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Bridge expansion joints (BEJs) in service are susceptible to damage from various factors such as fatigue, impact, and environmental conditions. While visual inspection is the most common approach for inspecting BEJs, it is subjective and labor-intensive. In this paper, we propose a novel methodology for detecting the fault status of BEJs, inspired by voiceprint recognition (VPR) based on audio signals. We establish an Artificial Neural Network to filter nonevent segments from low signal-to-noise ratio signals, achieving an AuC value of 0.981. We design and improve ConFormer VPR models with a multifeature aggregation strategy and cascade them to realize fault detection of BEJs. For three successive tasks in classifying environment sound types, vehicle impact types, and faults, the ConFormer VPR models achieve AuC values of 0.975, 0.925, and 0.886, respectively, demonstrating the feasibility of our methods for unmanned inspection of BEJs. In future research, the introduction of multiple types of damage and the implementation of benchmarking tests are planned to further enhance the capabilities of the system. [ABSTRACT FROM AUTHOR]

The fatigue crack at the rib-to-deck joint that initiated at the weld root and propagated through the deck plate is one of the most common and unfavorable crack types on orthotropic steel deck (OSD). To evaluate the fatigue performance of OSD during its life-cycle in a more accurate way, a numerical simulation method to reproducing the behavior of this type of crack was established based on linear elastic fracture mechanics (LEFM) in this paper. Firstly, the crack growth at the weld root was provided by the fatigue test using the beach marking method. Then, by adopting the proposed crack propagation simulation method, the crack growth in the test was simulated and the fatigue cracks growth life was predicted. Finally, some factors that may have a great influence on crack propagation behaviors were analyzed, including the lack of penetration defects (LOP) at the weld root, the angle between the crack surface and the deck plate, initial crack depth as well as crack aspect ratio. Accordingly, a practical approach was put forward to estimate the fatigue life based on the test, which can be applied to actual structures that are manufactured by the same process of the specimens, and the inspection and maintnenance works can be benefitted. [ABSTRACT FROM AUTHOR]

Multimodal tasks based on attention mechanism and language face numerous problems. Based on multimodal hierarchical attention mechanism and genetic neural network, this paper studies the application of image segmentation algorithm in data completion and 3D scene reconstruction. The algorithm refers to the process of concentrating attention that humans subjectively pay attention to and calculates the difference between each pixel in the genetic neural network test image in the color space and the average value of the target image, which solves the problem of static feature maps and dynamic feature maps of image sequences. In addition, in view of the problem that the number of attention enhancement feature extraction modules is too large and the parameters are too large, the recursive mechanism is used as the feature extraction branch, and new model parameters are not added when the network depth is increased. The simulation results show that the accuracy of the improved image saliency detection algorithm based on the attention mechanism reaches 89.7%, and the difference between the average value of the single-point pixel and the target image is reduced to 0.132, which further promotes the practicability and reliability of the image segmentation model. [ABSTRACT FROM AUTHOR]

This article proposes a deep convolutional neural network with perceptible generalization ability for structural topology optimization. The architecture of the neural network is made up of encoding and decoding parts, which provide down- and up-sampling operations. The popular U-Net was adopted to improve the performance of the proposed neural network. To train the neural network, a large dataset is generated by Simplified Isotropic Material with Penalization (SIMP). The performance of the proposed method was evaluated by comparing its efficiency and accuracy with SIMP on a series of typical optimization problems. Results show that a significant reduction in computation cost was achieved with little sacrifice to the performance of design solutions. Furthermore, the generalization ability of the proposed method is discussed. This ability enables the model to obtain a solution to a problem when a boundary condition is not included in the training dataset with a certain accuracy. [ABSTRACT FROM AUTHOR]

Under this background, this paper tries to find countermeasures and ways for carbon reduction by observing and analyzing the influencing factors of carbon emissions, designing ways to minimize carbon emissions and maximize resources and energy. In view of the above problems, the carbon emission prediction research is closely combined with the research of deep neural network, the carbon emission prediction models based on deep neural network are established, respectively, and the game theory is introduced to maximize the resource economy. Based on the analysis of the cost of energy resources, this paper puts forward a model based on game theory and makes an overall planning of the bidding online auxiliary decision-making system in combination with the actual market demand. Build a big data analysis platform based on the Internet of things, collect the data related to carbon emission for normalization, analyze the influencing factors related to carbon emission by using the principal component analysis method, select the data with higher connection value, and take the time series data as the input of the deep neural network for simulation verification. The simulation results show that the game model of carbon emission minimization and energy resource economic maximization based on deep neural network can effectively improve the economic maximization of energy resources and reduce carbon emissions. [ABSTRACT FROM AUTHOR]

To evaluate the crosswind stability (overturning and sideslip) of vehicles driving on the bridge, obtaining critical wind speed is essential. The traditional method is based on the aerodynamic forces of moving vehicles on the bridge and the analysis of force equilibrations. However, various shapes of the bridge make the flow field around the vehicle on the bridge very complicated to obtain. In this paper, a simplified method is introduced to calculate the critical wind speeds of moving vehicles on bridges based on the influence of coefficients of the wind environment on the bridge and the aerodynamic forces of moving vehicles on open fields. The aerodynamic forces of moving vehicles are simulated with dynamic mesh techniques. Besides, the characteristics of the wind environment on the bridge deck are studied to evaluate the driving safety and determine the influence coefficient. To further demonstrate the reliability, critical wind speed in different road conditions of the proposed simplified method shows very good agreement with the traditional method. [ABSTRACT FROM AUTHOR]

Topology optimization is computationally demanding for times of finite element analysis during iteration, especially for 3D structure optimization in intelligent design and construction, where a large amount of concept designs are executed. To this end, this paper proposes a deep Convolutional Neural Network (CNN) for 3D structural topology optimization, which can predict a near-optimal structure in negligible time without using any iterative scheme. To train the neural network, the Simplified Isotropic Material with Penalization (SIMP) method was adopted to generate the dataset of the optimized structures under the randomness loading conditions and volume fractions. The performance evaluation results show that compared with the SIMP method, the proposed method achieved a significant reduction in computation cost with little sacrifice on the performance of design solutions. Furthermore, the generalization ability of the proposed method trained on single boundary condition as well as multiple boundary conditions are explored. Finally, a stress-based topology optimization of the L-shape design domain is performed, which shows the portability of the proposed method to other more complex constraints. [ABSTRACT FROM AUTHOR]

