Search Results (263)

Distributed fiber optic sensing (DFOS) has emerged as a critical technology for structural health monitoring of large-scale infrastructure, offering unique advantages in terms of coverage and environmental adaptability. This review presents a comprehensive analysis of the two dominant technical routes: fully distributed sensing based on intrinsic backscattering and massive-capacity sensing based on ultra-weak fiber Bragg grating (UWFBG) networks. For backscattering-based systems—encompassing Raman, Brillouin, and Rayleigh scattering—the inherent trade-offs among signal-to-noise ratio (SNR), spatial resolution, and sensing range constitute major performance bottlenecks. This review systematically summarizes advanced demodulation and signal processing strategies designed to overcome these physical barriers, including pulse coding sequences, chaotic laser compressed correlation, and deep learning-enhanced noise reduction algorithms. In parallel, for UWFBG-based technologies, the evolution from traditional multiple-point fiber Bragg grating (FBG) array to quasi-distributed and fully distributed UWFBG network is discussed. This review highlights key breakthroughs in achieving high spatial resolution and high-speed interrogation through hybrid multiplexing, aliased spectrum reconstruction, and dispersion-based demodulation techniques. By synthesizing recent advances in modulation schemes, detection hardware, and algorithmic processing, this paper outlines the trajectory of DFOS technologies toward high-precision, long-distance, and real-time sensing networking. Full article

Transverse mode instability (TMI) in high-power ytterbium-doped double-clad fiber lasers is widely interpreted as being a consequence of a thermo-optic nonlinear phenomenon driven by stimulated thermal Rayleigh scattering. This work presents a coupled optical–thermal model for a continuous-wave forward-pumped (${\lambda }_p=976\mathrm{nm}$) fiber amplifier emitting at ${\lambda }_s=1064\mathrm{nm}$ over an optimal length of 12 m. The formulation explicitly resolves the three radial regions of a double-clad fiber, avoiding single-clad approximations. Modal fields are computed using the weakly guiding approximation (WGA) in the core combined with the semi-WGA at the cladding interfaces, enabling accurate calculation of higher-order modes of penetration into the inner cladding and of the transverse eigenvalues $U_{01}$ and $U_{mn}$ relevant to TMI. Within this framework, the nonlinear stimulated thermal Rayleigh scattering coupling coefficient is evaluated, including gain saturation and the thermal eigenmodes of the multi-layer geometry. The results show that the inner cladding modifies both the optical and thermal mode structures, altering the optical–thermal overlap between ${\mathrm{LP}}_{01}$ and higher-order modes and changing the effective strength of STRS, directly influencing the predicted TMI threshold. The proposed formulation provides a quantitative and physically consistent tool for analyzing thermo–optic dynamics in Yb-double-clad fiber amplifiers and supports the design of next-generation high-power fiber lasers with improved modal stability. Full article

In remote sensing, multi-sensor data fusion enhances environmental monitoring by integrating complementary observations. A critical step in this integration is spatial resampling to a common scale. Although often regarded as a routine preprocessing operation, resampling can become a significant source of radiometric uncertainty, systematically altering scene radiance during scale transformation, especially in heterogeneous aquatic environments. In this study, we evaluate resampling-induced radiometric uncertainty and assess the physical advantages of flux-conserving resampling in multi-scale aquatic remote sensing. Using the radiometrically stable Landsat 8 OLI sensor as a reference platform, this study develops a radiometric stability–based framework to evaluate multi-scale resampling methods. Radiometric consistency in the visible bands was first evaluated using a Rayleigh scattering calibration, allowing a systematic comparison of four resampling methods across multiple spatial scales. Normalized water-leaving radiance was then retrieved using the Satellite Signal in the Solar Spectrum (6S) radiative transfer model and validated against in situ AERONET-OC measurements. Our results indicate that radiometric consistency decreases with increasing scale, while flux-conserving resampling maintains higher stability and preserves the spatiotemporal characteristics of water radiance. These findings highlight the importance of flux-conserving resampling for multi-scale radiometric fidelity and establish the proposed framework as a reference for reliable multi-source data fusion and quantitative inversion in aquatic remote sensing and beyond. Full article

