Search Results (1,024)

Interferometric fiber optic hydrophones (IFOHs) are highly sensitive for underwater acoustic detection but face challenges owing to the trade-off between laser monochromaticity and coherence length. In this study, we propose a pseudo-random binary sequence (PRBS) phase modulation method for laser coherence length control, establishing the first theoretical model that quantitatively links PRBS parameter to coherence length, elucidating the mechanism underlying its suppression of parasitic interference noise. Furthermore, our research findings demonstrate that while reducing the laser coherence length effectively mitigates parasitic interference noise in IFOHs, this reduction also leads to elevated background noise caused by diminished interference visibility. Consequently, the modulation of coherence length requires a balanced optimization approach that not only suppresses parasitic noise but also minimizes visibility-introduced background noise, thereby determining the system-specific optimal coherence length. Through theoretical modeling and experimental validation, we determined that for IFOH systems with a 500 ns delay, the optimal coherence lengths for link fibers of 3.3 km and 10 km are 0.93 m and 0.78 m, respectively. At the optimal coherence length, the background noise level in the 3.3 km system reaches −84.5 dB (re: rad/√Hz @1 kHz), representing an additional noise suppression of 4.5 dB beyond the original suppression. This study provides a comprehensive theoretical and experimental solution to the long-standing contradiction between high laser monochromaticity, stability and appropriate coherence length, establishing a coherence modulation noise suppression framework for hydrophones, gyroscopes, distributed acoustic sensing (DAS), and other fields. Full article

By embedding optical fiber sensors into fiber preforms and utilizing liquid molding processes such as resin transfer molding (RTM), intelligent composite materials with self-sensing capabilities can be fabricated. In the liquid molding process of these intelligent composites, the quality of the final product is highly dependent on the resin flow and impregnation effects. The embedding of optical fibers can affect the microscopic flow and impregnation behavior of the resin; therefore, it is necessary to investigate the specific impact of optical fiber embedding on the resin flow and impregnation of fiber bundles. Due to the difficulty of directly observing this process at the microscopic scale through experiments, numerical simulation has become a key method for studying this issue. This paper focuses on the resin micro-flow in RTM processes for intelligent composites with embedded optical fibers. Firstly, a steady-state analysis of the resin flow and impregnation process was conducted using COMSOL 6.0 obtaining the velocity and pressure field distribution characteristics under different optical fiber embedding conditions. Secondly, the dynamic process of resin flow and impregnation of fiber bundles at the microscopic scale was simulated using Fluent 2022R2. This study comprehensively analyzes the impact of different optical fiber embedding configurations on resin flow and impregnation characteristics, determining the impregnation time and porosity after impregnation under different optical fiber embedding scenarios. Additionally, this study reveals the mechanisms of pore formation and their distribution patterns. The research findings provide important theoretical guidance for optimizing the RTM molding process parameters for intelligent composite materials. Full article

To address the poor thermal performance and low output efficiency of conventional solid-state microchip lasers, this study proposes and implements a bonded Nd:YAG/Cr⁴⁺:YAG laser based on fiber splitter pumping. Experimental results demonstrate that at a 4.02 mJ pump pulse energy and a 100 Hz repetition rate, the system achieves four linearly polarized output beams with an average pulse energy of 0.964 mJ, a repetition rate of 100 Hz, and an optical-to-optical conversion efficiency of 23.98%. The energy distribution ratios for the upper-left, lower-left, upper-right, and lower-right beams are 22.61%, 24.46%, 25.50%, and 27.43%, with pulse widths of 2.184 ns, 2.193 ns, 2.205 ns, and 2.211 ns, respectively. As the optical axis distance increases, the far-field spot pattern transitions from a single circular profile to four fully separated spots, where the lower-right beam exhibits beam quality factors of M_x² = 1.181 and M_y² = 1.289. Simulations at a 293.15 K coolant temperature and a 4.02 mJ pump energy reveal that split pumping reduces the volume-averaged temperature rise in Nd:YAG by 28.81% compared to single-beam pumping (2.57 K vs. 3.61 K), decreases the peak temperature rise by 66.15% (6.97 K vs. 20.59 K), and suppresses peak-to-peak temperature variation by 78.6% (1.34 K vs. 6.26 K). Compared with existing multi-beam generation methods, the fiber splitter approach offers integrated advantages—including compact size, low cost, high energy utilization, superior beam quality, and elevated damage thresholds—and thus shows promising potential for automotive multi-point ignition, multi-beam single-photon counting LiDAR, and laser-induced breakdown spectroscopy (LIBS) online analysis. Full article

