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Environmental factors, such as temperature, traffic, and wind, play an important role on the variations of dynamic properties of long-span cable-stayed bridges. The dynamic characteristics of Sutong Cable-Stayed Bridge (SCB), including acceleration and strain responses as well as modal frequencies, are investigated using one-year continuous monitoring data under operating conditions by the structural health monitoring system. The in situ wind characteristics and structural temperature behavior of SCB are also analyzed.More than 99% of the wind speed values are smaller than 16 m/s; and the largest temperature variation of the main girder exceeds 60°C. Besides, acceleration and strain, root mean square (RMS) data are both normalized using the Z-score standardization method. Relation analysis between the normalized acceleration and strain RMS values is conducted based on the time-history comparison and linear least square fitting. Results show that both of the processed acceleration and strain RMS values could properly describe the variation trend of the traffic load, although variation amplitudes of the two normalized parameters differ from each other. In addition, one-year continuous modal frequencies of SCB are identified using Hilbert-Huang transform method.Variability analysis of the structural modal frequencies due to environmental temperature and operational traffics is then conducted. Results show that temperature is the most important environmental factor for vertical and torsional modal frequencies. The traffic load is the second critical factor especially for the fundamental vertical frequency of SCB. Research results could provide references for damage detection and safety evaluation for similar long-span cable-stayed bridges.

This paper investigates the seismic performance of bridges installed with a sliding-lead rubber bearing (LRB) isolation system subjected to near-fault earthquakes. A three-span continuous bridge isolated with sliding-LRB system is used as an example. Nonlinear time history analyses are conducted to investigate the sensitivity effects of isolation period, friction coefficient and sliding displacement limit on the bridge responses. The responses of the sliding-LRB system are compared with those of the conventional LRB system. The results show that the base forces of the piers can be reduced by employing proper friction coefficients. However, the residual displacement of the sliding-LRB system may be larger compared with that of the conventional LRB system. To overcome this disadvantage, an improved solution to reduce the residual displacement is proposed with its effectiveness investigated. It was also demonstrated that the residual displacement and peak displacement can be effectively reduced by employing the shape memory alloy devices in the sliding-LRB system without significantly increasing the base forces.

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Summary Obtaining timely information about the health of civil infrastructure is critical to ensuring safe and reliable operation. Structural health monitoring has been proposed as a means to provide such information; however, most structural health monitoring systems provide only raw data, rather than actionable information. It is necessary to develop automated modal analysis strategies that can provide near real‐time dynamic information regarding the in‐service state of a bridge, which is essential to vibration control, finite element model calibration, and damage detection for safety and serviceability condition assessment. This study presents an automated framework to extract structural modal parameters from the stabilization diagram using a parametric modal identification method such as stochastic subspace identification. The framework focuses on the automated modal analysis issues of an in‐service long‐span bridge with close‐frequency modes. The presented framework is validated using experimental tests of a 1.8‐m 18‐story laboratory model. Subsequently, data from Sutong Cable‐Stayed Bridge are employed to demonstrate its potential usage in the field. Finally, an application of the automated framework is presented to identify and track the modal parameters of the deck of Sutong Cable‐Stayed Bridge for 20 days. Results show that the presented framework can successfully extract the structural modal parameters with good accuracy and robustness, hence can provide a reliable technical support for in‐service monitoring of long‐span bridges.

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