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Traffic load simulation (TLS) is critical for the design and assessment of long-span bridges. Traditional methods, such as Monte-Carlo sampling and Cellular Automaton, rely on actual traffic data for load generation and evolution. However, they often overlook in-lane transverse movements, which are vital for precise bridge component assessment. This paper presents a TLS framework that incorporates in-lane transverse movements for long-span bridges. We select eight parameters as input features for a Transformer-based deep learning model, designed to predict both longitudinal and transverse vehicle speeds. The TLS process begins with spatial-temporal traffic load monitoring on the target bridge. Monte-Carlo sampling generates vehicle data, and the trained Transformer model simulates traffic evolution. A case study on a 1490-meter main-span suspension bridge illustrates the proposed method. Traffic trajectories were captured using a multi-vision system and reconstructed to minimize errors. The Transformer model was trained with optimized hyperparameters, enabling the completion of TLS on the entire bridge deck. We also compare the performance of other deep learning models, evaluate the accuracy of transverse distribution in TLS, and discuss its potential applications in future bridge assessments. The proposed TLS method enhances current practices by accurately simulating transverse vehicle positions on bridge decks, thereby improving the fidelity of microscopic traffic simulations and enabling more precise fatigue damage assessments of bridge components.

ABSTRACTA 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 [...]

Vehicle detection and classification (VDC) is a crucial aspect of bridge engineering, as vehicles exert significant dynamic loads on bridges. Various contact and noncontact methods have been proposed for VDC, but finding a durable and cost-effective sensing approach remains challenging for practical bridge applications. In this study, we propose a voiceprint recognition (VPR) method for VDC using a single microphone, offering flexibility and affordability. The distinctive acoustic signatures generated by vehicles impacting bridge expansion joints (BEJs) are captured and utilized for VDC. We optimize a threshold-based algorithm for vehicle detection and a deep learning-based VPR model for vehicle classification. In addition, cascading VPR models enable fine-grained vehicle classification, including lanes and axle types. We validate the proposed method on an actual bridge. The short-term energy (STE) thresholding algorithm achieves a detection accuracy and recall of 90.0% and 91.6%, respectively. The ConFormer model achieves an area under the curve (AuC) of 0.925 for vehicle classification. These results highlight the method as an easy-to-implement and cost-effective solution for efficient VDC surveys. Future work can focus on expanding datasets and incorporating multiple microphones to further enhance the system’s capabilities.

In this study, nonlocal gradient and divergence operators are introduced to eliminate the dependence on the derivation of the kernel function in smoothed particle hydrodynamics (SPH) and improve the numerical stability and interpolation consistency. Eulerian consistent SPH equations for weakly compressible viscous flows are derived, and a new laminar viscosity model is proposed. Several benchmark problems were reproduced using the developed code, demonstrating the accuracy of the proposed method. Finally, this method was applied to simulate a lid-driven cavity problem at different Reynolds numbers (Re). The results obtained were compared with those of the existing literatures, exhibiting good consistency and demonstrating its reliability in viscous flows simulation.

This paper presents a novel nonlocal numerical paradigm for a class of general nonlinear ordinary differential equations using the peridynamic differential operator. Differential governing equations and initial/boundary conditions are reformulated from the local differential form to the nonlocal integral form using a meshless orthogonal technique. The solution domain is partitioned into a finite number of points, of which the properties are obtained through weighted summation over the corresponding properties of neighboring points. Using the Lagrange multiplier method and the variational principle, nonlinear ordinary differential equations with initial/boundary conditions can be solved through the Newton–Raphson iteration method. Moreover, the differences between the proposed method and other methods are illustrated by comparing several impact factors. Furthermore, three benchmarks, including the Riccati equation, the Poisson equation, and the fluid flow equation, have been solved to show the applicability and accuracy of the proposed numerical method, and the results are consistent with the numerical results in the previous literature. Finally, the proposed method is applied to the galloping vibration problem to reveal the galloping mechanism.

