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Frequency‐dependent nonlinear process in microresonators is widely acknowledged, but there is no theory available to calculate the conversion efficiency for each resonance of the ring, except for the phase‐matching one. Similarly for azimuth‐dependent nonlinear process in birefringent rings, there is a lack of theory to analysis the conversion efficiency for each azimuth of the ring. Consequently, it leads to old‐fashioned or ill‐considered coupling position and inefficient energy conversion in birefringent microrings. Here, the study introduces spatio‐temporal coupled‐mode equation to describe mode spatial properties in the cavity, compensating for the deficiency of temporal coupled‐mode equation in describing sophisticated responses. By this equation, it is found that over a wide frequency range, the extremely strong second‐harmonic generation of TE modes can be achieved at different azimuth under different pumps in an X‐cut lithium niobate microring, as proved by a 440 000%/W conversion efficiency in a non‐poling ring recently. This theory is important for realizing an efficient entangled quantum light source, for example. Meanwhile, it will provide new ideas and guidelines for design and applications of monolithic birefringent photonic integrated circuits with high energy efficiency. [ABSTRACT FROM AUTHOR]

Modal parameter estimation is crucial in vibration-based damage detection and deserves increased attention and investigation. Concrete arch dams are prone to damage during severe seismic events, leading to alterations in their structural dynamic characteristics and modal parameters, which exhibit specific time-varying properties. This highlights the significance of investigating the evolution of their modal parameters and ensuring their accurate identification. To effectively accomplish the recursive estimation of modal parameters for arch dams, an adaptive recursive subspace (ARS) method with variable forgetting factors was proposed in this study. In the ARS method, the variable forgetting factors were adaptively updated by assessing the change rate of the spatial Euclidean distance of adjacent modal frequency identification values. A numerical simulation of a concrete arch dam under seismic loading was conducted by using ABAQUS software, in which a concrete damaged plasticity (CDP) model was used to simulate the dam body's constitutive relation, allowing for the assessment of damage development under seismic loading. Utilizing the dynamic responses obtained from the numerical simulation, the ARS method was implemented for the modal parameter recursive estimation of the arch dam. The identification results revealed a decreasing trend in the frequencies of the four initial modes of the arch dam: from an undamaged state characterized by frequencies of 0.910, 1.166, 1.871, and 2.161 Hz to values of 0.895, 1.134, 1.842, and 2.134 Hz, respectively. Concurrently, increases in the damping ratios of these modes were observed, transitioning from 4.44%, 4.28%, 5.42%, and 5.56% to 4.98%, 4.91%, 6.61%, and 6.85%%, respectively. The correlation of the identification results with damage progression validated the effectiveness of the ARS method. This study's outcomes have substantial theoretical and practical importance, facilitating the immediate comprehension of the dynamic characteristics and operational states of concrete arch dam structures. [ABSTRACT FROM AUTHOR]

The stress behavior of key parts of concrete dams is related to the safe operation of the dam. However, the stress sensors in concrete are susceptible to aging and failure with increasing service life. Estimating the structural stress under sensor failure or data loss scenarios for concrete dams in service is essential and complex. This study presents a stress estimation method driven by the observation data. Firstly, a one-to-one correspondence exists between dam deformation reflecting the load effect and structural stress. Estimating the structural stress by simulating load effects with dam deformation is more convenient when it is hard to simulate complex load effects directly. Therefore, based on the observed data before stress sensor failure, the spatial–temporal relationship between structure stress and multi-point deformations of a concrete dam is developed using convolutional neural networks (CNN) and long short-term memory (LSTM). An improved particle swarm optimization algorithm combined with swarm information entropy (SIE–APSO) is proposed simultaneously for tuning the network's hyperparameter and accelerating the convergence. Finally, the stress estimation of the target part of the concrete dam in service is obtained. The case shows that it is valid and feasible. The RMSE decreased by approximately 21–58%, MAPE decreased by 19–58%, and ARV decreased by 22–94% compared with the load-stress relationship model. [ABSTRACT FROM AUTHOR]

Recent studies in dam displacement monitoring primarily focus on single‐response monitoring or model updating using advanced techniques. Few studies involve the combination analysis of displacement with other synchronized responses utilizing their monitoring characteristics. In situ strain data provide a strength‐safety perspective for dam displacement monitoring. The challenge lies in that estimating displacement directly using limited discrete strain data may be misleading. This paper analyzes the relationship between displacement and global, and multipoint local strains from the perspective of the differences in load effects of gravity dams, and indicates that introducing appropriate state factors improves the estimation. A displacement estimation model driven by strain data and state factors is developed using stacked convolutional neural network, and the variable relationships within the model are interpretated via accumulated local effects. Incorporating specific strength criteria, a novel displacement monitoring indicator based on the tensile safety of the dam heel is proposed. A case study of a gravity dam showcases the effectiveness of the proposed approach in comparison with the solely strain‐based model and the traditional hydrostatic‐seasonal‐time factors‐based model. [ABSTRACT FROM AUTHOR]

Abstract: SnO2–ZnO/polyaniline (PANI) composite thick film for NO2 detection was fabricated from SnO2–ZnO porous nanosolid and PANI by a conventional coating method. The SnO2–ZnO composite porous nanosolid was prepared by a solvo-thermal hot-press (SHP) method. It was found that the composite sensor has high selectivity and response to low concentration NO2 gas. Furthermore, the composite sensor also showed high stability to NO2 over a long working period at low optimum working temperature (180°C). The response and recovery times of SnO2/PANI composite sensor (SZ20-P) were as short as about 9 and 27s to 35ppm NO2 at 180°C, respectively. The experiment results show that both the pore structures of SnO2 porous nanosolid and the content of ZnO had effects on the sensor response of SnO2–ZnO/PANI composites, and the optimum content of ZnO was 20wt.%. The possible sensing mechanism was discussed. [Copyright &y& Elsevier]

Phase change materials (PCMs) are attracting more and more attentions as enabling materials for tunable nanophotonics. They can be processed into functional photonic devices through customized laser writing, providing great flexibility for fabrication and reconfiguration. Lithium Niobate (LN) has excellent nonlinear and electro-optical properties, but is difficult to process, which limits its application in nanophotonic devices. In this paper, we combine the emerging low-loss phase change material Sb 2 S 3 with LN and propose a new type of high Q resonant metasurface. Simulation results show that the Sb 2 S 3 -LN metasurface has extremely narrow linewidth of 0.096 nm and high quality (Q) factor of 15,964. With LN as the waveguide layer, strong nonlinear properties are observed in the hybrid metasurface, which can be employed for optical switches and isolators. By adding a pair of Au electrodes on both sides of the LN, we can realize dynamic electro-optical control of the resonant metasurface. The ultra-low loss of Sb 2 S 3 , and its combination with LN, makes it possible to realize a new family of high Q resonant metasurfaces for actively tunable nanophotonic devices with widespread applications including optical switching, light modulation, dynamic beam steering, optical phased array and so on. [ABSTRACT FROM AUTHOR]