Search Results (447)

The design of smart skin with lightweight requirements utilizes high-performance composite materials, resulting in thin structural characteristics. When subjected to complex aerodynamic loads, the smart skin structure experiences warping deformation, which significantly impacts both flight efficiency and structural integrity. However, this deformation behavior has been largely overlooked in current shape sensing methods embedded within the structural health monitoring (SHM) systems of smart skin, leading to insufficient monitoring capabilities. To address this issue, this paper proposes a novel shape sensing methodology for the real-time monitoring of warping deformation in smart skin. Initially, the structural displacement field of the smart skin and the warping function are mathematically defined, incorporating constitutive relations and considering the influence of material parameters on sectional strains. Subsequently, the inverse finite element method (iFEM) is employed to establish a shape sensing model. The interpolation function and the actual sectional strains, derived from discrete strain measurements, are calculated based on the current constitutive equations. Finally, to validate the accuracy of the proposed iFEM for monitoring warping deformation, numerical tests are conducted on curved skin structures. The results indicate that the proposed methodology enhances reconstruction capability, with a 10% improvement in accuracy compared to traditional iFEM methods. Consequently, the shape sensing algorithm can be seamlessly integrated into the SHM system of smart skin to ensure the predicted performance. Full article

The supporting system of super-large cooling towers is crucial for the structural safety of nuclear power plants. The X-shaped reinforced concrete column has emerged as a promising solution due to its superior stability. However, the performance of the cast-in-place base joint, which is a key force-transfer component, requires thorough investigation. This study experimentally investigates the mechanical performance of the joints under ultimate vertical compressive and tensile loads. The loads represent gravity-dominated and extreme wind uplift scenarios, respectively. A comprehensive testing program monitored load–displacement responses, strain distributions, crack propagation, and failure modes. The compression specimen failed in a ductile flexural compression manner with plastic hinge formation above the column base. In contrast, the tension specimen exhibited a tension-controlled failure pattern. Crucially, the joint remained stable after column yielding in both loading scenarios. The result validates the “strong connection–weak member” design principle. The findings confirm that the proposed cast-in-place joint possesses excellent load-bearing capacity and ductility. Therefore, the study provides a reliable design basis for the supporting structures of super-large cooling towers. Full article

In order to improve the accuracy of the deformation reconstruction method based on the Ko displacement theory, a beam deformation reconstruction method based on CEEMDAN-HT-GMM-KO is proposed in this study. The method uses the CEEMDAN method to decompose the original signal and the GMM method to identify the noise so as to complete the noise reduction of the original data. A three-dimensional (3D) laser scanner was used to verify the results of strain information reconstruction before and after noise reduction. The results show that the average relative error of strain information reconstruction results after noise reduction is 4.54%. This method can eliminate the noise in the strain information and verify the accuracy of the deformation reconstruction method based on the Ko displacement theory in the overhanging beam under the condition of pre-deformation, providing a new method for the health monitoring of large steel structures. Full article

The large-scale deployment of aerospace composite structures has become a defining trend in modern aeronautics; however, hidden damage is difficult to detect over the full life cycle with conventional non-destructive inspection. This creates an urgent demand for on-line, high-fidelity structural health monitoring (SHM) technology. Optical-fiber sensors—featuring minimal mass, micron-scale diameter, immunity to electromagnetic interference and the ability to be co-cured into composite laminates for distributed measurement—are widely regarded as the key enabling technology. This paper presents a comprehensive review of recent advances and engineering applications of optical fiber sensing. Emphasis is placed on its engineering applications covering wing strain mapping, landing-gear load tracking, fuselage deformation localization, and cure-process monitoring and low-velocity impact damage identification of composite materials. Emerging intelligent assessment methodologies are examined. Finally, the development trends of optical fiber sensing technology are prospected, offering a reference framework for future theoretical innovation and engineering deployment of aerospace composite SHM technology. Full article

Distributed Acoustic Sensing (DAS) transforms conventional optical fibres into large-scale acoustic sensor arrays. While existing telecommunication cables are increasingly considered for DAS-based monitoring, their performance depends strongly on cable construction and strain transfer efficiency. In this study, the relative DAS signal amplitudes of three commercial telecommunication optical cables were experimentally compared using a benchtop Rayleigh backscattering-based interrogator under controlled laboratory conditions. By maintaining a constant temperature and ensuring no additional strain changes from the outside environment, we guaranteed that only strain-induced variations from acoustic excitations were measured. The results show clear differences in signal amplitude and signal-to-noise ratio (SNR) among the tested cables. The Microcable consistently produced the highest spatial peak amplitude (up to 0.029 a.u.) and SNR (up to 79), while the Duct cable reached 0.00268 a.u. with mean SNR ≈ 32. The Anti-Rodent cable showed low signal amplitude (0.0018 a.u.) but exhibited a high mean SNR (≈111) driven by an exceptional low noise floor in one of the runs. These findings reflect the variations in mechanical coupling between the fibre core and external perturbations and provide practical insights into the suitability of different telecom cable types for DAS applications, supporting informed choices for future deployments. Full article

