Search Results (2,034)

To address the challenges of bedding separation and large deformation in deep gob-side roadways with composite roofs under the influence of stress deviation and weak interlayers, this study takes the 1692(1) rail roadway of Pansan Coal Mine as the research object. By combining numerical simulation, theoretical analysis, and field testing, the study thoroughly investigates the evolution patterns of the plastic zone in the surrounding rock and the mechanisms governing delamination. The results demonstrated that stress deviation induces shear failure of weak interlayers and causes bedding separation at the early excavation stage, which subsequently transforms into tensile failure and leads to coal pillar instability. The principal stress deviation angle determines the expansion direction of the plastic zone, while the thickness and number of weak interlayers are positively correlated with the degree of bedding separation. It is concluded that the coal pillar strength is a critical factor for bedding separation control. Based on these findings, a combined control scheme of “strengthening coal pillars, restraining shear damage, improving coordinated deformation” is proposed. Field engineering practice confirms that this proposed scheme effectively restrains the expansion of the plastic zone and ensures the long-term stability of the roadway. Full article

Polymer insulation layers such as polyimide (PI) have gradually replaced inorganic dielectric layers (SiO₂, SiCN) in the integrated packaging process of hybrid bonding (HB). PI can fill the gaps in the thermal compression bonding process and help to obtain a good Cu/Polymer bonding interface. At present, the existing post-crack double cantilever beam tensile test (PBC-DCB) has been successfully applied to the quantitative measurement of bonding strength of hybrid bonding with inorganic materials, but this method only considers elastic behavior. Since PI exhibits viscidity, elasticity and plasticity, knowing how to correlate these properties to the bonding process is challenging. Whether PBC-DCB is suitable for the characterization of PI bonding is unclear. This paper presents a comprehensive experimental and finite element analysis (FEA) study on the PI–PI bonding interface. Firstly, nanoindentation experiments and simulations are performed on the prepared PI interface to obtain key elasticity and plasticity parameters. Then, the bonding strength is characterized by the PBC-DCB test. Theoretical and experimental results show that the plasticity of PI causes energy dissipation during stretching, resulting in a deviation of approximately 2.51% compared with pure elasticity. Based on experimental data, the Cohesive Zone Model (CZM) FEA method is used to simulate the crack propagation. The results indicate that the Embedded Process Zone (EPZ) model can accurately describe crack initiation and delamination behavior, with a margin of error of about 3.61%. Finally, based on the EPZ CZM, defects such as bonding void and wafer warpage are further discussed in relation to bonding strength measurement. Full article

Composite laminates experience static and fatigue delamination, presenting significant challenges for failure prediction. This is critical in curved composites, where delamination behavior is complex to predict. In this study, fatigue tests were conducted on curved composite laminates under non-constant mixed-mode conditions. The testing setup involved a four-point bending test using L-shaped, unidirectional carbon-fiber-reinforced polymer curved beam specimens. A Teflon insert placed at the bend was used to initiate delamination. Experimental data acquisition included digital image correlation (DIC) to monitor delamination length during testing. This is important since it enhances subsequent model correlation. A virtual crack closure technique (VCCT)-based method for simulating fatigue-driven delamination under variable mixed-mode conditions was validated against experiments. Delamination growth was modeled using a Paris-like power–law relationship based on the strain energy release rate. The approach was implemented in Abaqus as a user subroutine, incorporating load ratio and mode mixity effects through VCCT-based mode separation. This study demonstrates accurate fatigue delamination prediction and highlights the role of optical measurements in experiments. The model improves our understanding of delamination propagation under varying mode mixity and contributes to structural integrity analysis. The results show how mode mixity influences delamination, impacting the performance and lifecycle of composite structures. Full article