In this paper, the Gram matrix is used to calculate the correlation of the filter response sets under different scale kernels learned by each layer of the network in the deconvolution, and the loss between the corresponding feature response correlations in the multilayer network is calculated. Linear summation is used to obtain a stable, multiscale image model representation. This paper extracts the contours of the salient areas of the image and adjusts the parameters of the deconvolution network to learn the salient area patterns of the image. At the same time, for the image to be generated, a shape template is used to limit the range of the area to be generated in order to obtain a shape image with similar patterns. When the spatial relative relationship characteristics of the image constituent objects are obvious, we appropriately add high-level semantic feature activation values for reinforcement. This paper solves the estimation of the unknown blur kernel by using image prior knowledge, filtering and gradient domain algorithms and other different technologies to obtain image jitter or scene movement information and estimate the size, location, and density of the blur kernel. This paper studies a relatively robust deconvolution model, which is insensitive to random noise, has stable effects, and can overcome the water ripple effect caused by the usual convolution process. This paper attempts to study the fuzzy model with variable space. The usual blur is a spatial invariant model; that is, a single kernel is used to describe the motion of all pixels on the image. By selecting different characteristic parameters, this paper conducts experimental research on some existing hydrophobic indicator function methods and calculates the relationship between characteristic parameters and hydrophobicity when different hydrophobic indicator functions are adopted. One characteristic of the hydrophobic image of composite insulators is low contrast. The traditional method of converting color images to grayscale images cannot improve the image contrast. This paper analyzes the hydrophobic image of the composite insulator, and the extracted B channel component image of the hydrophobic image improves the contrast of the image and facilitates the subsequent segmentation of water traces and background. In this paper, the water repellent image's watermark area is counted, and connected-domain wave processing is used to limit the area of water droplets retained, thereby improving the efficiency of filtering water droplets without having a big impact on the image as a whole. The problem of uneven illumination is an unavoidable problem in the field of image processing, and the resulting reflection problem brings difficulties to image processing. This article regards the reflective area of the watermark as a "hole" and uses the idea of "hole filling" to eliminate the reflective point, which weakens the reflection problem to a certain extent. [ABSTRACT FROM AUTHOR]

One gene could be transcribed to different RNA isoforms, and then produce various forms of protein sequences. This mechanism largely diversifies the cellular pool and allows natural selection to select from a wider range of substrates. In the cancer field, the isoform switches between tumor and normal tissues, such as the alternative splicing, stop codon read-through, or protein domestication, are significantly ignored by the traditional differential expression analyses. The intention of this work is to fill this gap. We collected public transcriptome and translatome data from ten patients with liver cancer, and performed genome-wide comparison on the stop codon read-through and protein domestication events. Both events diversify the proteome during long-term evolution. Surprisingly, we found that the tumor tissues globally have higher occurrence of stop codon read-through events as well as protein domestication events (translation signals of non-coding repetitive elements). These read-through and domestication events show limited overlapping across the ten patients, indicating the randomness of their occurrence and their deleterious nature. These tumor-specific events might have been purged by natural selection if they are not collected timely. Our work manifests the role of protein extension and domestication in liver cancer oncogenesis, adding new aspects to the cancer field. [ABSTRACT FROM AUTHOR]

Vehicle Load Monitoring (VLM) on entire long-span bridge decks presents significant challenges due to the spatial and temporal randomness of vehicles. Existing VLM systems often suffer from limited viewing coverage and poor continuity of multi-vehicle tracking methods. This paper proposes a VLM system consisting of multi-vision image pre-processing, modified YOLO-v4 model, kinematics-enhanced vehicle tracking algorithm, and data fusion method between vision and Weigh-In-Motion sub-systems. The system was tested on a long-span bridge using six cameras, achieving vehicle monitoring of entire deck. The precision of multi-vehicle tracking achieved 99.28% built upon YOLO-v4 model with 96.2% mean Average Precision (mAP). Comparative results demonstrate that the modified YOLO-v4 model outperforms state-of-the-art approaches, and our proposed tracking method surpasses other methods. Our proposed system offers a comprehensive solution for VLM on entire bridge deck, overcoming the limitations of existing methods. Future work could extend the system's capability to include complex traffic patterns. [Display omitted] • Multi-view video data are seamlessly integrated to broaden limited monitoring field. • Original YOLO-v4 is modified, achieving SOTA performance in vehicle detection. • Kinematics-based strategies are exploited to achieve high-precision vehicle tracking. • Intersection principle is proposed, fusing vision-WIM data accurately. [ABSTRACT FROM AUTHOR]

Owing to environmental and loading effects, complex processes of deterioration in structural performance will be encountered in the maintenance and management of long-span bridges during their service life. Therefore, the method of evaluation for acquiring the current status and trend in the deterioration of bridge performance is important. To improve the efficiency and objectivity of performance evaluations, the concept of standardization can be introduced to specify each step of the evaluation procedure. This paper presents a preliminary research framework for the standardization of performance evaluations for the Taizhou multi-pylon suspension bridge, which has special structural characteristics. This study is a part of a three-stage project on data standardization, evaluation, and retention. First, a framework with six core modules (action, structure, response, performance, indicator, and target) is established. Second, the relationship between these core modules and the performance evaluation procedure is discussed. Third, the content (e.g., definition and hierarchy) of each core module is described in detail. Finally, three examples (saddle sliding on top of middle steel pylon, concrete carbonation, and performance of middle pylon under extreme actions) are provided to demonstrate how the framework can be applied in performance evaluations of long-span bridges. [ABSTRACT FROM AUTHOR]

Timely wear evaluation is crucial in maintaining the functionality of bridge expansion joints (BEJs), ultimately ensuring the safety of bridges. Despite the significance of traffic load simulation (TLS) in simulation-based evaluation methods, existing TLS approaches face challenges in accurately modeling in situ traffic flow at a high fidelity. This paper presents a novel methodology and its application for evaluating the wear performance of BEJs, employing a Transformer-enhanced TLS approach. Initially, a tailored dataset is crafted for data-driven car-following modeling, leveraging an established spatial-temporal traffic load monitoring system. High-fidelity TLS with a mean absolute error (MAE) of 0.1738 m/s is then achieved using Transformer modules equipped with an attention mechanism. To evaluate the final wear life of BEJs, transient dynamic analysis and a calibrated finite element model of the bridge are employed to extract cumulative displacement. Additionally, a surrogate model is developed to depict the relationship between the hourly traffic weight on the entire bridge deck and the cumulative displacement of BEJs, yielding an impressive R-squared value of 0.96619. Comparative results demonstrate the superior performance of our proposed TLS approach over other data-driven approaches, with the linear model derived from our TLS approach outperforming the model generated by the conventional Monte Carlo-based TLS approach. To conclude, our proposed TLS emerges as a comprehensive and precise methodology for the wear evaluation of BEJs. [ABSTRACT FROM AUTHOR]

