Yongtao Bai

This study addresses the need for an accurate damage model to represent the nonlinear degradation behavior of steel assemblies under axial cyclic loading. The proposed model is developed based on the theory of lumped damage mechanics (LDM) and structural mechanics, simplifying buckling and associated damage by focusing on plastic hinge effects in the central region of axial steel members while treating the rest as elastic beams. The model's predictions were validated against experimental results, demonstrating its capability to accurately forecast hysteresis curves, energy dissipation, and the onset of buckling. The findings indicate that the model effectively captures the nonlinear degradation of strength and stiffness in axial steel members, including phenomena such as compressive buckling‐induced deterioration, tensile yielding, the Bauschinger effect, and stiffness degradation. These results underscore the model's potential applicability in practical engineering scenarios, offering a computationally efficient alternative to traditional finite element methods for analyzing large‐span bridges and grid structures.

Truss structures with obvious periodical repetition in civil engineering are commonly used in long-span bridges and large-span buildings. Based on phononic crystal theory, periodical repetition structures have the potential to develop elastic wave bandgaps, which conduct noise attenuation or novel nondestructive testing. However, there needs to be more current knowledge about the engineering truss structures bandgaps and their potential applications. This study investigates the elastic wave bandgaps and transmission characteristics of two typical engineering truss structures analytically and numerically. We first decoupled the unit cells from the large truss structures. Then, we proposed a standard analytical model to get the dispersion relationship of the truss structures. The analytical dispersion relationship is verified by the finite element method. The results show that truss structure A could generate a bandgap from 1032 to 2065 Hz, while truss structure B could generate bandgaps from 982 to 1980 Hz. The mode analysis further reveals that the bandgap mechanism is Bragg scattering rather than local resonator. We verified the elastic wave transmission characteristics through frequency domain analysis, which agrees well with the bandgaps. To exhibit how the bandgap of the truss structures conducts noise attenuation and potential applications in nondestructive testing, we employ two case studies to illustrate the propagation of noise waves and the novel nondestructive testing for periodical truss structures. The results show that the two truss structures could attenuate noise waves. Defects in truss structures could conduct abnormal transmission, which could be applied in novel nondestructive testing.

Long‐span bridges face the significant challenge of deteriorating life cycles under fatigue loads. A new macroscopic damage mechanics model for rod hinge elements has been proposed to quantify the predamage of bridge beams subjected to high‐cycle fatigue. This model introduces predamage variables to evaluate the damage evolution process prior to fatigue crack initiation, enabling the prediction of moderate deterioration in bridges that cannot be monitored during their service life. By comparing the fatigue test results and predamage simulation results of simply supported composite beams and continuous composite beams, it was found that the error between the model predictions and the test results is relatively small. This result confirms the reliability of the model. The predamage model has been implemented as a self‐programming subroutine for numerical analysis. Taking the Daxi River Bridge as the engineering background, this predamage model was applied to practical engineering. Combined with typical traffic loads, a predamage assessment was conducted on its dangerous points. The dangerous beam segments of the bridge were taken and the damage values were calculated using a predamage subroutine model. The results obtained had a small error compared to the damage values of the corresponding beam segments in the full bridge simulation. The proposed high‐cycle fatigue predamage subroutine model offers a valuable reference for predicting fatigue damage in bridges.

In this paper, evaluation of wind‐induced vibration and travel comfort of the long‐span suspension bridge were comprehensively conducted based on multisource monitoring data. The wind field distribution and turbulent characteristics during the normal and vortex‐induced vibration (VIV) period were comparatively revealed. It reveals that the bridge experienced vertical VIV due to the long‐duration wind with specific speed perpendicularly acting on the girder, which cannot be predicted by the turbulence intensity and gust factor. Meanwhile, dynamic response evolution, VIV lock‐in effect, modal identification, and wavelet spectrum were further explored based on displacement and acceleration. The VIV frequency was consistent with a natural frequency of the bridge, whose mode can been determined by the deflection correlation heat map. The VIV was due to periodic vortex shedding generate aerodynamic forces, and the reaction of the structure vibration on vortex shedding can cause the vortex shedding frequency to be “locked” over a considerable range of wind speeds. According to driving visual safety and vibration tolerance, it is indicated that such VIV of the bridge may lead to the very discomfort for driving and pedestrian can tolerate short‐term vibration in this period. Comfort evaluation for the bridge during the VIV should be further improved accuracy and reliability, which can contribute to emergency response to VIV situations. Note that a certain degree of discomfort may occur under normal vibration conditions, which raises doubts about the reasonableness of the limit value.

Multiaxial fatigue failure of metals, a common issue in industrial production, often leads to significant losses. Recently, many researchers have applied deep learning methods to predict the multiaxial fatigue life of metals, achieving promising results. Due to the high costs of fatigue testing, training data for deep learning is scarce and labor-intensive to collect. This study meets this need by creating a large-scale, high-quality dataset for multiaxial fatigue life prediction, consisting of 1167 samples from 40 materials collected from literature. The dataset includes key mechanical properties (elastic modulus, yield strength, tensile strength, Poisson’s ratio) and 48 loading paths, along with additional relevant information (composition ratios, processing conditions). Common deep learning models validated the dataset’s effectiveness. This dataset aims to support researchers applying deep learning to fatigue life prediction, addressing the long-standing issue of data scarcity, thereby advancing the intersection of artificial intelligence and metal fatigue research.

Seismic metamaterials can attenuate seismic waves before reaching the city, providing earthquake protection to all buildings in the city. However, although several seismic metamaterials have been proposed, full-scale seismic metamaterials are hardly manufactured and tested due to large mass or excessive height, even in the lab. In this study, we develop a novel high-rigid steel lattice seismic metamaterial with low-frequency bandgap by ordinary angle steels, which is impossible for the mainstreamed resonators metamaterial. A new coupling model of the beam and the solid is proposed to get the dispersion relationships and transmission characteristics. We found that the developed seismic metamaterial generates a bandgap near 10 Hz and could decrease the peak ground acceleration by more than 80%. Then, we conduct a full-scale in-situ experiment to exhibit the manufacturing and verify the wave attenuation. The experiment results indicate that the developed seismic metamaterial could attenuate surface waves, which agrees with the bandgap. The research has resulted in a solution for new earthquake protection for cities and critical infrastructure thanks to low-frequency wave attenuation and easy full-scaled manufacturing.