Carbon fiber-reinforced polymer (CFRP) is extensively applied in aerospace and rail transportation industries, and the quality of CFRP joint holes is crucial for ensuring joint performance and service reliability. However, CFRP drilling involves complex interactions among drilling parameters, tool geometry, and multiple quality indicators, making it difficult to accurately predict drilling quality and identify optimal process parameters. In this study, drilling experiments using twist drills and dagger drills were conducted to analyze the relationships among drilling parameters, drilling physical indicators, and drilling quality indicators. Compared to the twist drill, the dagger drill maintained lower thrust force and cutting temperature, and reduced the delamination factor, burr factor, and drilling wall roughness by 20.6%, 95.5%, and 81.1% on average, respectively. To consider the effect of different drilling indicators on the quality of CFRP drilling holes, a comprehensive fuzzy evaluation prediction model FCE-NN for drilling quality was proposed. The average prediction accuracy reached 91.3% and the drilling indicators FCE were output. The NSGA-II algorithm was employed, and an entropy-weighted TOPSIS method integrated with fuzzy comprehensive evaluation (FCE) was used to rank the Pareto-optimal solutions, thereby achieving multi-objective optimization of the thrust factor, delamination factor, and machining efficiency. Full article

Accurate damage characterization in thermoset Carbon Fiber-Reinforced Polymer (CFRP) composites using Acoustic Emission (AE) requires statistically robust and interpretable models. This study employs multinomial logistic regression with forward selection and Type III analysis to identify the minimal set of AE parameters necessary for classifying damage mechanisms (fiber breaks, delamination, matrix cracks) in quasi-isotropic thermoset CFRP laminates under synchronously recorded load conditions. Starting from 18 conventional time- and frequency-domain descriptors, forward selection yielded seven candidate predictors. However, Type III analysis revealed that only four parameters, Load, Initiation Frequency, Amplitude, and Average Frequency, provide unique, statistically significant contributions (p < 0.05). The remaining predictors became redundant once these four were included. Machine learning and deep learning models trained on this minimal feature set achieved validation accuracies up to 98.7% on external specimens. High-frequency components (>1 MHz), as recorded at the sensor location after propagation and sensor convolution, were associated with fiber break events at elevated loads, while delamination events exhibited higher amplitude and lower-frequency content (<200 kHz) compared to matrix crack events. These observed frequency ranges reflect the combined effects of source mechanisms, guided wave dispersion in the 2.4 mm thick laminate, PWAS sensor response, and HDT-based hit segmentation, and are consistent with established AE damage signatures in literature. The results indicate that this four-parameter set is sufficient to classify the labeled AE waveform classes under monotonic tensile loading of quasi-isotropic [45/90/−45/0]_2s laminates, achieving 98.7% agreement with reference labels assigned via waveform morphology and spectral analysis. The proposed approach reduces computational overhead and enhances interpretability for structural health monitoring applications, pending validation across broader material systems and loading scenarios. A limitation of this study is that reference labels were assigned using waveform morphology and spectral analysis, lacking independent physical validation (e.g., microscopy). Full article

Composite hydrogen storage vessels exhibit pronounced anisotropy, multilayered winding architectures, and strong ultrasonic attenuation, which severely degrade the focusing accuracy and defect visibility of the conventional isotropic total focusing method (TFM). To address these challenges, this study proposes an enhanced TFM framework for defect inspection in composite hydrogen storage vessels by integrating anisotropic delay correction, Gray-code coded excitation, and coherence-weighted reconstruction. First, an anisotropic propagation delay model is established using forward ray tracing to compensate for beam deviation and focusing mismatch induced by the anisotropic winding structure. Then, Gray-code excitation and pulse compression are introduced to improve signal energy and echo detectability under high-attenuation conditions. Finally, coherence-weighted imaging is applied to suppress incoherent background noise and structural artifacts, thereby enhancing defect contrast and image readability. The proposed method is validated on hydrogen storage vessel specimens containing artificial defects, with CT results used as references. Experimental results show that, compared with conventional isotropic TFM, the proposed collaborative approach significantly improves defect imaging quality for defects of different sizes and depths. The signal-to-noise ratio is increased from 7.2, 12.8, 14.8, and 7.4 dB for isotropic TFM to 32.5, 29.9, 52.6, and 42.7 dB, respectively, for the combined anisotropic, coded-excitation, and coherence-weighted TFM. In addition, the defect depth estimation remains stable and agrees well with the CT references, yielding approximately 9.0–9.6 mm for shallow defects and 18.7–19.3 mm for deeper defects. These results demonstrate that the proposed method can effectively improve defect detectability, image contrast, and depth characterization for embedded delamination-like artificial defects in composite hydrogen storage vessels, providing a promising ultrasonic imaging strategy for thick-walled anisotropic composite pressure structures. Full article