With the expansion of offshore oil and gas resources to deepwater areas, the problem of the vortex-induced vibration of marine risers, as a key structure connecting offshore platforms and subsea wellheads, has become increasingly prominent. At present, there are few reviews on the vortex-induced vibration of flexible risers. This review provides a detailed discussion of vortex-induced vibration in marine risers. This review begins with the engineering background. It then systematically analyzes the key factors that influence VIV response. These factors include the riser’s structural parameters, such as aspect ratio and mass ratio. They also include the external fluid environment. Next, this review evaluates current VIV suppression strategies by analyzing specific experimental results. It compares the effectiveness and trade-offs of passive techniques. It also examines the potential and limitations of active methods, which often use smart materials, like piezoelectrics. This study highlights the major challenges in VIV research today. These challenges relate to prediction accuracy and suppression efficiency. Key problems include model uncertainty at high Reynolds numbers and the practical implementation of suppression devices in engineering systems. Finally, this paper presents an outlook on the future directions. It concludes that an intelligent, full-lifecycle integrity management system is the best path forward. Full article

Optical networks serve as the backbone of modern communication, requiring statistical analysis and modeling to optimize performance, reliability, and scalability. This review paper explores statistical methodologies for analyzing network characteristics, dimensioning, parameter estimation, and cost prediction of optical networks, and provides a generalized framework based on the idea of convex areas, and link length and shortest path length distributions. Accurate dimensioning and cost estimation are crucial for optical network planning, especially during early-stage design, network upgrades, and optimization. However, detailed information is often unavailable or too complex to compute. Basic parameters like coverage area and node count, along with statistical insights such as distribution patterns and moments, aid in determining the appropriate modulation schemes, compensation techniques, repeater placement, and in estimating the fiber length. Statistical models also help predict link lengths and shortest path lengths, ensuring efficiency in design. Probability distributions, stochastic processes, and machine learning improve network optimization and fault prediction. Metrics like bit error rate, quality of service, and spectral efficiency can be statistically assessed to enhance data transmission. This paper provides a review on statistical analysis and modeling of optical networks, which supports intelligent optical network management, dimensioning of optical networks, performance prediction, and estimation of important optical network parameters with partial information. Full article

Conventional detectors based on ionization chambers, semiconductors, or thermoluminescent materials generally cannot be used to verify the in vivo dose delivered during brachytherapy treatments with γ-ray sources. However, certain adaptations and alternative methods, such as the use of miniaturized detectors or other specialized techniques, have been explored to address this limitation. One approach to solving this problem involves the use of dosimetric materials based on efficient scintillation crystals, which can be placed in the patient’s body using a long optical fiber inserted intra-cavernously, either in front of or next to the tumor. Scintillation crystals with a density close to that of tissue can be used in any location, including the respiratory tract, as they do not interfere with dose distribution. However, in many cases of radiation therapy, the detector may need to be positioned behind the target. In such cases, the use of heavy, high-density, and high-Z_eff scintillators is strongly preferred. The delivered radiation dose was registered using the radioluminescence response of the crystal scintillator and recorded with a compact luminescence spectrometer connected to the scintillator via a long optical fiber (so-called fiber-optic dosimeter). This proposed measurement method is completely non-invasive, safe, and can be performed in real time. To complete the abovementioned task, scintillation detectors based on YAG:Ce (ρ = 4.5 g/cm³; Z_eff = 35), LuAG:Ce (ρ = 6.75 g/cm³; Z_eff = 63), and GAGG:Ce (ρ = 6.63 g/cm³; Z_eff = 54.4) garnet crystals, with different densities ρ and effective atomic numbers Z_eff, were used in this work. The results obtained are very promising. We observed a strong linear correlation between the dose and the scintillation signal recorded by the detector system based on these garnet crystals. The measurements were performed on a specially prepared phantom in the brachytherapy treatment room at the Oncology Center in Bydgoszcz, where in situ measurements of the applied dose in the 0.5–8 Gy range were performed, generated by the ¹⁹²Ir (394 keV) γ-ray source from the standard Fexitron Elektra treatment system. Finally, we found that GAGG:Ce crystal detectors demonstrated the best figure-of-merit performance among all the garnet scintillators studied. Full article