This paper presents an orthogonal-heading wavelength-resolution SAR (WRSAR) target detection framework that fuses multi-heading image stacks for foliage-penetrating (FOPEN) vehicle detection. First, a low-rank–sparse decomposition is applied to very-high-frequency (VHF), ultra-wideband (UWB) WRSAR stacks to suppress vegetation clutter and enhance target contrast. The clutter-suppressed sparse stacks acquired from orthogonal headings are then fused to enrich target scattering characteristics. Finally, a Rayleigh-entropy statistic computed on the fused sparse stack is used to represent discontinuous positional changes. Based on the non-negative nature of WRSAR amplitudes for both clutter and FOPEN targets, we introduce a non-negative constrained tensor robust principal component analysis (NCTRPCA) to improve sparsity in the stack components. Furthermore, since Shannon differential entropy has no tunable parameter, we replace Shannon entropy with RE in this work and derive its closed-form expression for the proposed detector. Experiments on the publicly available multi-heading, multi-temporal CARABAS II dataset show that the proposed orthogonal-heading WRSAR fusion achieves higher FOPEN vehicle detection performance than recent state-of-the-art methods while maintaining moderate computational cost. Full article

The integration of optical-network sensing and communication (optical-network ISAC) can effectively utilize resources and meet the demands of intelligent scenarios, becoming a future development trend. This article reviews the fundamental technical principles involved in the optical-network ISAC, including three types of backward-sensing based on Rayleigh scattering, Raman scattering, and Brillouin scattering, respectively. The forward-sensing methods based on power profile estimation (PPE) and the state of polarization (SOP), as well as bidirectional sensing, are compared and analyzed. The technical difficulties and recent solutions to realize the optical-network ISAC are introduced, including the existing solutions implemented at the transmitter side or the receiver side. Finally, we discuss the new opportunities and major challenges of the optical-network ISAC technique for practical applications. Full article

To investigate the hypersonic boundary layer transition over complex three-dimensional configurations, this study conducted an experiment using infrared thermography, Rayleigh scattering visualization, and high-frequency pressure sensors in a Mach 6 Ludwieg wind tunnel. The infrared results indicate that increasing the Reynolds number promotes boundary layer transition on the model surface. Spectral analysis reveals a high-frequency peak centered at 250 kHz on the finless side of the windward surface. Comprehensive analysis indicates this represents high-frequency secondary instability triggered by the traveling crossflow mode in its nonlinear phase. On the finless side of the leeward surface, a typical Mack second-mode high-frequency instability amplification process is observed within the 140–280 kHz frequency band. Additionally, the spectrum results for the fin–cone junction became more complex. On the windward side, the primary energy concentration in the junction zone is observed between 80 and 200 kHz, with calculated wave packet velocities higher than those on the finless side. Wavelet analysis reveals that low-frequency modes are amplified first and gradually excite high-frequency components, with significant modal coupling appearing in the high-frequency region of the bicoherence. The leeward fin–cone junction exhibits dual-band characteristics at 60–120 kHz and 180–260 kHz, demonstrating stronger intermodal interactions. Both the windward and leeward surfaces of the fin show low-frequency transverse flow-like modes around 70–180 kHz. The spectral results for the windward and leeward sides are largely consistent, with only slight differences in amplitude levels and saturation positions. Full article

We report the use of σ-alkynyl d⁶ electron-rich transition metal complexes as electron-releasing end-groups in octupolar molecules designed for nonlinear optical (NLO) applications, specifically, N,N′,N″-triarylisocyanurates (5,7,8,10,12) and 1,3,5-triarylbenzenes (6,9,11) functionalized by Fe(II) and Ru(II) organometallic moieties, and their NLO properties, as assessed by hyper-Rayleigh scattering (HRS) and Z-scan. The redox properties are briefly investigated through isolation of the corresponding Fe(III) trications 5[PF₆]₃ and 6[PF₆]₃. The second-harmonic generation (SHG) or two-photon absorption (2PA) performance of the Fe(II) and Ru(II) parents is compared with the help of TD-DFT calculations performed on models. Comparison with tris-ferrocenyl isocyanurate 4 reveals that the σ-connection of the metallic centers to the π-manifold is superior to the η⁵-connection for enhancing NLO properties. The positive effect of organometallic end-groups on NLO properties relative to purely organic electron-releasing substituents is established. The mechanism by which NLO enhancement occurs is complex and possibly connected to the polarizable π-electrons in the ligands surrounding the metal alkynyl units, but in most cases, the observed NLO enhancement must arise from the transition metal centers interacting with the central π-manifold. Full article