Automated Fibre Placement (AFP) enables the rapid and precise manufacturing of composite structures, but the process inherently introduces defects such as gaps and overlaps, which can significantly affect structural performance. Most existing studies assess these effects through coupon-scale testing; however, such an approach may not capture the influence of structural scale and defect interaction. This study investigates the combined effects of specimen dimension and defect configuration on stiffness, strength, and damage evolution. Two characteristic defect patterns were examined—aligned and staggered gaps—across two specimen dimensions. The results reveal different scaling trends for strength and stiffness between the two configurations. They also show the influence of specimen size on damage initiation and delamination behaviour. The findings demonstrate that coupon-based knockdowns cannot be directly extrapolated to structural components without accounting for defect interaction and scale effects. Full article

To improve the dry cutting performance of YG8 cemented carbide tools, CaF₂/[BMIM]PF₆@PPSU solid–liquid dual-core microcapsules were incorporated into microtextures on the rake face, thereby constructing a microcapsule–microtexture composite self-lubricating tool system. Cutting experiments were conducted to systematically investigate the effects of microcapsule content and microtexture edge spacing on the cutting performance of the tools. The results indicate that optimal cutting performance is achieved at a microcapsule content of 20 wt.% and an edge spacing of 100 μm. Under these conditions, the tool embedded with dual-core microcapsules exhibited a main cutting force as low as 88.6 N, a cutting temperature of 237.8 °C, a machined surface roughness of 1.08 μm, and an extended cutting distance of 9497 m. Compared with the unlubricated tool, the main cutting force, axial force, and radial force decreased by approximately 40%, 45.6%, and 47.4%, respectively; the cutting temperature decreased by 43.9%, and the surface roughness was reduced by 24.5%. Micromorphological analysis reveals that, under optimal conditions, the TC2 tool effectively mitigates adhesive and delamination wear on both the rake and flank faces. Energy-dispersive spectroscopy (EDS) analysis demonstrates that the rupture of microcapsules releases two core materials, forming a stable solid–liquid biphasic lubricating film that effectively suppresses adhesive and abrasive wear. Full article

The long-term performance of photovoltaic (PV) modules significantly affects the reliability and economic viability of solar energy systems, as various environmental and operational factors can gradually degrade module efficiency and reduce energy output. This study investigates the long-term performance degradation analysis of 40 outdoor photovoltaic (PV) modules exposed for four years on a five-level building in Mirpur, Dhaka, Bangladesh. Electrical parameters, including voltage, current, power, and fill factor, were measured using a PROVA 1011 PV analyzer under IEC60904-1 standard test conditions, and analyzed to evaluate the extent of long-term degradation of PV modules. The image-based analysis identified degradation factors such as dust accumulation, soiling, hotspots, discoloration, micro-cracks, delamination, and corrosion. All test data were normalized to standard conditions (1000 W/m², 25 °C) for consistency. The measured average maximum power output was 9.85 W, with an average fill factor of 0.713 and a standard deviation of 0.939 for the 40 photovoltaic modules with a rated capacity of 10 W each. The dataset provides valuable insights for researchers and industry professionals to assess long-term PV performance, optimize maintenance strategies, and support solar energy deployment in tropical environments. Additionally, it can aid policymakers in developing regulatory frameworks for improving solar infrastructure resilience. Full article