Suspenders play a crucial role in transmitting loads from the bridge deck to the main cable in a suspension bridge. They are susceptible to fatigue due to repeated dynamic loads, particularly traffic loads. Traffic Load Models (TLMs), typically created using Monte–Carlo simulation and Weigh-In-Motion (WIM) data, are employed to evaluate this fatigue. However, these models often overlook practical vehicle trajectories and spatio-temporal distribution, which compromises the precision of fatigue assessments. In this study, we introduce a novel 2D Intelligent Driver Model (2D-IDM) that incorporates actual vehicle trajectories, with a particular focus on transverse vehicle movement. This enhancement aims to improve the fidelity of existing TLMs. To provide a clear, qualitative, and quantitative understanding of the effects of fatigue evaluation with or without actual trajectory characteristics, we have structured this paper as a comparative study. We compare our proposed model, denoted as TLM S-3, with two observation-based models (O-1 and O-2) and two simulation-based models (S-1 and S-2). We conducted an experimental case study on a long-span suspension bridge, where the actual traffic load trajectory was obtained using a WIM-Vision integrated system. To calculate fatigue damage considering both longitudinal and transverse directions, we established a multi-scale Finite Element Model (FEM) using solid element types to simulate the bridge girder. This model can generate the stress influence surface of the bridge and has been verified in both static and dynamic aspects. Our detailed comparative analysis demonstrates the consistency of the proposed 2D-IDM with the actual measured traffic load trajectories. This indicates that our approach can enhance the fidelity and precision of fatigue evaluations for bridge suspenders. [ABSTRACT FROM AUTHOR]

Tinnitus is a widespread and serious clinical and social problem. Although oxidative injury has been suggested to be one of pathological mechanisms in auditory cortex, whether this mechanism could be applied to inferior colliculus remains unclear. In this study, we used an online electrochemical system (OECS) integrating in vivo microdialysis with selective electrochemical detector to continuously monitor the dynamics of ascorbate efflux, an index of oxidative injury, in inferior colliculus of living rats during sodium salicylate-induced tinnitus. We found that OECS with a carbon nanotubes (CNTs)-modified electrode as the detector selectively responses to ascorbate, which is free from the interference from sodium salicylate and MK-801 that were used to induce tinnitus animal model and investigate the N -methyl- d -aspartate (NMDA) receptor mediated excitotoxicity, respectively. With the OECS, we found that the extracellular ascorbate level in inferior colliculus significantly increases after salicylate administration and such increase was suppressed by immediate injection of NMDA receptor antagonist MK-801. In addition, we found that salicylate administration significantly increases the spontaneous and sound stimuli evoked neural activity in inferior colliculus and that the increases were inhibited by the injection of MK-801. These results suggest that oxidative injury may occur in inferior colliculus following salicylate-induced tinnitus, which is closely relevant to the NMDA-mediated neuronal excitotoxicity. This information is useful for understanding the neurochemical processes in inferior colliculus involved in tinnitus and its related brain diseases. [Display omitted] • We validated an OECS for in vivo sensing of the dynamics of ascorbate (AA) in rat brain with salicylate-induced tinnitus. • The increase of AA in inferior colliculus (IC) induced by salicylate implies the upregulated of oxidative stress in IC. • MK-801 can suppress the increase of AA suggesting the oxidative stress is relevant to NMDA-mediated neural excitotoxicity. • This study represents an example that how in vivo electrochemical sensing can be used to solve pathological questions. [ABSTRACT FROM AUTHOR]

[Display omitted] • SERS hybrid substrate with the sandwich structure was fabricated by a simple way. • Enhancement factors of up to 3.10 * 104 were achieved by adjusting the particle size. • Direct detection of trace amounts of pesticides on the surface of fruits is 10-9 g/ml. The overuse of mixed pesticides poses a threat to both the ecosystem and human health, yet general pesticide detection methods are complex in terms of steps, such as the need for pretreatment and cleaning. Surface-enhanced Raman scattering (SERS) has been used for real-life trace detection of residues due to its rapid detection and ultra-high sensitivity. Here, we prepared a novel Ti 3 C 2 Tx (MXene)-noble metal hybrid flexible substrate with a layer of MXene on top of flower-like Ag nanoparticles (AgNFs), and finally grew Au nanoparticles (AuNPs) by galvanic replacement and self-reduction reactions. The limit of detection (LOD) can be as low as 2 × 10-12 M by detecting 4-mercaptobenzoic acid (4MBA). For efficient sampling, transparent and flexible platform made of polydimethylsiloxane (PDMS) were used for the extraction and detection of thiabendazole (TBZ), thiram, methyl parathion (MP) and their mixtures. Notably, the lowest concentrations detected by swabbing on the tomato surface (3.7 ng/mL, 2.8 ng/mL) were lower than the EU maximum permissible limits of pesticides on raw fruits and vegetables (4.0 mg/L, 6.33 mg/mL). This high performance Ti 3 C 2 Tx-noble metal hybrid flexible substrate offers a great advantage in the trace detection of molecules. [ABSTRACT FROM AUTHOR]

[Display omitted] • The Au(x)@ZIF-Co/Zn photocatalysts have been designed. • The size effect of Au NPs have been revealed. • Catalyst has integrated function of photocatalytic degradation and SERS detection. • Two electron transfer path models was found in ZIF-Co/Zn photocatalysts. It is well known that gold nanoparticles have been widely used in various photo-redox reactions because of the unique surface plasmon resonance effect and the excellent internal electron transfer ability. However, the essential factors of how the metal nanoparticles enhancing the activity of photocatalysts have not been fully revealed. In this paper, gold colloidal particles of different sizes were modified on the surface of the dodecahedral skeleton of ZIF-Co/Zn. The photocatalytic activity of Au@ZIF-Co/Zn was investigated under simulated visible light for treating Rhodamine B/Cr(VI) mixture solutions (RhB/Cr(VI) 20 mg/L) and 4-nitrophenol solution (4-NP 20 mg/L). The results indicate that the size of gold nanoparticles could affect the surface plasmon resonance effect observably, internal electron transfer capacity and carrier density change. Photoelectric chemistry experiments and radical quenching experiments were performed to reveal the charge-transfer photocatalytic mechanism and size influence of gold nanoparticles in composite photocatalysts. This work may provide a novel strategy for the construction of metal–organic frameworks for the purification of wastewater mixed with heavy metal ions, organic pollutants and pharmaceutical intermediates. [ABSTRACT FROM AUTHOR]