Quantitative precipitation estimation (QPE) from radar reflectivity is fundamental for weather nowcasting and water resource management. Conventional Z-R relationship formulas, derived from Rayleigh scattering theory, rely heavily on empirical parameter fitting, which limits the estimation accuracy and generalization across different precipitation regimes. Recent deep learning (DL)-based QPE methods can capture the complex nonlinear relationships between radar reflectivity and rainfall. However, most of them overlook fundamental physical constraints, resulting in reduced robustness and interpretability. To address these issues, this paper proposes FusionQPE, a novel Physics-Constrained DL framework that integrates an adaptive Z-R formula. Specifically, FusionQPE employs a Dense convolutional neural network (DenseNet) backbone to extract multi-scale spatial features from radar echoes, while a modified squeeze-and-excitation (SE) network adaptively learns the parameters of the Z-R relationship. The final rainfall estimate is obtained through a linear combination of outputs from both the DenseNet backbone and the adaptive Z-R branch, where the trained linear weight and Z-R parameters provide interpretable insights into the model’s physical reasoning. Moreover, a physical-based constraint derived from the Z-R branch output is incorporated into the loss function to further strengthen physical consistency. Comprehensive experiments on real radar and rain gauge observations from Guangzhou, China, demonstrate that FusionQPE consistently outperforms both traditional and state-of-the-art DL-based QPE models across multiple evaluation metrics. The ablation and interpretability analysis further confirms that the adaptive Z-R branch improves both the physical consistency and credibility of the model’s precipitation estimation. Full article

The majority of the fatigue damage on offshore structures is generally assumed to be caused by relatively frequently occurring moderate sea states, i.e., sea states with significant waves lower than 7 m. This study aims to investigate the interrelationship between fatigue damage versus sea state severity on a moored offshore hybrid structure for wind and wave energy absorption. The analysis is performed using both a deterministic and a probabilistic method. The spectral-based fatigue assessment method is the deterministic element, and it attempts to account for the random nature of sea states in a rational manner. The analysis is performed using sea scatter diagrams and then developing the structure’s stress response spectrum. The probabilistic method uses the Rayleigh and lognormal cumulative density functions of the stresses in order to predict the probability of survival over a 31-year period, which is the period covered by the records. Full article

The integration of artificial intelligence (AI) with optical fiber sensing (OFS) is transforming the capabilities of modern sensing systems, enabling smarter, more adaptive, and higher-performance solutions across diverse applications. This paper presents a comprehensive review of AI-enhanced OFS technologies, encompassing both localized sensors such as fiber Bragg gratings (FBG), Fabry–Perot (FP) interferometers, and Mach–Zehnder interferometers (MZI), and distributed sensing systems based on Rayleigh, Brillouin, and Raman scattering. A wide range of AI algorithms are discussed, including supervised learning, unsupervised learning, reinforcement learning, and deep neural architectures. The applications of AI in OFS were discussed. AI has been employed to enhance sensor design, optimize interrogation systems, and adaptively tune configurations, as well as to interpret complex sensor outputs for tasks like denoising, classification, event detection, and failure forecasting. 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 long-time absorption spectroscopic development of the genetically encoded microbial rhodopsin fluorescent voltage indicator QuasAr1 at room temperature in the dark was reinvestigated, mainly theoretically. The data analysis indicates protein aggregation within one day to some ten-nanometer sized Mie scattering particles. The absorption coefficient spectra can be deduced from measured attenuation coefficient spectra by scattering contribution subtraction. The initially present protonated retinal Schiff base (PRSB) Ret_580 isomerized and then deprotonated to neutral retinal Schiff base (RSB). One part of Ret_580, Ret_580_I, (fraction 43%), isomerized moderately fast to Ret_500 which then deprotonated to neutral retinal Schiff base Ret_405 (time constant ≈ 1000 h). The other part of Ret_580, Ret_580_II, (fraction 57%), isomerized slowly to Ret_460 which deprotonated to Ret_340 (time constant ≈ 400 h). The dynamics are described by a differential equation system which is solved numerically. Reaction parameters are determined by fitting the simulations to the experimental results. Full article

