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Cable-stayed bridges have been commonly used on high-speed railways. The design, construction, and maintenance of cable-stayed bridges necessitate an accurate assessment of the cable temperature field. However, the temperature fields of cables have not been well established. Therefore, this research aims to investigate the distribution of the temperature field, the time variability of temperatures, and the representative value of temperature actions in stayed cables. A cable segment experiment, spanning over one year, is conducted near the bridge site. Based on the monitoring temperatures and meteorological data, the distribution of the temperature field is studied, and the time variability of cable temperatures is investigated. The findings show that the temperature distribution is generally uniform along the cross-section without a significant temperature gradient, while the amplitudes of the annual cycle variation and daily cycle variation in temperatures are significant. To accurately determine the temperature deformation of a cable, it is necessary to consider both the daily temperature fluctuations and the annual cycle of uniform temperatures. Then, using the gradient boosted regression trees method, the relationship between the cable temperature and multiple environmental variables is explored, and representative cable uniform temperatures for design are obtained by the extreme value analysis. The presented data and results provide a good basis for the operation and maintenance of in-service long-span cable-stayed bridges. [ABSTRACT FROM AUTHOR]

• An efficient approach is explored to evaluate the extreme response and reliability of train-bridge interaction system. • The extreme response of an innovative railway integral bridge considering various stochastic excitations is studied. • The failure probability of high-speed train running safety conditional on wind speed and running speed is assessed. • The in-site long-term wind field measured data are applied to improve the assessment accuracy. The randomness of responses in a train-bridge interaction (TBI) system induced by stochastic track irregularity and crosswind has been addressed. However, the extreme value distribution (EVD) and reliability prediction of TBI system are little known. Due to the complexity of TBI system, the prediction approach is critical to the issues of extreme value and reliability evaluation, involving the computational accuracy and efficiency. Thus, the Monto Carlo-based global maximum method, probability density evolution-based virtual time process method (VPM), and average conditional exceeding rate method (ACERM) are considered in this study. The optimal approach for the EVD prediction of bridge buffeting responses and the TBI system with or without the consideration of crosswinds is identified. An innovative 3 × 70 m integral bridge is chosen as the study case, which is an emerging type of bridge structures used in the Chinese high-speed railway lines. Its extreme responses under the single and dual stochastic excitations of track irregularity and wind turbulence are fully investigated in this study. The study results show that the VPM and ACERM are efficient and accurate to evaluate the extreme responses of a TBI system. The ACERM is recommended in assessing the train running safety due to its high computational efficiency and reasonable accuracy. When the crosswind is not a consideration, the high-speed train running safety can be ensured with high probability if the train travels on the integral bridge below the design speed of 350 km/h. However, the failure probability of wheel-rail lateral contact forces reaches 51% if predicted under the mean wind speed of 30 m/s and train speed of 120 km/h. Finally, the advantages of the integral bridge over conventional bridges (e.g., continuous girder bridge) are discussed. [ABSTRACT FROM AUTHOR]

• The randomness of track irregularity and wind turbulence is considered to evaluate the extreme value distributions of high-speed train-bridge interaction system under crosswinds. • To obtain the accurate wind parameters used in the extreme analysis, the turbulence characteristic is analyzed based on the long-term wind field measurement near the bridge site. • The applicability of PDEM based virtual time process method to the extreme responses evaluation of train-bridge interaction (TBI) system is validated by comparing with Monto Carlo Method. • The Weibull distribution model (Type 3 of the generalized extreme value distribution) can be used for the extreme value evaluation of TBI system. This conclusion may be useful to the other similar analysis about extreme responses of TBI system. Deterministic safety curves of safe train running speeds versus mean wind speeds (MWSs) have been studied in the time domain, considering the train-bridge interaction (TBI) dynamics. However, the randomness of track irregularity and wind turbulence makes the extreme response of the TBI system indeterministic; and so does the safety curve. Therefore, an extreme evaluation theory based on the probability density evolution method (PDEM) is adopted in this study to investigate the extreme response distributions of TBI system under crosswinds with the consideration of the field measured turbulence characteristics. The applicability of the theory on train-bridge wind interaction system is verified first, followed by the discussion on the variations of extreme responses of train and bridge versus MWSs and running speeds of trains running on a high-speed railway cable-stayed bridge. A probabilistic safety curve is finally determined based on 40 cases with the wind speeds ranging from 10 m/s to 45 m/s and the train speeds ranging from 200 km/h to 400 km/h. The study analyses demonstrate the computational accuracy and efficiency of the PDEM-based extreme theory applied to the TBI system; and indicate that the extreme responses of high-speed trains and Quanzhou Bay Bridge increase with increasing MWSs and train speeds. In addition, most of performance indicators do not exceed the code-stipulated failure criteria except the train unloading factor and the lateral displacement at the mid-main span. The probabilistic safety curve for the studied bridge is thus deduced according to these two controlling indexes. [ABSTRACT FROM AUTHOR]

The non-Gaussian property of turbulence has been emphasized in some measured wind data. However, the classic Scanlan buffeting theory with the Gaussian distribution assumption of turbulence may cause errors in predicting the structural extreme response. In this study, a hybrid approach for predicting bridge's extreme buffeting response is proposed and validated, which considers multi-dimensional non-Gaussian random variables. Then the extreme buffeting response of a cable-stayed bridge under the attack of non-Gaussian wind is investigated, where the in-situ measured wind data of Typhoon ' Bailu ' is adopted. The sensitivity of extreme buffeting response to turbulence skewness and kurtosis is also analyzed. The study results show that the lateral and vertical buffeting displacements are in skewed distributions under the attack of Typhoon ' Bailu '. Compared to the Gaussian wind assumption, the non-Gaussian typhoon decreases the lateral extreme response, while increases the vertical extreme response. The results from the sensitivity analysis reveal a strong correlation between the non-Gaussian intensity of component u and that of the lateral buffeting response. In addition, the lateral extreme buffeting response increases significantly with the skewness and kurtosis of component u at a high probability level. • The non-Gaussian property of Typhoon ' Bailu ' is fully investigated from the perspective of probabilistic statistics. • A hybrid approach for predicting bridge's extreme buffeting response is proposed and validated • The effect of the non-Gaussian typhoon on the extreme buffeting response of a cable-stayed bridge is addressed. • The sensitivity of the extreme buffeting responses to the non-Gaussian intensity is comprehensively investigated. [ABSTRACT FROM AUTHOR]