Oz virus, an emerging tick-borne thogotovirus, has been reported to cause fatal human infection in Japan. However, its ecology and geographic distribution remain largely unknown. In this study, we developed a double-antigen sandwich enzyme-linked immunosorbent assay (DAgS ELISA) for detecting Oz virus antibodies in animals and used it to conduct a seroepidemiological survey of wild boars (Sus scrofa) in Miyazaki Prefecture, Japan. Recombinant Oz virus nucleoprotein was expressed in E. coli and used as both the capture and detection antigen. Relative to the neutralization test, the DAgS ELISA showed a sensitivity of 72.2%, a specificity of 88.2%, and an overall concordance rate of 79.0%. We used this assay to examine 1045 wild boar serum samples collected between November 2022 and May 2025, finding a seroprevalence of 33.5%. The seroprevalence did not significantly differ by sex, age, or region, but showed significant seasonal variation, peaking in summer (p < 0.0001). Oz virus RNA was detected by quantitative RT-PCR in one serum sample (0.09%). Phylogenetic analysis of the partial Oz virus glycoprotein gene showed that this strain shared 98.8% nucleotide identity with the EH8 strain, which was the first Oz virus isolate obtained from ticks in Ehime Prefecture. These findings suggest that wild boars in Miyazaki are frequently exposed to Oz virus and that ticks in the region harbor the virus. However, no human cases have been reported to date. The DAgS ELISA developed in this study provides a practical tool for serological surveillance in animals. Continuous monitoring of animal populations is warranted to clarify the epidemiology of Oz virus in the region and to identify potential reservoir species. Full article

To study the mechanical properties and displacement evolution of rock masses near coal-seam normal faults under mining disturbances; this paper utilizes fiber optic monitoring and distributed strain measurement techniques to achieve the fine monitoring of the entire process of stress–displacement–strain during mining. The experimental design adopts a stepwise mining approach to systematically reproduce the evolution of fault formation; slip; and instability. The results show that the formation of normal faults can be divided into five stages: compressive deformation; initiation; propagation; slip; and stabilization. The strength of the fault plane is significantly influenced by the dip angle. As the dip angle increases from 30° to 70°, the peak strength decreases by 23%, and the failure mode transitions from tensile failure to shear failure. Under mining disturbances, the stress field in the overlying rock shifts from concentration to dispersion, with a stress mutation zone appearing in the fault-adjacent area. During unloading, vertical stress decreases by 45%, followed by a rebound of 10% as mining progresses. The rock layers above the goaf show significant subsidence, with the maximum vertical displacement reaching 150 mm. The displacement between the hanging wall and footwall differs, with the maximum horizontal displacement reaching 78 mm. The force chain distribution evolves from being dominated by compressive stress to a compressive–tensile stress coupling state. The fault zone eventually enters a stress polarization state and tends toward instability. A large non-uniform high-speed zone forms at the fault cutting point in the velocity field, revealing the mechanisms of fault instability and the initiation of dynamic disasters. These experimental results provide a quantitative understanding of the multi-physics coupling evolution characteristics of coal-seam normal faults under mining disturbances. The findings offer theoretical insights into the instability of coal-seam normal faults and the mechanisms behind the initiation of dynamic disasters. Full article

High-temperature superconductor (HTS) magnet systems, especially those designed for fusion reactors, require effective and reliable monitoring to avoid damaging anomalies. In tokamaks, some of the magnetic coils are time-dependent, which causes strain and large inductive voltages within the magnet, rendering detection of incipient quench challenging. Ionizing radiation can also create material defects and lead to non-uniform degradation of conductors. The resulting decrease in critical current uniformity across the magnet, along with manufacturing defects, such as failure of structural materials or cooling systems, can all potentially initiate a quench. HTS magnets have a lower normal zone propagation velocity than low-temperature superconductors, and this causes normal zones to be localized, increasing the risk of permanent damage. Fiber optic sensors have several qualities that are essential in fusion systems. Unlike traditional voltage-based sensors, fiber optic cables are immune to the large electromagnetic fields present. This study presents and validates a fiber optic interrogation technique for monitoring magnetic confinement fusion and other high-temperature superconducting magnet systems. Coherent-phase optical time domain reflectometry (OTDR) allows for the high sampling rates (tens of kHz) necessary to quickly detect and mitigate quench events over the long distances required to monitor fusion magnet systems. This technique was demonstrated to successfully detect localized thermal transients at cryogenic temperatures as low as 6 K. These outcomes were also demonstrated using fibers embedded in HTS magnet coils at 77 K, verifying the potential for this interrogation technique’s use for failure detection in HTS coils. Full article