Understanding the time-lagged response of land subsidence to groundwater level fluctuations and subsurface strain variations is crucial for uncovering its underlying mechanisms and enhancing disaster early warning capabilities. This study focuses on Dangshan County, Anhui Province, China, and systematically analyzes the spatio-temporal evolution of land subsidence from 2018 to 2024. A total of 207 Sentinel-1 SAR images were first processed using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to generate high-resolution surface deformation time series. Subsequently, the seasonal-trend decomposition using the LOESS (STL) model was applied to extract annual cyclic deformation components from the InSAR-derived time series. To quantitatively assess the delayed response of land subsidence to groundwater level changes and subsurface strain evolution, time-lagged cross-correlation (TLCC) analysis was performed between surface deformation and both groundwater level data and distributed fiber-optic strain measurements within the 5–50 m depth interval. The strain data was collected using a borehole-based automated distributed fiber-optic sensing system. The results indicate that land subsidence is primarily concentrated in the urban core, with annual cyclic amplitudes ranging from 10 to 18 mm and peak values reaching 22 mm. The timing of surface rebound shows spatial variability, typically occurring in mid-February in residential areas and mid-May in agricultural zones. The analysis reveals that surface deformation lags behind groundwater fluctuations by approximately 2 to 3 months, depending on local hydrogeological conditions, while subsurface strain changes generally lead surface subsidence by about 3 months. These findings demonstrate the strong predictive potential of distributed fiber-optic sensing in capturing precursory deformation signals and underscore the importance of integrating InSAR, hydrological, and geotechnical data for advancing the understanding of subsidence mechanisms and improving monitoring and mitigation efforts. Full article

This study focuses on the multiphase flow in horizontal wells based on distributed acoustic sensing (DAS) monitoring. Through laboratory experiments and field data analysis, it was found that the micro-seismic differences in flow patterns can be clearly observed in the fiber optic micro-seismic waterfall chart. In the case of slug flow, the DAS acoustic energy decreases when the inclination angle increases. The performance of annular flow is similar to that of bubble flow, with the DAS energy increasing as the inclination angle increases. Overall, the order of DAS acoustic energy from the strongest to weakest is slug flow, followed by annular flow, and then bubble flow. The research shows that fiber optic DAS monitoring signals can effectively identify differences in gas volume, well inclination, and flow pattern, which provides an important technical basis and research foundation for the monitoring and analysis of multiphase flow in horizontal wells. Full article

A stable microwave signal transmission system for a distributed system that is capable of simultaneous downloads at multiple arbitrary nodes within the optical path is proposed. The download module, which is based on optical circulators and optical couplers, can be inserted at any node position within the transmission optical path to complete the downloading of frequency-synchronization signals. Experimentally, a distributed frequency-synchronization system with multiple download nodes is demonstrated over 40 km of optical fiber. Experimental results show that the signal has been downlink-transferred from different download modules with the standard deviation of phase jitter being 1°@10 GHz at 1 h through 40-km optical fiber. Moreover, the standard deviation of phase jitter between downloaded signals from any two download modules is also better than 1°@10 GHz at 1 h. In addition, the Allan Deviation is better than ${10}^{-12}$@1 h for the download module. Full article

The increasing demand for high-speed internet and advanced digital services necessitates the deployment of robust and scalable broadband infrastructure, particularly in smaller urban and rural areas. This paper presents the design and implementation of a passive optical network (PON) based on a gigabit-capable passive optical network (GPON) standard to deliver fiber-to-the-home (FTTH) services in a small-town setting. The proposed solution prioritizes cost-effectiveness, scalability, and minimal energy consumption by leveraging passive splitters and unpowered network elements. We detail the topology planning, splitter architecture, installation practices, and technical specifications that ensure efficient signal distribution and future network expansion. The results demonstrate the successful implementation of an optical access infrastructure that supports high-speed internet, Internet Protocol television (IPTV), and voice services while maintaining flexibility for diverse urban layouts and housing types. Full article

In response to the increasing demands for reliable, fast, and secure communications beyond 5G scenarios, the high-capacity networks have become a focal point. Quantum communication is at the forefront of this research, offering unmatched throughput and security. A free space optics (FSO) communication system integrated with fiber-end is designed and investigated using the Bennett–Brassard 1984 quantum key distribution (BB84-QKD) protocol. Simulation results show that reliable transmission can be achieved over a 10–15 km fiber length with a signal power of −19.54 dBm and high optical-to-signal noise of 72.28–95.30 dB over a 550 m FSO range under clear air, haze, fog, and rain conditions at a data rate of 1 Gbps. Also, the system using rectilinearly and circularly polarized signals exhibits a Stokes parameter intensity of −4.69 to −35.65 dBm and −7.7 to −35.66 dBm Stokes parameter intensity, respectively, over 100–700 m FSO range under diverse weather conditions. Likewise, for the same scenario, an FSO range of 100 m incorporating 2.5–4 mrad beam divergence provides the Stokes power intensity of −6.03 to −11.1 dBm and −9.04 to −14.12 dBm for rectilinearly and circularly polarized signals, respectively. Moreover, compared to existing works, this work allows faithful and secure signal transmission in free space, considering FSO–fiber link losses. Full article