Running vehicles cause disturbances in the surrounding air, which lead to a vehicle-induced aerodynamic load (VIAL) on roadside thin-wall structures. In this study, to reveal the aerodynamic load mechanism on roadside sound barriers subjected to the action of a vehicle-induced airflow, the Computational Fluid Dynamics(CFD) method is used to simulate the airflow around a running vehicle and adjacent to the sound barrier. First, the reliability of the numerical simulation is verified by comparing it with field tests. Second, using the CFD method, flow fields around the running vehicle with and without a sound barrier are obtained, the wind-pressure distribution is extracted, and the micro-mechanism of the sound barrier's influence on the airflow around the running vehicle is revealed by comparing and analyzing the flow-field distribution characteristics. Thirdly, through parametric studies, the changing rules of the wind-pressure distribution and the VIAL effect of internal force on the sound barrier screen are presented under different conditions, i.e., sound barrier height, vehicle shape, vehicle–barrier separation distance, and sound barrier shape. Then, using the FEM method, the load effect of vehicle-induced airflow on the sound barrier column is revealed. The conclusions improve the understanding of the action mechanisms of the vehicle-induced airflow on roadside sound barriers. [ABSTRACT FROM AUTHOR]

To explore the technological innovation efficiency of industrial enterprises above designated size and its influencing factors under the China's economic census industry classification, using the stochastic frontier approach to estimates the innovation efficiency of the 34 industry from 2008 to 2018. Taking the sales revenue of new products as the dependent variable, R&D capital stock and R&D personnel equivalent are taken as the independent variable, control variables are reasonably selected. The characteristics and influencing factors of innovation efficiency between industries are analyzed. The results show that the innovation efficiency of all industries in China is steadily improving, and the difference between industries is gradually narrowing. Industries with high innovation efficiency are related to future competition and national economy and people's livelihood, while industries with low innovation efficiency are concentrated in mining and supply industry. The low input and low output industries are in the majority. The influence of innovation capital input on output is greater than that of personnel input. The proportion of state-owned property rights and capital constraints have a negative effect on innovation output, while the sales income has a positive effect on innovation output. Therefore, China should further improve the innovation efficiency of industrial industries, adopt classified policies, and increase the number of industries with low input and high output. The conclusion of the paper is of reference value to the development of China's 14th five-year industry and the medium and long term planning. [ABSTRACT FROM AUTHOR]

In order to accurately predict the ice accumulation on bridge cables under two typical freezing rain conditions, rime and glaze ice, this paper proposes a numerical simulation framework based on the three-dimensional Messinger theory. Two technical challenges of determining the flow direction of unfrozen water and solving three-dimensional Messinger equations are solved in this research. Based on the outflow, mass was calculated according to the three-dimensional Messinger theory, and the flow direction of unfrozen water in each cell was determined by the resultant force of air shear stress and water film gravity. To solve the three-dimensional equations, an iterative method without finding the stagnation line was introduced. The final iced geometries were determined when the inflow mass ratio was satisfied with the converge criteria. Moreover, this modified numerical model was programmed and embedded into computational fluid software. For both two typical freezing rain conditions, the effects of temperature and wind speed on iced geometries were studied. The aerodynamic characteristics and galloping instability of bridge cables with different iced geometries were also investigated. These preliminary aerodynamic simulations can provide the basis for the wind-induced vibration analysis of the whole structure. [ABSTRACT FROM AUTHOR]

The LaBaCo2O5+δ−x wt.% Bi2O3 (LBCO-xBi2O3, x=10, 20, 30, and 40) were prepared as composite cathodes for intermediate-temperature solid oxide fuel cells (IT-SOFCs) via the conventional mechanical mixing method. The effect of Bi2O3 on polarization resistance, overpotential, and long-term stability of the LBCO cathode was investigated. An effective sintering aid for LBCO cathode, Bi2O3 not only lowers its sintering temperature by ~200°C, but also improves the electrochemical performance within the intermediate temperature range of 600–800°C. Electrochemical impedance spectroscopy measurements showed that the addition of 20wt% Bi2O3 to LBCO exhibited the lowest area-specific resistance of 0.020Ωcm2 at 800°C in air, which was about a seventh of that of the LBCO cathode at the same condition. At a current density of 0.2Acm−2, the cathodic overpotential of LBCO-20Bi2O3 was about 12.6mV at 700°C, while the corresponding value for LBCO was 51.0mV. Compared to B2O3–Bi2O3–PbO frit, the addition of Bi2O3 significantly improved the long-term stability of cathode. Therefore, LBCO-20Bi2O3 can be a promising cathode for IT-SOFCs. [ABSTRACT FROM AUTHOR]

Simple and effective measurement of Mg2+ in the brain of living animals is of great physiological and pathological importance. In this study, we report a facile yet highly selective colorimetric method for effective sensing of cerebral Mg2+. The method is based on rational design of surface chemistry of gold nanoparticles (Au-NPs) with functional molecules including 1,4-dithiothreitol (DTT) and cysteine, enabling the fine tuning of the surface chemistry of Au-NPs in such a way that the addition of Mg2+ into the Au-NPs dispersion could selectively trigger the change of the dispersion/aggregation states of Au-NPs. The strong chelation interaction between Mg2+ and the hydroxyls in 1,4-dithiothreitol and the co-existence of cysteine on the surface of Au-NPs could, on one hand, enable the selective colorimetric detection of Mg2+ and, on the other hand, avoid the aggregation of Au-NPs induced by DTT itself. As a result, the addition of Mg2+ into the dispersion of the Au-NPs containing both cysteine and DTT results in the changes in both the color and the UV-vis spectra of the Au-NPs dispersion. The signal readout shows a linear relationship of Mg2+ within the concentration range from 1 μM to 40 μM with a detection limit of 800 nM (S/N = 3). Moreover, the assay demonstrated here is free from the interference of some physiological species commonly existing in rat brain. Although Ca2+ could interfere with the detection of Mg2+ because of its strong chelation with DTT, it could be selectively masked by masking agent (i.e., ethyleneglcol-bis (2-aminoethylether) tetraacetic acid). By combining the microdialysis technique, the basal dialysate level of Mg2+ is determined to be 299.2 ± 41.1 μM (n = 3) in the cerebral systems. The method essentially offers a new method for the detection of Mg2+ in the cerebral system. [ABSTRACT FROM AUTHOR]