The paper presents two innovative measurement methods for assessing the flexural performance of precast concrete beams that are prestressed with Carbon Fiber-Reinforced Polymer (CFRP) bars. Strains, displacements, crack development, and failure modes were recorded until failure occurred, using a combination of Distributed Fiber Optic Sensing (DFOS) and Digital Image Correlation (DIC) techniques. This approach provides a more comprehensive understanding of the behavior of CFRP-prestressed beams under load, allowing for more accurate predictions than traditional measurement systems. By integrating both techniques, it is possible to validate results and establish an effective monitoring system. Based on tests conducted on three CFRP-prestressed beams subjected to three-point bending, general recommendations are made for both DFOS and DIC measurement techniques for reinforced concrete (RC) members. DFOS is more effective at detecting minor strains, while DIC excels in measuring large strains in RC structures. Both DFOS and DIC techniques facilitated the monitoring of crack development in RC structures, providing detailed analyses of the location, number, spacing, and width of the cracks. However, beyond the cracking load, the DFOS results can become unreliable due to the impact of cracks on the fiber optic readings. Therefore, DFOS and DIC measurement techniques can be used complementarily, taking into account their respective limitations. Full article

Structural Health Monitoring (SHM) is now essential for certifying many composite primary structures as it resolves strain redistribution at the moment of impact. Traditional detection methods, including resistive strain gauges, face challenges due to susceptibility to electromagnetic noise, as well as increased mass and wiring complexity proportional to the number of channels. This study proposes an impact strain monitoring and simulating method using optical fiber sensors for composite skin panels. Repeated low-velocity impact tests were conducted on large-size composite skin panels using various impact forces and locations. The 95% confidence interval for unit load strain in the simulation results differs from the experiment by 18%. This method effectively facilitates the monitoring of global impact strain on large-size composite skin panels. Full article

To address the challenges in preventing and controlling mastitis caused by Escherichia coli and Staphylococcus aureus in large-scale dairy farms, as well as the issues of traditional disinfection protocols relying on experience and exhibiting significant efficacy fluctuations, this study aimed to systematically explore optimal disinfection strategies adapted to different scenarios and seasons. Five common commercial disinfectants in China were selected to target the two aforementioned pathogenic strains. Experiments were conducted under three typical scenarios—bacterial suspension, stainless steel carriers (simulating milking equipment), and cow dung cubicle bedding—and three temperature conditions (4 °C, 25 °C, 37 °C, simulating seasonal temperatures). A series of tests were performed, including neutralizer identification tests, determination of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC), quantitative suspension and carrier spray disinfection tests, and monitoring of bacterial growth and decline in cow dung cubicle bedding. These tests were used to quantitatively analyze the regulatory mechanisms of disinfectant concentration, action time, and environmental temperature on disinfection efficacy. The Compound Glutaral Solution (CGS) exhibited the best overall performance, with strong temperature stability across all scenarios and high-efficiency bactericidal activity even at low concentrations. Additionally, the combined system of the CGS and bleaching powder (BP) achieved the optimal effect in controlling bacterial rebound in the cow dung cubicle bedding scenario. This study clarified the scenario-specific adaptation rules of different disinfectants and established a scenario-specific precision disinfection strategy for dairy farms. It provides a scientific basis for improving the level of mastitis prevention and control and optimizing biosafety systems, while also offering references for the disinfection of hard surfaces in fields such as healthcare and food processing. Full article

Rapid and accurate diagnostics for influenza viruses are essential for preventing future epidemics. Surface-enhanced Raman spectroscopy (SERS) presents a promising alternative to conventional techniques, offering a rapid, cost-effective, and highly sensitive platform for influenza virus detection. It is a highly sensitive analytical technique that enables the detection of minute chemical substances through significant signal enhancement. It operates by illuminating a sample with a laser and analyzing the scattered light to generate a unique molecular Raman spectrum. The sensitivity of SERS is derived from its use of metal nanoparticles, which amplify the weak Raman signals, making it particularly effective for detecting low-concentration targets such as viruses. Avian influenza (AI) is a major threat to domestic poultry, leading to large-scale culling during outbreaks. It leads to economic losses globally and can also infect pigs and humans, potentially causing a pandemic. Migratory birds spread various strains, leading to the development of highly pathogenic viruses. Viral monitoring is crucial for prevention strategies and understanding the virus evolution. This review outlines the challenges in detecting AI virus in chickens and critically assesses the established and emerging diagnostic technologies, with a specific focus on the factors influencing detection and recent advances in SERS-based AI detection. Ultimately, this review aims to provide insights that will assist the influenza research community in developing novel strategies for monitoring and preventing AI outbreaks in chickens and mitigating zoonotic transmission. Full article

