Research Progress of Stress Measurement Technologies for Optical Elements

It is of great significance to measure the residual stress distribution accurately for optical elements and evaluate its influence on the performance of optical instruments in optical imaging, aviation remote sensing, semiconductor manufacturing, and other fields. The stress of optical elements can be closely related to birefringence based on photoelasticity. Thus, the method of quantifying birefringence to obtain the stress becomes the main method of stress measurement technologies for optical elements. This paper first introduces the basic principle of stress measurement based on photoelasticity. Then, the research progress of stress measurement technologies based on this principle is reviewed, which can be classified into two methods: polarization method and interference method. Meanwhile, the advantages and disadvantages of various stress measurement technologies are analyzed and compared. Finally, the developing trend of stress measurement technologies for optical elements is summarized and prospected

Predicting shear strength in UHPC beams through an innovative neural network with SHAP interpretation

Ultra-High performance concrete (UHPC) has garnered considerable attention in the construction industry due to its exceptional mechanical properties and durability. In the design of UHPC beams, accurately predicting shear strength is crucial. Inspired by the dense blocks in DenseNet, this paper proposes a novel neural network for predicting the shear strength of UHPC beams. A comprehensive database of UHPC beams was initially established through extensive literature data collection, amassing 619 experimental data samples. Preprocessing was subsequently conducted using mahalanobis distance (DM) to eliminate outliers. Subsequently, the database underwent detailed parameter analysis. In practical testing, the novel neural network model exhibited superior accuracy in predicting the shear strength of UHPC beams, surpassing traditional machine learning (ML) models and empirical formulas. Furthermore, it demonstrated excellent generalization capabilities, achieving an R2 value of 0.988 in the training set and 0.964 in the test set. The study introduced the shapley additive explanations (SHAP) method to conduct global and local interpretability analysis of the network model, demonstrating the contributions of each input parameter to the model predictions. Finally, based on this network model, a graphical user interface (GUI) was developed for researchers engaged in UHPC beam design, enabling users to easily input relevant parameters and obtain shear strength predictions. The findings of this study are expected to promote the application of ML models in predicting the complex nonlinear behavior of UHPC structures, providing strong support for engineering practice

Bond behavior and modeling of steel-FRP composite bars in engineered cementitious composites

The combination of the steel-FRP composite bar (SFCB) and engineered cementitious composite (ECC) holds favorable applications in terms of durable resilient structures. However, a clear understanding of the interfacial bond performance of this novel combination is currently lacking. Therefore, the bond behavior and mechanism of the SFCB-ECC interface were investigated through direct pullout tests. A total of 48 cube specimens were fabricated, with the test variables including bar type, bar diameter, embedment length, and matrix type. The experimental results indicated that the bond failure mode of SFCBs and FRP bars differed from that of deformed steel bars, attributed to the damage of resin-rich ribs in relatively high-strength ECC. The bond-slip curves revealed both the fundamental differences and similarities among steel bars, SFCBs, and FRP bars. The Poisson effect and shear lag effect increased with a decrease in bar stiffness and an increase in diameter. The combined impact of the interaction between the bar stiffness and diameter resulted in varying bond strengths for steel bars, SFCBs, and GFRP bars, despite their similar surface geometries. A theoretical model for the bond strength at the SFCB-ECC interface was derived using the thick-walled cylinder principle and subsequently validated with test data. Finally, a unified empirical model framework for predicting the bond strength of various bar-matrix combinations was proposed based on the theoretical model. The accuracy of this method was evaluated using a collected database

Full-Field Vibration Measurements by Using High-Speed Two-Dimensional Digital Image Correlation

This work developed a method that uses a single monochrome high-speed camera without sacrificing the spatial resolution to measure both in-plane and out-of-plane full-field vibrations. By using the high-speed camera and a two-dimensional digital image correlation (2D-DIC) algorithm, the method first extracts the out-of-plane displacement field from the measured virtual in-plane strains. Then it retrieves the in-plane displacement field after eliminating the out-of-plane motion-induced virtual component. For validation, in-plane and out-of-plane translation tests and single-frequency vibration experiments were carried out. The measurement results show good agreement with the reference values, indicating the effectiveness of the proposed high-speed 2D-DIC (HS-2D-DIC). Further, the natural frequencies and mode shapes of a rectangular cantilever panel were also measured successfully, exhibiting the method’s effectiveness in practical applications. Since the HS-2D-DIC requires only a single monochrome camera, no complex optical setup, and no complicated calibration process, the method can be developed as a competitive tool for full-field vibration characterizations

Tensile Strain and Damage Self-Sensing of Flax FRP Laminates Using Carbon Nanofiber Conductive Network Coupled with Acoustic Emission