A series of solid solutions of 1-x(Bi0.85La0.15)FeO3–xPbTiO3 for x = 0.35, 0.4, 0.415, 0.43, 0.45, 0.47)(BLFPT) are prepared by the mixed oxide method. The X-ray diffraction analysis shows that BLF-PT has a single perovskite phase with mixed tetragonal and rhombohedral phases in x = 0.415. The dielectric constant and Curie temperature of BLF-PT for x = 0.415 is 836 at 102Hz and 419 °C, respectively. The remnant polarization and magnetization of x = 0.415 reach 39 μC/cm2and 0.03 emu/g, showing a coexistence of ferroelectricity and ferromagnetism in the vicinity of the morphotropic phase boundary. The structure refinement is used to explain the correlation between structural and multiferroic properties of BLFPT solid solutions, which may be due to the existence of the monoclinic and orthorhombic phases lies on both sides of morphotropic phase boundary. [ABSTRACT FROM AUTHOR]

The root-deck crack is one of the most concerned fatigue issues on orthotropic steel decks (OSDs) as it is unfavorable for the serviceability of the bridge while being difficult to detect. In this paper, the fatigue test was designed and carried out by using beach marking method to record the crack propagation process. By conducting microscopic examination on the fracture surface, it shows that the lack of penetration (LOP) at the weld root, combined with the high stress at that site, results in the fatigue crack initiation and propagation to penetrate the deck. Additionally, the fatigue assessment in terms of the S-N curves for such a failure mode was carried out. With comparison to other fatigue test results from the literature, it manifests the differences between the specimens failed due to root-deck crack and toe-deck crack, which can benefit the fatigue design of OSDs by giving a more specific and process-oriented results. [Display omitted] • Fatigue test with beach marking method is conducted on OSD specimens. • The crack growth process of the root-deck crack are revealed. • The fatigue strengths for root/toe cracks are compared. [ABSTRACT FROM AUTHOR]

Summary: Due to the absence of antifatigue design under vehicle‐induced aerodynamic load (VIAL) during the process of structural design, structural failures of noise barriers erected on urban highway viaducts have become a common issue in China. In this paper, a novel VIAL monitoring methodology is proposed, which can achieve a remote VIAL measuring only by analysis and application of the data from a traffic‐monitoring camera. To establish this methodology, a VIAL determinative model and a computer vision system for measuring the vehicle running characteristics are developed. The accuracy and reliability of this methodology have been validated by a field experiment. By comparing with the results of vehicle‐induced aerodynamic pressure (VIAP) from a sensor‐based wind pressure acquisition system, it was found that the systemic root mean square deviations of maximum and minimum values of VIAP were 12.13% and 10.10%, respectively. [ABSTRACT FROM AUTHOR]

The improved hybrid discretisation of volume integral equation (VIE) combined with the characteristic basis function method is proposed to analyse the scattering from complex dielectric objects in this study. To mitigate the excessive number of discrete elements which arise from the conformal discretisation on the complex dielectric objects, the hybrid discretisation is developed. For the conventional hybrid discretisation, the conformal Schaubert–Wilton–Glisson (SWG) basis functions are used to discretise the homogeneous regions, meanwhile, the non‐conformal half‐SWG basis functions are employed to discretise the boundary regions which separate different materials or multiscale structures. The hybrid discretisation takes advantage of the merits of both conformal and non‐conformal basis functions and improves the computational efficiency for solving the VIE. In our study, a kind of edge basis function defined within boundary tetrahedral elements substitutes for the SWG basis functions to model the boundary regions, leading to the further reduction on the number of basis functions. Moreover, the characteristic basis functions extracted from the low‐level basis functions are employed to construct the reduced matrix of which the size is considerably smaller than that of the system matrix derived from the VIE. Several numerical results are presented to demonstrate the accuracy and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Vortex-induced vibration (VIV) is a kind of wind-induced vibration that occurs at low wind speeds. The actual effect of VIV in bridges is different from that in wind tunnels and has a severe impact on traffic safety. Therefore, to guide the bridge management department in taking reasonable control measures in the initial stage of VIV and ensure that vehicles pass over the bridge safely, an identification model for VIV is established based on a large amount of data collected from Zhoushan Sea Crossing Bridge. Firstly, the wind field and vibration characteristic parameters of VIV are calculated based on data measured from 2014 to 2016 by anemometers and acceleration sensors. Then, by the big-data significant differences method and distribution function fitting analysis, two wind field parameters and two vibration response parameters are determined to serve as indexes in the identification of VIV. Finally, based on a parameter optimization algorithm, the VIV identification model is established and the data of 2017 are used to test the prediction model. The results show that the recognition rate of VIV is 89% and the identification model can be used to warn about the occurrence of VIV in practical engineering. • A new method to identify vortex-induced vibration of long-span suspension bridges by monitoring data has been proposed. • Wind field characteristics data and bridge vibration response data during vortex-induced vibration are fully analyzed. • The threshold range of four vortex-induced vibration identification parameters are performed. • Early warning and countermeasures classification during vortex-induced vibration can be achieved. [ABSTRACT FROM AUTHOR]

Owing to the slenderness and lightness of most modern footbridges, vibration serviceability assessment becomes a crucial issue in the design process. As one of the key factors, the vibration comfort criterion has an important influence on the assessment of the final result. However, there is an obvious lack of experimental studies in this field, especially regarding the pedestrians' perception of the induced vibrations. In this study, an experiment was conducted to investigate the pedestrians' perception of human-induced vibrations of footbridges. During the experiment, the subjects walked on a pathway that was mounted on top of a shaking table. By imposing sinusoidal excitations with different amplitudes and frequencies, the experiment aimed to determine the influence of the two factors on the walking people's perception. Based on the data collected, perception scales were proposed for both the vertical and lateral vibrations of the footbridge. The established scales comprise five levels that depend on the acceleration amplitude and the frequency. Finally, a comparison between the proposed scales, existing comfort criteria in the literature and international codes was carried out. [ABSTRACT FROM AUTHOR]

On the basis of massive data collected by the Weigh-in-motion (WIM) system of XiHouMen Bridge, analysis of fatigue-loaded vehicle models and theoretical fatigue life of U ribs butt weld of steel box girder are discussed in this paper. Firstly, basic vehicle information can be obtained from preliminary statistics of various types of vehicles data and the vehicles passing XiHouMen Bridge are divided into seven types based on the number of axles and axle groups. Secondly, the statistical distribution functions of gross vehicle weight under different loading conditions and wheelbase for each type of vehicle are developed to obtain the equivalent fatigue vehicle load. Then, the parameters of various types of fatigue-loaded vehicles are determined by combining the mathematic expectation of gross vehicle weight distribution with Palmgren-Miner fatigue damage accumulation theory. Finally, the seven types of fatigue-loaded vehicles are applied to the component-coupled finite element model of the steel box girders in XiHouMen Bridge and the theoretical fatigue life of the U ribs butt weld can be estimated. This research provides a reference to define the vehicle models for fatigue loading on steel box-girder bridges based on WIM data. [ABSTRACT FROM AUTHOR]