Ferritin, a natural cage-like protein, can be applied as a nanomaterial to encapsulate and deliver bioactive ingredients, while challenges remain when using ferritin to deliver multiple bioactive ingredients. In this study, a ferritin–zinc ion–alginate oligosaccharide (AOS) core–shell complex (FZA) and hydrophobic astaxanthin (AST) were applied as the water and oil phase to prepare oil-in-water emulsions simultaneously containing mineral element and hydrophobic AST. The ferritin works as a multicompartment carrier to encapsulate the Zn²⁺ ions and bind with the AOS. This emulsion exhibited smaller particle size and higher apparent viscosity, elastic modulus, and anti-delamination stability. After heat treatment, natural light irradiation, and ultraviolet irradiation, the retention rates of AST in FZA-stabilized emulsion were increased by 23.09%, 18.25%, and 19.24%, respectively, compared with AST dissolved in oil. The release rate of AST in FZA-stabilized emulsion was increased by 26.97% compared with that dissolved in oil in vitro digestion simulation, and release rate of Zn²⁺ ions in FZA-stabilized emulsion improved by 20.38% relative to the control. This study provides experimental evidence for the emulsion stabilized by the AOS and ferritin multi-interface, which achieves dual co-delivery and protection of mineral and hydrophobic molecules. Full article

Ultrasonic Guided Wave (UGW)-based Structural Health Monitoring (SHM) is a promising strategy for detecting damage to aeronautical structures, although its application is complicated by signal complexity and experimental uncertainty. This work seeks to identify damage-sensitive signal features for integration into Machine Learning (ML) frameworks, offering physics-informed indicators. The study combined experimental monitoring of damage to Carbon Fibre Reinforced Polymer (CFRP) plates and finite element models. To overcome the numerical–experimental mismatch, an ML algorithm predicted experimental characteristics from numerical data. The robustness of the model was validated by extrapolation (prediction of future damage) and generalization (prediction on unseen plates) strategies, confirming that ML can robustly correct for uncertainty. These results validate hybrid strategies that feed Digital Twin approaches to structural diagnosis and real-time forecasting. Full article

The intralaminar and interlaminar mode I initiation fracture toughness of unidirectional IM7/8552 carbon/epoxy composites were re-evaluated using only the published experimental data. Classical statistics, two-parameter Weibull analysis (location fixed at zero), non-parametric kernel density estimation (KDE), bootstrap resampling (10,000 replications), and bootstrap-based uncertainty quantification were applied to the fatigue-precracked (FPC) initiation values (n = 12) and the corresponding R-curves. The pooled FPC mean initiation toughness was 0.1982 kJ/m² (COV = 8.50%). Weibull fitting yielded a shape parameter β = 12.33 and scale η = 0.2058 kJ/m², providing a B-basis value of 0.1715 kJ/m² (90% reliability) and an A-basis value of 0.1417 kJ/m² (99% reliability). The Kolmogorov–Smirnov test confirmed statistical equivalence between intralaminar and interlaminar groups (p > 0.05), validating the use of a single initiation toughness for both crack planes when sharp fatigue-precracked starter cracks are employed. Intralaminar R-curves exhibited significantly steeper propagation, rising to approximately 0.385 kJ/m² at Δa = 30 mm due to extensive fiber bridging, whereas interlaminar R-curves reached a near-plateau after 12–15 mm. Bootstrap 95% confidence bands quantified the higher uncertainty associated with the intralaminar R-curve. Teflon-insert data produced artificially high initiation values and unstable growth, confirming that only fatigue-precracked results are suitable for design allowables. This study demonstrates that a single, statistically robust initiation toughness (B-basis = 0.1715 kJ/m²) can be used interchangeably for intra- and interlaminar cracking in progressive-damage models and preliminary design analysis of IM7/8552 structures. The open-source statistical workflow (KDE + bootstrap) developed here is transferable to other small-sample composite datasets, though the numerical B-basis value (0.1715 kJ/m²) is specific to IM7/8552 and should not be generalized without validation. Full article

Acoustic emission (AE) was employed to characterize the mechanical behavior of repaired multi-layered woven lattice sandwich composite (MWLSC) in this paper. A patch repair strategy was adopted, in which damaged cores were reconstructed with polyurethane foam and fractured face sheets were restored using fiber fabric. Mechanical recovery was evaluated through mechanical testing, and AE monitoring was used to analyze damage evolution before and after repair. The repaired double-layered and triple-layered warp specimens recovered 123% and 104% of their original peak load, respectively, while the triple-layered weft specimen recovered 83%. Compared with pristine specimens, repaired MWLSC exhibited reduced cumulative AE counts and lower proportions of high-energy events. Continuous wavelet transform analysis revealed that the high-frequency components associated with interfacial delamination were significantly diminished after repair. These results indicate that repair modifies the dominant failure mechanism, shifting from delamination-dominated fracture toward core-related damage. The study demonstrates the effectiveness of AE techniques in capturing changes in damage evolution and mechanical response in repaired MWLSC. Full article