In this paper, we present the development of a new semi-distributed interferometer (SDI) biosensor with a Zn, Cu, and Co metal oxide nanopowder coating for the detection of a kidney disease biomarker as a model system. The combination of nanopowder coating with the SDI platform opens up unique opportunities for improving measurement reproducibility while maintaining high sensitivity. The fabrication of sensors is simple, which involves one splice and subsequent cutting at the end of an optical fiber. To ensure specific detection of the biomarker, a monoclonal antibody was immobilized on the surface of the probe. The biosensor has demonstrated an impressive ability to detect biomarkers in a wide range of concentrations, from 1 aM to 100 nM. The theoretical limit of detection was 126 fM, and the attomolar detection level was experimentally achieved. The sensors have achieved a maximum sensitivity of 190 dB/RIU and operate with improved stability and reduced dispersion. Quantitative analysis revealed that the sensor’s response gradually increases with increasing concentration. The signal varies from 0.05 dB at 1 aM to 0.81 dB at 100 nM, and the linear correlation coefficient was R² = 0.96. The sensor showed excellent specificity and reproducibility, maintaining detection accuracy at about 10⁻⁴ RIU. This opens up new horizons for reliable and highly sensitive biomarker detection, which can be useful for early disease diagnosis and monitoring using a cost-effective and reproducible sensor system. Full article

As an advanced real-time monitoring technique, optic fiber downhole sensing has been widely applied in monitoring fracture propagation during hydraulic fracturing. However, existing fracture shape inversion methods face two main challenges: firstly, traditional methods struggle to accurately capture the dynamic changes in strain rate and fracture shape during the propagation process, and secondly, they are computationally expensive. To address these issues, this study proposes a full-time-step fitting inversion method. By precisely fitting all time steps of fracture propagation, this method effectively overcomes the shape deviation problems often encountered in traditional methods and significantly reduces computational costs. Compared to conventional single-time-step inversion methods, our approach not only provides a more accurate representation of the spatiotemporal dynamics of fracture propagation but also avoids the risk of significant errors in fracture shape reconstruction. Therefore, the proposed inversion method holds substantial practical value and significance in fracture monitoring and sensing for oil and gas fields. Full article

Ultrafine fibers from poly(3-hydroxybutyrate) (PHB) and polyvinylpyrrolidone (PVP) and their blends with different component ratios in the range of 0/100 to 100/0 wt.% were obtained, and their structure and dynamic properties were studied. The polymers were obtained via electrospinning in solution mode. The structure, morphology, and segmental dynamic behavior of the fibers were determined using optical microscopy, SEM, EPR, DSC, and IR spectroscopy. The low-temperature maximum on the DSC endotherms provided information on the state of the PVP hydrogen bond network, which made it possible to determine the enthalpies of thermal destruction of these bonds. The PHB/PVP fiber blend ratio significantly affected the structural and dynamic parameters of the system. Thus, at low concentrations of PVP (up to 9%) in the structure of ultra-fine fibers, the distribution of this polymer occurs in the form of tiny particles, which are crystallization centers, which causes a significant increase in the degree of crystallinity (χ) activation energy (E_act) and slowing down of molecular dynamics (τ). At higher concentrations of PVP, loose interphase layers were formed in the system, which caused a decrease in these parameters. The strongest changes in the concentration of hydrogen bonds occurred when PVP was added to the composition from 17 to 50%, which was due to the formation of intermolecular hydrogen bonds both in PVP and during the interaction of PVP and PHB. The diffusion coefficient of water vapor in the studied systems (D) decreased as the concentration of glassy PVP in the composition increased. The concentration of the radical decreased with an increase in the proportion of PVP, which can be explained by the glassy state of this polymer at room temperature. A characteristic point of the 50/50% mixture component ratio was found in the region where an inversion transition of PHB from a dispersion material to a dispersed medium was assumed. The conducted studies made it possible for the first time to conduct a comprehensive analysis of the effect of the component ratio on the structural and dynamic characteristics of the PHB/PVP fibrous material at the molecular scale. Full article

Distributed acoustic sensing (DAS) is a highly effective method of monitoring all kinds of intrusions on railway tracks. These intrusions represent a real problem in the railway sector, as they can lead to human deaths or damage to railway tracks, and these intrusions may be human or animal. A fiber was deployed along 12 km of track in a railway test center, enabling us to acquire data day and night. A data acquisition campaign was carried out in April 2023 to capture the signatures of several scenarios (walking, digging, falling rocks, etc.) in order to train machine learning models and prevent any intrusion by detecting and classify these intrusion. The study shows the diversity of signals that fiber can acquire in the rail sector and the machine learning model performance. Signals associated with the presence of animals are also presented. Full article