The lattice model is a discrete model that is typically used to simulate the fracture process of brittle materials. This review summarizes the main achievements during the development history of the state-of-the-art lattice model during the past 80 years from the theory and application viewpoints. It is found that the classical lattice spring model (LSM) can only simulate a fixed Poisson’s ratio. This problem has been partially or fully solved in developed versions of novel lattice models by using (1) extra nodal DOFs, (2) extra shear springs, (3) extra nonlocal energy parameters, and (4) higher dimensional normal springs. The lattice model has already been successively applied in simulations of fracture processes of different materials and under different loads. However, the applications in fracture analyses of metals, dynamic load-induced fracture, and real large-scale structures, are not sufficient. Innovative areas of future research in reference to the use of the lattice model in engineering practice include constitutive relations, failure criteria, anisotropic material modeling and efficient computing techniques to expand its use and range of applications. [ABSTRACT FROM AUTHOR]

Simultaneous recording of neurochemical signal and electrophysiological activity in the same brain region remains vitally essential to understanding the essences of physiological and pathological events because of the intrinsic chemical and electrical nature of communication between the neurons. However, the difficulty in selectively recording chemical signal with a high temporal resolution in chemically complex central nervous system presents a great challenge for achieving this goal. In this study, we demonstrate a method for simultaneous and real-time recording of ascorbate and electrical signals in live brain by using an integrated dual-mode microelectrode (IDMME), in which a single-walled carbon nanotube (SWNT)-modified carbon fiber microelectrode (CFME) was efficiently integrated with a glass microcapillary electrode. The SWNT-based CFME was served as an electrochemical recording channel to in vivo monitor cerebral ascorbate with a high selectivity and an improved temporal resolution, while the glass microcapillary electrode was employed as an electrophysiological recording channel for single-unit recording in the cerebral system. We found that no reciprocal interference between the two recording channels with the IDMME when constant-potential amperometry was employed for in vivo monitoring of ascorbate. The validity of the IDMME in neurochemical studies was illustrated by concurrently and real-time recording the dynamic changes of cortical ascorbate level and electrophysiological signal in the same brain region of live rats following ischemia/reperfusion. This study essentially offers an effective approach to in vivo monitoring of neurochemical and electrophysiological events in live brain, which is envisaged to be useful for understanding physiological processes involved in brain functions. [ABSTRACT FROM AUTHOR]

In this paper, an iteration-free method based on the convolutional neural network (CNN) is proposed to increase the computational efficiency of stress-based topology optimization (SBTO). The p-norm stress aggregation scheme is adopted to measure the global stress level, and the method of moving asymptotes (MMA) is utilized to generate a dataset consisting of various load conditions and volume fractions. A deep CNN based on U-Net architecture is constructed, and based on the generated dataset, different input tensors are designed to train the network to find the optimal input mode for the SBTO problem. With a well-trained network, the optimized structures can be generated in real-time without any iterations with little sacrifice on the performance of the design scheme. Finally, the deep learning-based SBTO method is extended to a 3D case, and the results show that the proposed method can realize near optimal 3D SBTO prediction using negligible calculation cost. • A real-time stress-based topology optimization method based on deep learning technique. • Given near-optimal or even outperforming structures in negligible time. • Achieved good results in accuracy and efficiency, both in 2D and 3D design domains. [ABSTRACT FROM AUTHOR]

Cable replacement has been commonly implemented to avoid its insufficient bearing capacity after long-term service. To guide better the cable maintenance and life assessment, the experimental studies on replaced cables are significant. As the fundamental step of replaced cable assessment, the corrosion examination of steel wires is required. The existing methods and systems mainly focus on the qualitative estimation and localization of corrosion, which is hard to fulfill the requirement of precise analyses. In this paper, a multi-vision scanning system is proposed to detect and represent the real corrosion and its distribution on the surface of a steel wire. Applied with a novel high-definition image scanning hardware and advanced panoramic image stitching processing algorithms, the surface 2D texture of a single steel wire can be scanned automatically. Afterward, by using the deep learning methods, the corrosion is precisely identified. Furthermore, non-uniformity indicators are proposed for the description of the apparent corrosion. The system has been verified and utilized in the inspection and evaluation of several steel wires from a replaced suspender. Due to it is effective and economical, the system is promising and serves as an instrument for both corrosion researches and structural assessment. [Display omitted] • Design and develop a novel flexibly extensible multi-vision system for visual examination of steel wires. • Deduct and accomplish the image processing algorithms for standard panoramic image acquisition of steel wires. • Propose the evaluation indicators reflecting the non-uniformity of corrosion by image identification of the panoramic image of steel wires. [ABSTRACT FROM AUTHOR]

This paper mainly demonstrates some experiences in China regarding surface damage inspection and performance evaluation of reinforced concrete (RC) bridges. To begin with, the mechanisms of the major damages of RC bridges such as chloride attack, concrete carbonation, and rebar corrosion are briefly reviewed. A statistical result of concrete cracking that exists in (prestressed) concrete bridges is presented as well. Second, the inspection practices of surface damages such as crack by using computer vision and deep learning on the RC pylons of the Jiang‐Yin Yangtze River bridge are demonstrated. Third, the specifications used in China for the performance evaluation of RC bridges are introduced. Its general philosophy and framework are explained. The Xia‐Men bridge is taken as an example to illustrate how to conduct a quantitative performance evaluation by following the instructions in China specifications. Finally, some perspectives on more advanced and efficient inspection techniques and performance evaluation methods are provided. [ABSTRACT FROM AUTHOR]