This paper proposes a non-local Eulerian particle method coupling with immersed boundary method (IBM) for fluid–structure interaction (FSI) problems. In the Eulerian particle method, the partial differential forms of governing equations are transformed into integral forms using peridynamic differential operator (PDDO). Symmetric particle distribution is applied in the Eulerian particle method, enhancing the efficiency and stability of the algorithm. By introducing the IBM framework into the original Eulerian particle method, we can obtain a new coupling method, which could solve problems with moving bodies inside fluid and extend the applicability of the Eulerian particle method. The numerical procedure of the proposed hybrid method is detailed. The proposed method is then applied to three benchmark problems: 2D flow around a steady rectangle/moving square and an impulsively started rigid plate inside a rectangular box filled with water. The results capture the flow characteristics of these problems, showing the proposed method's stability and accuracy.

Purpose: Insulin resistance (IR) is common in patients with polycystic ovary syndrome (PCOS). Metabolic syndrome (MS) includes, inter alia, IR, hypertension, dyslipidemia, and disturbances in glucose metabolism. The triglyceride–glucose (TyG) index and non-traditional lipid parameters are strong predictors of IR and cardiovascular disease and can be considered as screening indicators for MS. This study aimed to evaluate the predictive potential of non-traditional lipid parameters and the TyG index to identify MS in PCOS. Methods: This cross-sectional study included 134 women diagnosed with PCOS (50 patients with comorbid MS and 84 patients without MS). Biochemical indices were collected, and triglycerides (TG)/high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC)/HDL-C, low-density lipoprotein cholesterol (LDL-C)/HDL-C, non-HDL-C, TyG, and TyG–BMI indices were calculated. Logistic regression analysis was used to compare and determine the association of the six parameters with MS, and the receiver operating characteristic (ROC) curve was used to evaluate the performance of each parameter in identifying MS in the PCOS population. Results: After adjusting for age and body mass index (BMI), TG/HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C, TyG, and TyG–BMI were associated with MS (all P<0.05). The odds ratios were 4.075 (0.891, 1.107), 3.121 (1.844, 5.282), 3.106 (1.734, 5.561), 2.238 (1.302, 3.848), 13.422 (4.364, 41.282), and 1.102 (1.056, 1.150), respectively. TG/HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C, TyG, and TyG–BMI are effective predictors of MS in PCOS, and their cut-off values can be used for the early detection of MS. TyG–BMI had the strongest performance in predicting MS (area under the curve 0.905, 95% CI 0.855–0.956), and its optimal critical value for predicting MS was 202.542. Conclusions: TG/HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C, TyG, and TyG–BMI are novel, clinically convenient and practical markers for the early identification of MS risk in PCOS patients.

ABSTRACT This paper proposed a novel cost-effective movable hybrid GFRP and concrete deck consisting of corrugated pultruded GFRP plate with T-upstands for the tension part and concrete with reinforcing bars [...]

Abstract: The composite bridges with corrugated steel webs have excellent properties, such as lightness of girders, efficiency of introducing prestress forces, short construction period, optimum force distribution, good seismic performance, and aesthetics appearance etc., which have greatly promoted the application of such bridges. The objective of this paper is to provide and summarize important references related to the analysis, design and construction of composite bridges with corrugated steel webs. Subjects discussed in this review include (1) structural configuration and application; (2) shear behavior; (3) bending behavior; (4) torsional behavior; (5) patch loading resistance; (6) dynamic behavior; (7) long-term behaviors including fatigue and creep; (8) component connections; (9) analysis method and theory; (10) new concept application. The literature survey presented herein mainly focuses on papers written in English, Japanese, German and Chinese in relation to composite bridges with corrugated steel webs.

