-epoxy composites via atmospheric plasma activation: insights into damage modes through in-situ acoustic emission inspection
No full textCarbon fiber-reinforced epoxy composites may suffer from poor interfacial bonding, which negatively affects their mechanical performance and reliability in demanding applications. This study investigates the effect of atmospheric plasma activation (APA) on enhancing fiber–matrix adhesion, focusing on the systematic influence of APA exposure duration. The results show that APA-treated composites exhibit a significant increase in tensile strength (up to 13.5%) and mode-I and mode-II fracture toughness (up to 53% and 44%, respectively) compared to untreated (NT) specimens. Additionally, in-situ Acoustic Emission (AE) monitoring during mechanical tests enables real-time insights into damage initiation and progression. APA-treated composites display a notable shift in damage mechanisms, with delamination emerging as the dominant failure mode, unlike the fiber pull-out observed in NT specimens under tensile loading. AE analysis indicates enhanced interfacial adhesion in treated specimens, evidenced by delayed damage initiation and increased fracture resistance. Furthermore, scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) analyses confirm respectively enhanced surface roughness and the presence of oxygen-functional groups, contributing to stronger interfacial bonding. These findings suggest that fabric treatment via APA is an effective and eco-friendly approach for improving the mechanical performance of carbon fiber-reinforced composites, thereby lending itself to advanced engineering applications
Microstructural effects of melt electrowritten-reinforced hydrogel scaffolds for engineering thick skin substitutes
No full textEngineering thick skin tissue substitutes resembling the physiochemical and mechanical properties of native tissue is a significant challenge. Melt electrowriting (MEW) is a powerful technique with the capability of fabricating highly ordered structures with fine fiber diameters, closely replicating the native extracellular matrix (ECM). In this study, we constructed melt electrowritten porous polycaprolactone (PCL) scaffolds with three different geometries by depositing fibers at 0-90 and 60-120° in a mesh structure and in a honeycomb-like orientation to assess the effects of the microstructure on the mechanical strength of the scaffold and cellular behavior. These scaffolds were subsequently infilled with gelatin hydrogel, encapsulating human skin dermal fibroblasts (HSFs) and human umbilical vein endothelial cells (HUVECs). Mechanical tensile tests revealed that the honeycomb microstructure of the hybrid PCL/gelatin scaffold exhibited greater elongation at failure, along with an acceptable elastic modulus suitable for skin tissue applications. All scaffolds provided a cytocompatible microenvironment that maintained over 90% cell viability and preserved typical cell morphology. HSFs were guided through the PCL fibers to the apical surface, while HUVECs were distributed within the gelatin hydrogel within the hybrid structure. Additionally, HSFs’ alignment was regulated by the scaffold geometry. Notably, the expression of CD31 in HUVECs─a key transmembrane protein for capillary formation─increased significantly over a 14 day incubation period. Among those, 0-90° mesh and honeycomb geometries showed the greatest effects on the upregulation of CD31. These findings demonstrate that the microstructural guidance of HSFs and their interaction with HUVECs in hybrid structures play a crucial role in promoting vascularization. In conclusion, the honeycomb MEW-gelatin hybrid scaffold demonstrates significant potential for effectively replicating both the mechanical and physicochemical properties essential for full-thickness skin tissue substitutes
Curves with many rational points via Atkin-Lehner involution
No full textIn this article, we use reductions of the Drinfeld modular curves X0(n) to obtain curves over finite fields Fq of a given genus with many Fq-rational points. The main idea is to divide the Drinfeld modular curves by an Atkin–Lehner involution, which has many fixed points to obtain a quotient with a better #{rational points}genus ratio. If we divide the Drinfeld modular curve X0(n) by an involution W, then the number of rational points of the quotient curve W\X0(n) is not less than half of the original number. On the other hand, if this involution has many fixed points, then by the Hurwitz genus formula, the genus of the curve W\X0(n) is much less than half of the g(X0(n))
A thermodynamic cycle to predict the competitive inhibition outcomes of an evolving enzyme
No full textUnderstanding competitive inhibition at the molecular level is essential for unraveling the dynamics of enzyme-inhibitor interactions and predicting the evolutionary outcomes of resistance mutations. In this study, we present a framework linking competitive inhibition to alchemical free energy perturbation (FEP) calculations, focusing on Escherichia coli dihydrofolate reductase (DHFR) and its inhibition by trimethoprim (TMP). Using thermodynamic cycles, we relate experimentally measured binding constants (Ki and Km) to free energy differences associated with wild-type and mutant forms of DHFR with a mean error of 0.9 kcal/mol, providing insight into the molecular underpinnings of TMP resistance. Our findings highlight the importance of local conformational dynamics in competitive inhibition. Mutations in DHFR affect substrate and inhibitor binding affinities differently, influencing the fitness landscape under selective pressure from TMP. Our FEP simulations reveal that resistance mutations stabilize inhibitor-bound or substrate-bound states through specific structural and/or dynamical effects. The interplay of these effects showcases significant molecular-level epistasis in certain cases. The ability to separately assess substrate and inhibitor binding provides valuable insights, allowing for a more precise interpretation of mutation effects and epistatic interactions. Furthermore, we identify key challenges in FEP simulations, including convergence issues arising from charge-changing mutations and long-range allosteric effects. By integrating computational and experimental data, we provide an effective approach for predicting the functional impact of resistance mutations and their contributions to evolutionary fitness landscapes. These insights pave the way for constructing robust mutational scanning protocols and designing more effective therapeutic strategies against resistant bacterial strains
Effect of reduced-order modelling on passivity and rendering performance analyses of series elastic actuation
No full textWe study reduced-order models of series elastic actuation under velocity-sourced impedance control, where the inner motion controller is assumed to render the system into an ideal motion source within a control bandwidth and replaced by a low-pass filter. We present necessary and sufficient conditions for the passivity of this system and prove that the passivity results obtained through the reduced-order model may violate the passivity of the full-order model. To enable safe use of the reduced-order model, we derive conditions under which the passivity bounds of the reduced-order model guarantee the passivity of the full-order system. Moreover, we synthesize passive physical equivalents of closed-loop systems while rendering Kelvin-Voigt, linear spring, and null impedance models to provide rigorous comparisons of the passivity bounds and rendering performance among the full-and reduced-order models. We verify our results through a comprehensive set of simulations and experiments