[Display omitted] • The composites of Bi 2 O 2 S/Bi 2 O 3 heterojunctions were prepared by a one-step method. • The prepared Bi 2 O 2 S/Bi 2 O 3 electrode sheets have good self-powered capability. • The Bi 2 O 2 S/Bi 2 O 3 heterojunction composites exhibit excellent performances in tetracycline photoelectrochemical detection. The overuse of tetracycline, a broad-spectrum antibiotic, has posed a severe threat to both the ecological environment and public safety. This paper presents the one-step synthesis of Bi 2 O 2 S/Bi 2 O 3 heterojunctions utilizing a simple and environmentally friendly chemical synthesis method. These heterojunctions were subsequently employed in the fabrication of photoelectrochemical sensors tailored for tetracycline detection. Under optimal conditions, with a bias voltage of 0 V, the sensor manifests exceptional self-powered capability, yielding a photocurrent density of approximately 270nA/cm2. The detection sensitivity for tetracycline spans a wide linear range from 0.1 pM to 200 nM, accompanied by a remarkably low detection limit of 0.5 pM (S/N = 3). Furthermore, the photoelectrochemical sensor demonstrates commendable stability, rapid response characteristics, high selectivity, and consistent detection reproducibility. These findings not only offer a novel opportunity for advancing photoelectrochemical sensors but also present a fresh perspective in the realm of photoelectrochemical sensor development. [ABSTRACT FROM AUTHOR]

[Display omitted] • ZnO-Pt @ AlN core shell UV photodetector synthesized by two general methods. • The photodetector based the core shell nanowire array displays faster response speed. • The enhancement mechanism was vitrificated by experimental and theoretical results. ZnO, a potential optoelectronic material, is attracting significant attention in ultraviolet (UV) photodetectors. However, low photoelectric conversion efficiency is a shortcoming because of its surface defect. In this paper, a plasmonic enhanced high speed UV photodetector was fabricated by ZnO-Pt@AlN core shell nanowires arrays using chemical vapor deposition (CVD) and magnetron sputtering methods. As shown in experiment results, the core shell nanowire arrays exhibit 3.7 times enhancement of UV emission and inhibition of visible emission by surface defect. In addition, compared to the pure ZnO nanorod array detector, the introduction of Pt nanoparticles and AlN shell layer resulted in a device with faster rising and falling edges (from 5.67 s to 3.09 s; from 41.18 to 0.32 s) as well as higher bright-to-dark current ratio (from 6.6 to 310.5). As shown in simulation results, the optical field would be localized in the shell of ZnO nanorods, and the ZnO-Pt@AlN core–shell structure can effectively improve the absorption of 365 nm UV light. In one word, this paper employs two general methods to improve the optoelectronic performance of ZnO, and obtains plasmonic enhanced high speed UV photodetector fabricated by ZnO-Pt@AlN core shell nanowires array as well as the mechanism of enhancement is explained. [ABSTRACT FROM AUTHOR]

• Segmental model test on cable-pylon anchorage with RSS connectors was carried out. • Application performance of RSS connectors was obtained. • Nonlinear FE models were established against the segmental model test. • Numerical analysis was conducted to reveal the interface shear mechanism. The Ordinary Headed Stud (OHS) connector has been widely used in the steel–concrete composite structures. In some cases, the shear stiffness of partial OHS connectors could be beyond the actual demand, resulting in the uneven distribution of connector shear force. Therefore, the authors proposed the Rubber-Sleeved Stud (RSS) connector to reduce the shear stiffness of OHS connectors and enhance the deformation ability of the steel–concrete interface. In order to investigate the shear mechanism of RSS connectors in the steel–concrete interface of cable-pylon composite anchorage, the segmental model test and Finite Element (FE) analysis were carried out. The connector shear force, steel–concrete relative slip and concrete pylon stress under typical RSS connector layouts were discussed. Research results show that the maximum shear force of stud connectors in the actual pylon could be decreased by 20% when RSS connectors are adopted in the steel–concrete interface. RSS connectors possess better deformation ability so that the strain difference between two shank sides of the RSS connector is significantly greater than that of the OHS connector. Furthermore, the shear mechanism of RSS connectors is affected by their layouts in the steel–concrete interface. The peak connector shear force can be respectively reduced by 14.3%, 28.8% and 33.7% when RSS connector ratio λ (i.e. ratio of RSS connector number to total connector number) equals to 0.28, 0.50 and 0.72 compared with λ = 0. The shear force range of stud connectors is simultaneously decreased. When the RSS connector ratio equals 0.72, the longitudinal and vertical slip ability are respectively raised by 22.5% and 25.0% compared with λ = 0. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) digital technology is essential to the maintenance and monitoring of cultural heritage sites. In the field of bridge engineering, 3D models generated from point clouds of existing bridges is drawing increasing attention. Currently, the widespread use of the unmanned aerial vehicle (UAV) provides a practical solution for generating 3D point clouds as well as models, which can drastically reduce the manual effort and cost involved. In this study, we present a semi-automated framework for generating structural surface models of heritage bridges. To be specific, we propose to tackle this challenge via a novel top-down method for segmenting main bridge components, combined with rule-based classification, to produce labeled 3D models from UAV photogrammetric point clouds. The point clouds of the heritage bridge are generated from the captured UAV images through the structure-from-motion workflow. A segmentation method is developed based on the supervoxel structure and global graph optimization, which can effectively separate bridge components based on geometric features. Then, recognition by the use of a classification tree and bridge geometry is utilized to recognize different structural elements from the obtained segments. Finally, surface modeling is conducted to generate surface models of the recognized elements. Experiments using two bridges in China demonstrate the potential of the presented structural model reconstruction method using UAV photogrammetry and point cloud processing in 3D digital documentation of heritage bridges. By using given markers, the reconstruction error of point clouds can be as small as 0.4%. Moreover, the precision and recall of segmentation results using testing date are better than 0.8, and a recognition accuracy better than 0.8 is achieved. [ABSTRACT FROM AUTHOR]

Highlights • A 3D lattice model is developed to simulate concrete carbonation. • 3D reconstruction technique is applied to obtain the shape of real coarse aggregate. • 2D simulation will underestimate the concrete carbonation process. Abstract A three-dimensional (3D) lattice type model was developed to simulate the concrete carbonation at the meso-scale. To construct the meso-scale concrete model, the 3D reconstruction technique was applied to obtain the shape of real coarse aggregates. Experimental data obtained from prior publications on cement paste, mortar, and concrete specimens were used to validate the developed lattice model of concrete carbonation. Based on a parametric study, it was then found that (1) the type and irregularity of the lattice network do not show obvious effects based on the simulation results of carbonation front, (2) a coarser lattice mesh will overestimate the carbonation process but the effect of the lattice mesh can be decreased by its refinement, (3) a two-dimensional (2D) simulation will underestimate the carbonation depth and the degree of underestimation increases as a function of the aggregate content, (4) the carbonation depth obtained from a 3D simulation can be 8–15% larger than that from a 2D simulation. [ABSTRACT FROM AUTHOR]

