SUMMARYMonitoring strain data provides possibilities for the fatigue assessment of the critical components in real structures under the operational conditions. This paper presents a case study on the investigation of fatigue performance of welded details. Long-term monitoring strain data of 4 years between 2006 and 2009 collected by the structural health monitoring system mounted on the Runyang Suspension Bridge and Runyang Cable-stayed Bridge are utilized. The study focuses on two aspects: (i) the effects of different strain components in the raw strain data on the fatigue damage assessment and (ii) the necessity of long-term strain measurement for fatigue evaluation. The results indicate that temperature effect on the stress range spectrum is negligible. The enormous low-level stress cycles caused by random interference would result in erroneous equivalent stress ranges and number of cycles, and thus should be eliminated from the stress range spectrum. Through in-depth analysis of monitoring strain data in three special months and in 3 years, respectively, it is revealed that short-term data monitored in a few days and medium-term data monitored in a few months are not adequate enough to reveal the actual fatigue behaviors of steel bridges and would give inaccurate fatigue life prediction. Finally, the fatigue life predictions of two types of welded details by considering traffic flow growth are carried out. Lessons learned from the long-term monitoring are expected to enhance our understanding in fatigue performances of steel bridges.
Summary
Serviceability issues related to service load deformations is of great importance to in‐service bridge maintenance decision making. Development in structural health monitoring brings opportunities to serviceability assessment for long‐span bridges. In this study, a reliability assessment framework of traffic‐induced vertical deflection is developed by incorporating extreme values analysis and system reliability with deflection measurements. The framework includes the following steps: (a) identifying traffic‐induced deflection by eliminating temperature component and extracting local extremes from the original measurements; (b) probabilistically modeling the peaks‐over‐threshold (POT) data to the generalized Pareto distribution (GPD); (c) selecting proper threshold of the GPD based on the mean residual life plot and goodness‐of‐fit tests; (d) extending the GPD to generalized extreme value distribution‐based extreme value distribution with the assumption of filtered Poisson process; and (e) assessing the serviceability reliability of vertical deflection by using the concept of series system. The multisensor deflection measurements, which were collected by a previously verified system installed on a suspension bridge, are processed and studied according to the proposed framework. The results indicate that the best GDP fitting of the POT data can be obtained due to the proposed threshold selection strategy. The quasisystem reliability approach also shows its ability in addressing the relationship between the reliabilities of the multiple sections equipped with sensors and presenting a reasonable overall reliability for the prototype bridge.
Hangers or suspenders of a suspension bridge are the primary load-carrying members and are vital to the structural integrity and service life of the bridge. Site-specific vehicle loads monitored by the weigh-in-motion system can assist to obtain the operational cyclic stresses of hangers. Differing from most existing studies, herein, a framework for fatigue performance investigation for hangers of suspension bridges is proposed utilizing the full information of the weigh-in-motion data. This framework includes four steps: (1) generate influence surfaces for hangers, (2) reconstruct vehicular loading flows based on the weigh-in-motion data, (3) calculate time histories of hanger tension forces, and (4) evaluate fatigue damages and predict fatigue lives. Critical issues, such as the loading configuration of trucks, the threshold of the gross vehicle weight, and the time step for stress calculation, have been studied and discussed in detail. Based on 8-month weigh-in-motion data of a prototype suspension bridge, it is shown that the fatigue damage of hangers can be evaluated day by day, and subsequently the fatigue lives can be predicted. The correlation between the fatigue damages and vehicular loads is also investigated in this study.
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.
This paper focuses on developing an online structural condition assessment technique using long-term monitoring data measured by a structural health monitoring system. The seasonal correlations of frequency-temperature and beam-end displacement-temperature for the Runyang Suspension Bridge are performed, fi rst. Then, a statistical modeling technique using a six-order polynomial is further applied to formulate the correlations of frequency-temperature and displacement-temperature, from which abnormal changes of measured frequencies and displacements are detected using the mean value control chart. Analysis results show that modal frequencies of higher vibration modes and displacements have remarkable seasonal correlations with the environmental temperature and the proposed method exhibits a good capability for detecting the micro damage-induced changes of modal frequencies and displacements. The results demonstrate that the proposed method can effectively eliminate temperature complications from frequency and displacement time series and is well suited for online condition monitoring of long-span suspension bridges.
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