This study explores the influence of MXene solution as an interfacial liquid on the output performance of a Cu/n-Si-based direct current triboelectric nanogenerator (DC-TENG) system. The ${\mathrm{Ti}}_3{\mathrm{AlC}}_2$ MAX phase was successfully transformed into ${\mathrm{Ti}}_3{\mathrm{C}}_2{\mathrm{T}}_{\mathrm{x}}$ MXene through selective etching and was confirmed by scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) and X-ray diffraction (XRD) analyses, which revealed an increase in d-spacing from 8.99 to 9.58 Å and a transition from dense layered grains to delaminated, sheet-like structures. Electrochemical impedance spectroscopy (EIS) demonstrated a pronounced reduction in impedance with the introduction of MXene solution, indicating enhanced interfacial conductivity and charge transfer capability. The presence of MXene in deionized (DI) water led to the formation of an electrical double layer (EDL) at the Cu/n-Si interface, contributing to additional interfacial capacitance and more efficient charge relaxation dynamics. As a result, the DC-TENG output was significantly enhanced with the incorporation of MXene into the system, exhibiting a markedly higher current compared to the dry contact condition. Moreover, the MXene solution helped suppress charge decay compared to dry interfaces, highlighting its role as an effective liquid medium for stabilizing surface charge and improving interfacial electron transport in DC-TENG systems. Full article

This review summarizes the base materials, joining methods, filler materials, and principal technical challenges in endoscope joining fabrication, and proposes practical strategies to improve joint reliability under clinical constraints. We conducted a comprehensive search in multiple databases, including Web of Science, Google Scholar, patent databases, Scopus databases, and Medline (via PubMed), for articles on the joining for precision endoscope fabrication, covering the period from 1950 to 2026. We employed the combinations of keywords, “endoscopy”, “minimally invasive surgery”, “welding”, “joining”, “sealing”, “soldering”, “bonding”, and “brazing”. Approximately 500 references were retrieved. After excluding duplicates and irrelevant studies, 158 publications met the inclusion criteria. Data on base materials, joining, processes, filler materials, and technical issues related to sterilization, corrosion, and microstructural evolution were extracted and analyzed. Endoscopes are multi-material systems, involving metallic biomaterials (stainless steels (SSs), titanium alloys, nickel-based alloys, etc.), optical functional materials (glass, sapphire, quartz, etc.), engineering plastics, ceramics, composite materials, and coatings. Joining, sealing, and functional integration have been achieved via adhesive bonding, laser soldering, laser brazing, wave soldering, reflow soldering, fusion welding, and other joining techniques. The main challenges include how to reliably join highly mismatched dissimilar materials, how to fabricate low-residual-stress joints, and how to increase the long-term resistance to sterilization-induced degradation and thermal aging over repeated 100–200 °C thermal cycles. Conventional joining techniques struggle to balance mechanical integrity, joint hermeticity, and long-term stability under such harsh cyclic conditions. The resulting joints may suffer surface yellowing, interfacial debonding, microcracking, delamination, or progressive property degradation during service. We propose the following three strategies to achieve reliable, low-residual-stress, and sterilization-resistant joining of dissimilar materials for endoscopes: (1) A synergistic design that combines thin-film engineering (including evaporation, sputtering, and electroplating) with silver anti-oxidation layers is proposed to reduce residual stresses and to enhance the joint hermeticity. (2) To develop principles for the selection of multi-joining processes to achieve the multi-material integration and functional assembly of dissimilar material components. (3) To develop the laser-based joining methods (fusion, brazing, or braze-welding) for precision control of heat input, bonding quality, and the least damage to the heat-sensitive components. Full article