The composite structure composed of GO and Ag has better sensing ability and is widely used as SERS substrates. However, there are few studies on the influence of external environment such as light on the stability of GO and Ag composite structure. In fact, GO can effectively prevent Ag from oxidation, so it is necessary to deeply study the mechanism of GO protection. In view of this, we prepare Ag microspheres on glass slides by one-step reduction method, and spin-coated with GO as surface enhanced Raman scattering (SERS) strips for the detection of organic molecules R6G. The detection limit is as low as 10−12 M. The linearity of the detection results is significantly corrected by using the GO characteristic peak as the internal standard (IS). The effects of xenon lamp simulate sunlight irradiation on the SERS performance of Ag substrate and Ag/GO Raman strips are investigated comparatively. We find that the Ag/GO composite structure can maintain good stability without the influence of light compared to the Ag substrate. We discuss the dynamic variation of Ag and Ag/GO substrates during the light exposure. Bacterial inhibition experiments further demonstrate the protective effect of GO on Ag. The conclusions of this paper have potential applications for improving the stability of SERS substrates. [Display omitted] [ABSTRACT FROM AUTHOR]

• A multiple-cell section steel shell-concrete composite structure(SSC structures) for the bridge tower was proposed. • The uniaxial compressive tests of two specimens were conducted with different concrete strengths, and the experimental results were verified by nonlinear finite element simulation. • Failure modes and carrying capacity of specimens were conducted. • The load transfer mechanism and the influence of section form and material strength on bearing capacity were analyzed. To improve the mechanical performance and construction convenience of the bridge towers, a steel shell-concrete composite tower (SSC structures) was proposed. The steel shell consists of outer and inner steel plates, diaphragms, and stud connectors inside the cells. Then the high fluidity concrete is poured into the steel shell to form the composite tower. Through the uniaxial compressive tests of the specimens with different concrete strength and the nonlinear finite element parametric analyses, the force transfer mechanism of the steel shell, the infilled concrete, and the stud connectors at the steel–concrete interface were revealed. The results show that the proposed steel shell-concrete composite tower has a higher bearing capacity than the conventional concrete-filled steel tube tower, in which the bearing capacity of concrete was increased by about 20% from the test results due to the composite effect between steel and concrete. Diagonal breakage bands were formed when the specimens finally failed, on which the concrete was crushed, and the steel plates had large out-of-plane deformation and weld cracking. Through finite element calculation, it was found that the increase of stud forces mainly occurred after the yield of the steel wall plates, and the maximum values of the shear forces and tension forces were 3.6 kN and 4.7 kN, respectively. The results also show that the multiple-cell section has better mechanical performance than the double steel section, which is suitable for the section form of the composite bridge tower. [ABSTRACT FROM AUTHOR]

Pesticides are often overused in production and life, which harms the environment and human health. However, the current tools for detecting pesticides are not effective enough due to lower flexibility and stability. With regards to this, we synthesized a flexible substrate of PDMS modified by MXene (Ti 3 C 2 Tx)/Ag. The MXene-noble metal composite substrate can detect 4-mercaptobenzoic acid (4MBA) at a low concentration of 1.0 × 10−11 M. Furthermore, MXene can inhibit the oxidation of Ag nanoparticles (NPs) and efficiently localize the molecules to be tested within the hot spots. In particular, the flexibility of the substrate enables the detection of trace amounts of thiabendazole (TBZ) by collecting samples directly from uneven surfaces such as fruits and vegetables. The substrate is also capable of detecting a mixture of TBZ and 4MBA simultaneously. Using intrinsic Raman peak of PDMS as the internal standard can eliminate the influence of environmental factors on the detection results, which makes the detection results more quantitative. The resultant noble metal-semiconductor substrates show great potential applications in food safety and environmental monitoring fields. [Display omitted] • Synthesis of a noble metal-semiconductor (MXene/Ag/PDMS) substrate by a quick two-step method. • The substrate has excellent flexibility and stability and the signal of 4MBA is still stable after ten days. • The substrate can detect trace (10−8 g/mL) TBZ on fruit surfaces. • The substrate can simultaneously detect the mixed solution of TBZ and 4MBA. [ABSTRACT FROM AUTHOR]

Abstract: A partially encased composite I-girder with flat or corrugated web has been proposed to improve the structural performance of continuous composite girder under hogging moment. The flexural behavior of such structure under two points symmetric loading has been experimentally and analytically investigated. Static flexural loading tests showed that the partially encased girder improved bending strength in comparison to steel I-girder, as local bucking of steel flange was restricted by encased concrete. Especially for the corrugated web girder, the ultimate bending strength was improved about 20%, and the ductility also increased about 3 times. In addition, the limitation of width-to-thickness ratios for steel and concrete-encased composite I-girders with corrugated web were suggested to prevent premature failure due to local buckling of compressive flange. Moreover, the analytical methods of flexural strength under service and ultimate state for partially encased composite girder were proposed and verified with experimental results. It was found that the analytical bending strengths agreed well with the experimental ones at both service and ultimate state, which means the proposed analytical equations can be applied in predicting flexural strength accurately for such encased composite girder with flat or corrugated web. [Copyright &y& Elsevier]

For long-span composite bridges with corrugated steel webs, the encased concrete near the intermediate support section increases the weight of the girder, reduces pre-stressing efficiency, and causes difficulties in the construction process. The authors in the companion paper [1] proposed a corrugated steel web with vertical or/and horizontal stiffeners to replace or shorten the length of concrete encasement. In parallel with experimental study described in the companion paper, this paper further investigates the shear performance of proposed stiffened corrugated steel webs by numerical and analytical methods. Firstly, finite element (FE) models considering material nonlinearity, welding residual stress, and geometric imperfection were established and validated against the experimental results. Then the effects of web thickness, corrugation depth, height and thickness of stiffeners on shear strength and failure modes were analyzed based on the validated FE models. Finally, both experimental and numerical shear strength were used to evaluate the applicability of existing calculation methods proposed by different scholars to predict the shear capacity of stiffened corrugated steel web. The comparisons reveal that calculation methods proposed by Hassanein & Kharoob [2] and Leblouba et al. [3] predict the shear capacity of pure corrugated steel web more accurately, and all existing calculation methods underestimate corrugated steel web with vertical stiffeners. Therefore, the analytical model for accurately predicting shear strength of stiffened corrugated steel web need to be developed, which will be investigated in subsequent studies. • A new type of corrugated steel web with vertical or/and lateral stiffeners is proposed. • Shear behavior of steel I-girder with stiffened corrugated webs has been numerically investigated. • Non-linear finite element models considering residual stress and geometric imperfection were established and validated. • Applicability of current shear capacity calculation method for stiffened corrugated steel webs was evaluated. [ABSTRACT FROM AUTHOR]