The optical microscope is an indispensable observation instrument that has fundamentally contributed to progress in science and technology. Dark-field microscopy and scattered light imaging techniques enable high-contrast observation of nanoparticles in water. However, the scattered light is focused by the optical lenses, resulting in a blurred image of the nanoparticle structure. Here, we developed a projection optical microscope (PROM), which directly observes the scattered light from the nanoparticles without optical lenses. In this method, the sample is placed below the focus position of the microscope’s objective lens and the projected light is detected by an image sensor. This enables direct observation of the sample with a spatial resolution of approximately 20 nm. Using this method, changes in the aggregation state of nanoparticles in solution can be observed at a speed faster than the video frame rate. Moreover, the mechanism of such high-resolution observation may be related to the quantum properties of light, making it an interesting phenomenon from the perspective of optical engineering. We expect this method to be applicable to the observation and analysis of samples in materials science, biology and applied physics, and thus to contribute to a wide range of scientific, technological and industrial fields. Full article

Lead halide perovskites, including single-cation (MAPbI₃, FAPbI₃, CsPbI₃) and mixed-cation (Cs_0.12FA_0.88PbI₃, Cs_0.1MA_0.15FA_0.75PbI₃) compositions, are promising for both space photovoltaics and γ-ray detection due to their tunable optoelectronic properties. However, their response to high-energy radiation remains critical for reliable operation. We performed Monte-Carlo simulations using GEANT4 to investigate photon interactions (0.1–90 MeV) with perovskites of varying composition and thickness (1 cm to 1 μm). Results indicate that heavy atoms (Pb, I) dominate photoelectric absorption and scattering, broadly similar absorbed energies and event rates across compositions. Cs-containing perovskites exhibit slightly higher absorption and ionization, whereas FA- and MA-rich compositions show reduced photoelectric and Rayleigh scattering. Layer thickness strongly influences the radiation response: ultrathin films display fewer interactions with higher per-event energy, while millimeter-scale layers achieve efficient absorption and enable pair-production events at MeV energies. The sequence of dominant processes follows the expected energy dependence: photoelectric effect at low energies, Compton and Rayleigh scattering at intermediate energies, and pair production at high energies. These findings demonstrate that perovskite γ-interaction is primarily governed by heavy-atom content, with A-site cations fine-tuning the process balance, and that device performance for detection or photovoltaics depends critically on layer thickness. Full article

Optical frequency domain reflectometry (OFDR) is one of the key diagnostic tools for fiber optic components and circuits built on them. A low signal-to-noise ratio, resulting from the low intensity of backscattered signals, prevents the correct quantitative description of the medium parameters. Known methods of signal denoising, such as empirical mode decomposition, frequency filtering, and activation function dynamic averaging, make the signal smoother but introduce errors into its dynamic characteristics, changing the intensity of reflection peaks and distorting the backscattering level. We propose a method to reduce OFDR trace noise using elliptical arc fitting (EAF). The obtained results indicate that this algorithm efficiently processes both areas with and without contrasting back reflections, with zero distortion of Fresnel reflection peaks, and with zero attenuation error in regions without Fresnel reflections. At the same time, other methods distort reflection peaks by 14.2–42.6% and shift the correct level of Rayleigh scattering by 27.2–67.3%. Further work will be aimed at increasing the accuracy of the method and testing it with other types of data. Full article