Geohazards pose significant dangers to human safety, infrastructures, and the environment, highlighting the need for advanced monitoring techniques for early damage detection and structure management. The distributed optical fiber sensors (DFOS) are strain, temperature, and vibration monitoring tools characterized by minimal intrusiveness, accuracy, ease of deployment, and the ability to perform measurements with high spatial resolution. Although these sensors rely on well-established measurement techniques, available for over 40 years, their diffusion within monitoring and early warning systems is still limited, and there is a certain mistrust towards them. In this regard, based on several case studies, the implementation of DFOS for early warning of various geotechnical hazards, such as landslides, earthquakes and subsidence, is discussed, providing a comparative analysis of the typical advantages and limitations of the different systems. The results show that real-time monitoring systems based on well-established distributed fiber-optic sensing techniques are now mature enough to enable reliable and long-term geotechnical applications, identifying a market segment that is only minimally saturated by using other monitoring techniques. More challenging remains the application of the technique for vibration detection that still requires improved interrogation technologies and standardized practices before it can be used in large-scale, real-time early warning systems. Full article

The influence of stress on gas sorption behavior and sorption-induced swelling in coal is critical for the success of CO₂-enhanced coalbed methane recovery (CO₂-ECBM) and geological carbon sequestration—a key strategy for mitigating climate change and promoting clean energy transitions. However, this influence remains insufficiently understood, largely due to experimental limitations (e.g., overreliance on powdered coal samples) and conflicting theoretical frameworks in existing studies. To address this gap, this study systematically investigates the effects of two distinct stress constraints—constant confining pressure and constant volume—on CO₂ adsorption capacity, adsorption kinetics, and associated swelling deformation of intact anthracite coal cores. An integrated experimental apparatus was custom-designed for this study, combining volumetric sorption measurement with high-resolution strain monitoring via the confining fluid displacement (CFD) method and the confining pressure response (CPR) method. This setup enables the quantification of CO₂–coal interactions under precisely controlled stress environments. Key findings reveal that stress conditions exert a regulatory role in shaping CO₂–coal behavior: constant confining pressure conditions enhance CO₂ adsorption capacity and sustain adsorption kinetics by accommodating matrix swelling, thereby preserving pore accessibility for continuous gas uptake. In contrast, constant volume constraints lead to rapid internal stress buildup, which inhibits further gas adsorption and accelerates the attainment of kinetic saturation. Sorption-induced swelling exhibits clear dependence on both pressure and constraint conditions. Elevated CO₂ pressure leads to increased strain, while constant confining pressure facilitates more gradual, sustained expansion. This is particularly evident at higher pressures, where adsorption-induced swelling prevails over mechanical constraints. These results help resolve key discrepancies in the existing literature by clarifying the dual role of stress in modulating both pore accessibility (for gas transport) and mechanical response (for matrix deformation). These insights provide essential guidance for optimizing CO₂ injection strategies and improving the long-term performance and sustainability of CO₂-ECBM and geological carbon storage projects, ultimately supporting global efforts in carbon emission reduction and sustainable energy resource utilization. Full article

Photogrammetry offers a non-contact and efficient alternative for monitoring structural deformation and is particularly suited to large or complex surfaces such as masonry walls. This study proposes a spatio-temporal photogrammetric refinement framework that enhances the accuracy of three-dimensional (3D) deformation and strain analysis by integrating advanced filtering techniques into markerless image-based measurement workflows. A hybrid methodology was developed using natural image features extracted using the Speeded-Up Robust Features algorithm and refined through a three-stage filtering process: median absolute deviation filtering, Gaussian smoothing, and representative point selection. These techniques significantly mitigated the influence of noise and outliers on deformation and strain analysis. Comparative experiments using both manually placed targets and automatically extracted feature points on a full-scale masonry wall under destructive loading demonstrated that the proposed spatio-temporal filtering effectively improves the consistency of displacement and strain fields, achieving results comparable to traditional marker-based methods. Validation against laser rangefinder measurements confirmed sub-millimeter accuracy in displacement estimates. Additionally, strain analysis based on filtered data captured crack evolution patterns and spatial deformation behavior. Therefore, integrating photogrammetric 3D point tracking with spatio-temporal refinement provides a practical, accurate, and scalable approach to monitor structural deformation in civil engineering applications. Full article