Investigation of temperature actions on flat steel box girders of long-span bridges with temperature monitoring data

Tan

Measurement and Control

et al. 2021

The temperature distribution of the bridge and its thermal effect has always been an important issue for researchers. To investigate the temperature distribution and thermal stress in the steel-concrete composite bridge deck, a 1:4 ratio temperature gradient effect experimental study was carried out in this paper. First, a set of experimental equipment for laboratory temperature gradient loading was designed based on the principle of temperature gradient caused by solar radiation, the temperature gradient obtained from the measurements were compared with the specifications and verified by the FE method. Next, the loading of the steel-concrete composite deck at different temperatures was performed. The thermal stress response and change trend of the simply supported and continuously constrained boundary conditions under different temperature loads were analyzed. The experimental results show that the vertical temperature of steel-concrete composite bridge deck is nonlinear, which is consistent with the temperature gradient trend of specifications. The vertical temperature gradient has a great influence on the steel-concrete composite bridge deck under different constraints, and the extreme stress of concrete slab and steel beam is almost linear with the temperature gradient. Finally, some suggestions for steel-concrete composite deck design were provided based on the research results.

Section: Temperature Load Devicementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental study and numerical simulation of temperature gradient effect for steel-concrete composite bridge deck

Tan

Measurement and Control

et al. 2021

“…The block maximum method is a typical EVA method in practical applications [48]. The block maximum model is built up by 3 steps: (1) dividing all observations into k groups on average; (2) extracting the maximum value in each group for discussion; and (3) performing distribution analysis using the extracted maximum data.…”

Section: Determination Of Thresholdmentioning

confidence: 99%

Anomaly detection for large span bridges during operational phase using structural health monitoring data

Xu¹,

Ren²,

Huang³

et al. 2020

Smart Mater. Struct.

In view of the limitation of damage detection in practical applications for large scale civil structures, a practical method for anomaly detection is developed. Within the anomaly detection framework, wavelet transform and generalized Pareto distribution are adopted for data processing. In detail, to reduce the influence of thermal responses on signal fluctuations induced by anomaly events, wavelet transform is employed to separate thermal effects from raw signals based on the distinguished frequency bandwidths. Subsequently, a two-level anomaly detection method is proposed, i.e., threshold-based anomaly detection and anomaly trend detection. For the threshold-based anomaly detection, the threshold for anomaly detection is determined by generalized Pareto distribution analytics, corresponding to a 95% guarantee rate within 100 years. Moreover, the threshold is periodically updated by incorporating the latest monitoring data to model the increase of traffic volumes and gradual degradations of structures. For the anomaly trend detection, the moving fast Fourier transform is adopted for discussion. Finally, the mid-span deflection of Xihoumen Suspension Bridge is selected as the index to validate the effectiveness of the proposed methodology. Two types of anomaly events are assumed in the case study, i.e., the overloading event and structural damage. The two-level anomaly detection is implemented. It is indicated through the case study that the proposed anomaly detection approach (without the influence of temperature) is able to detect three 100-ton overloaded vehicles and damages in main cables. However, the assumed cases subject to 100-ton vehicle and damages in stiffening girders are hardly detected by using the deflection index, owing to the sensitivity of the index to each anomaly event. In the future studies, a structural health monitoring-based multi-index anomaly detection system is promising to ensure the operational and structural safety of large span bridges.

Advances in Structural Engineering

“…Traditionally, there are two main methods to analyze the temperature gradient model. The first method employs finite element method (FEM) to calculate the temperature field of the whole structure based on the theory of heat transfer (Deng et al, 2018; Tong et al, 2001; Zhou et al, 2016). While this method can provide the temperature model for the entire structure at any time, it requires huge computational cost to get the temperature gradient model for the girder’s service life.…”

Section: Introductionmentioning

confidence: 99%

Temperature gradient modeling of a steel box-girder suspension bridge using Copulas probabilistic method and field monitoring

Zhang

Liu

Deng³

2020

Self Cite

A novel copula-based probabilistic model is proposed to establish the temperature difference analysis model for a long-span suspension bridge’s steel box girder. The key idea is to express a two-dimensional function of the temperature difference in flat steel box girder by using copulas. The maximum and minimum values of daily temperature difference model was developed using long-terms structural health monitoring data. Then, the correlation between adjacent temperature differences is investigated using five types of copulas. Akaike information criterion (AIC) is used to select an optimal model from five types of copulas, and the optimal joint function (two-dimensional function) for steel box girder’s temperature difference is established. Finally, the structure’s temperature gradient model is extrapolated for the service life of the structure by using Monte Carlo method. Moreover, this paper discusses the temperature gradient models using five types of common copulas and four types of time-varying copulas. The result shows that the t-copula is the optimal function to build the two-dimensional functions for steel box girder’s temperature difference, and the temperature model along the transverse direction can offer useful information that is not available in the design codes.