ABSTRACTReynolds numbers play an important role in fluid dynamics, because flow separations and reattachments are often Reynolds-number dependent, even if the bodies have sharp edges. To satisfy Reynolds scaling in experiments, the model scale can be very large. Computational fluid dynamics (CFD) provides an interesting alternative to wind tunnel tests, especially when Reynolds effects have to be assessed for a design stage. In this paper, the particle strength exchange (PSE) of vortex methods is introduced for assessing Reynolds number effects on bridge deck cross-sections. For this purpose, this study analyses how the aerodynamic forces of two different bridges sections are influenced by these effects. The computation results with PSE are compared with wind tunnel tests. The relation between Strouhal numbers and Reynolds numbers are also analyzed and compared with experimental results. All the results show that the particle strength exchange method can be efficiently used to calculate Reynolds effects on 2-dimensional bridge deck sections.

Abstract: Ten specimens are tested to investigate the cyclic behavior of beam-to-column joints of steel frames with joint panels. The performances of the joints with respect to strength, rigidity, and hysteretic performance are examined. Three different load-carrying mechanisms can be identified. Panel resistance ratio (R p ) is presented for predicting the buckling patterns. The validity ofR p is confirmed through the present experimental results. On the basis of the experimental results of steel beam-to-column moment joints, 3-D nonlinear finite element models are established to analyze the mechanical properties of these connections. The load-displacement curves of the finite element analysis are in good agreement with those of the tests in terms of strength and unloading stiffness. A shear lag phenomenon was captured in the beam flanges by not only experimental results but also numerical analysis. Parametric studies are conducted on the connections under monotonic loading to investigate the influences of connection dimension, resistance ratio on the connection behavior. It was found that the failure modes are influenced by the resistance ratio, while the thickness of joint panels resulting in large effects on the strength and stiffness under shear failure mode.

Based on investigation of linear fatigue-damage accumulation theory and fracture mechanics, a deterministic assessment approach was first proposed, in which the fatigue failure behavior of existing steel bridges was reflected. Furthermore, according to the stochastic fatigue failure mechanism of existing steel bridges, member fatigue reliability assessment models were proposed using probabilistic fracture mechanics. The deterministic and probabilistic assessment methods proposed in this paper were applied to evaluate the remaining fatigue life and service safety of two case study bridges. According to assessment results, the safe inspection intervals and maintenance strategies were determined, which can control and avoid fatigue failure accidents and unnecessary repairs or replacements.

By using a computer program especially developed for externally prestressed concrete bridges, the stress variation of external tendons under live load in several typical spans of externally prestressed concrete box-girder bridges is analysed. The influence of span-to-depth ratio, the level of bonding between external tendons and the structure, and the spacing between deviators on externally prestressed concrete simply-supported bridges is discussed. The influence of the construction method, the ratio of external tendons to internal tendons, the number of continuous spans, and the layout of external tendons on externally prestressed concrete continuous bridges is investigated. The comparison of results between externally prestressed concrete bridges to similar conventional internally prestressed concrete bridges is also made.

The mechanical performance degradation of concrete in marine environments is often caused by multi-hazard, such as long-term environmental loads and short-term extreme loads, which also lead to more complex damage pattern. This study presents a thermal-mechanical coupling phase field meso‑scale model to simulate the damage evolution process of concrete subjected to rebar corrosion and fire hazards. This model employed a fracture phase-field model to characterize damage progression in concrete and utilized thermal expansion strain, temperature-dependent material property phase field-dependent thermal conductivity to realize the coupling of temperature field, mechanical field, and phase field. We validated the proposed model with examples of concrete fracture, fire-induced damage and fire-induced mechanical property degradation. Subsequently, we simulated the fire-induced damage in corrosion-damaged concrete with varying corrosion-induced damage extents and aggregate volume fractions, which involves two steps: (1) simulation of damage induced by corrosion; (2) utilizing results as initial conditions for subsequent simulation of fire-induced damage. Simulation results indicate that fire-induced damage originates in the interfacial transition zone and propagates radially, ultimately resulting in a failure pattern of mesh cracks and local spalling. The corrosion-induced damage extent influences the fire-induced damage evolution process, spalling location and fire-induced damage extent, while the aggregate volume fraction primarily affects damage extent. Finally, we further researched and compared the fire-induced damage of corrosion-damaged concrete with one middle rebar, one corner rebar and multiple rebars. [ABSTRACT FROM AUTHOR]