The strain and damage self-sensing properties of carbon nanofibers (CNFs)/flax fiber-reinforced polymer (FFRP) laminates under tension were investigated via simultaneously measuring the changes of electrical resistance (ER) and acoustic emission (AE) signals. The piezoresistive mechanisms together with the damage evolution of CNFs/FFRP laminates were also explored. The results revealed that both ER and AE responses to tensile strains in CNFs/FFRP laminates could be segmented into three stages, which confirmed their good damage self-sensing ability. The isochronous and reversible electrical resistance responses to tensile strains proved the stability and repeatability of strain self-sensing capability for CNFs/FFRP laminates. Moreover, in-situ ER measurement is sensitive not only to new damages but also to existing damages, whereas AE signals are only sensitive to new damages. Therefore, adding a small amount of conductive CNFs into non-conductive FFRP laminates could provide an effective strategy to achieve the self-sensing ability in their strain and damage development

Advances in All-Solid-State Passively Q-Switched Lasers Based on Cr4+:YAG Saturable Absorber

All-solid-state passively Q-switched lasers have advantages that include simple structure, high peak power, and short sub-nanosecond pulse width. Potentially, these lasers can be applied in multiple settings, such as in miniature light sources, laser medical treatment, remote sensing, and precision processing. Cr4+:YAG crystal is an ideal Q-switch material for all-solid-state passively Q-switched lasers owing to its high thermal conductivity, low saturation light intensity, and high damage threshold. This study summarizes the research progress on all-solid-state passively Q-switched lasers that use Cr4+:YAG crystal as a saturable absorber and discusses further prospects for the development and application of such lasers

Effects of Intellectual Activities on Different Domains of Cognitive Function in Elderly People

Background Intellectual activities such as reading and playing puzzle games can slow the decline of cognitive function in the elderly, but the effects of specific types of such activities on cognitive function and cognitive domains need to be further studied. Objective To explore the influence of common types of intellectual activities on cognitive function and cognitive domains of the elderly in the community. Methods From May to August 2022, stratified convenience sampling was used to select elderly people from four communities in Nanjing, Changzhou, Nantong and Xuzhou of Jiangsu Province. A face-to-face survey was conducted with a general information questionnaire and the Montreal Cognitive Assessment (MoCA) Beijing edition to collect data regarding sociodemographics, frequency and types of intellectual activities, and cognitive function. Stepwise multiple regression analysis was used to explore the relationship between intellectual activities and different cognitive domains. Results In total, 782 cases attended the survey, and 758 of them (96.93%) who completed it were included for analysis, including123 from Nanjing, 197 from Changzhou, 240 from Nantong, and 198 from Xuzhou. The intellectual activities done by these older people include learning new knowledge (n=170), playing chess and cards (n=228), reading (n=228), singing (n=59), playing puzzle games (n=57), helping grand children with their homework (n=42), painting (n=16), playing a musical instrument (n=47), and practicing calligraphy (n=30). Stepwise multiple linear regression analysis showed that learning new knowledge, reading, helping grand children with their homework, playing puzzle games and playing musical instruments were associated with cognitive function (P<0.05). Learning new knowledge (B=0.250), reading (B=0.590), playing puzzle games (B=0.585), helping grand children with their homework (B=0.711), and playing musical instruments (B=0.643) were the influencing factors of Visuospatial/Executive (P<0.05). Learning new knowledge (B=0.219) was an influencing factor of Abstraction and Delayed recall/Memory (B=0.727) (P<0.05). Reading was a factor affecting Naming (B=0.095), Attention (B=0.207), Language (B=0.290), Abstraction (B=0.241), and Delayed recall/Memory (B=0.377) (P<0.05). Playing puzzle games (B=0.290) and playing musical instruments (B=0.278) were the influencing factors of Language (P<0.05). Among various types of activities, reading was included in a total of seven regression equations, with a standardized regression coefficient of 0.225 for its impact on the total score of MoCA, which was higher than that of the other types. Conclusion Intellectual activities such as reading, learning new knowledge, playing puzzle games, helping grand children with their homework and playing a musical instrument can maintain or improve the cognitive function of the elderly in the community. The effects of different types of intellectual activities on cognitive function are domain-specific, which has a positive significance for the prevention and intervention of cognitive function decline of the elderly

Convolution Error Reduction for a Fabry–Pérot-Based Linewidth Measurement: A Theoretical and Experimental Study

Linewidth measurement of a short pulse single-longitudinal mode laser with a low repetition rate has been a big challenge. Although the Fabry–Pérot (FP) etalon in combination with a beam profiler is an effective approach to measure the linewidth, the convolution error introduced by the inherent transmission spectrum width of an FP restricts the measurement accuracy. Here, the source of convolutional errors of the FP etalon-based linewidth measurement is analyzed, and the convolutional fitting method is proposed to reduce the errors. The results show that the linewidth measurement using the FP cavity with low reflectance (95%) can achieve the same resolution as that with high reflectance (99.5%) based on this convolution error reduction method. The study provides a simple approach to accurately measuring the linewidth of pulsed lasers, even with low energy