Structural Health Monitoring of a Cable-Stayed Bridge Using Regularly Conducted Diagnostic Load Tests

The management and maintenance of cable-stayed bridges represents a major investment of human and financial capital. One possible approach to reducing the cost while simultaneously improving the process is by utilizing structural health monitoring (SHM) systems to enable diagnostic load tests to be regularly and efficiently conducted. The Indian River Inlet Bridge (IRIB), a 533-m long cable stayed bridge, was opened for traffic in 2012. From the very early stages of the design process, the Center for Innovative Bridge Engineering (CIBrE) at the University of Delaware (UD) worked with the Delaware Department of Transportation (DelDOT) and their design-build team of Skanska and AECOM to plan and install a comprehensive structural health monitoring (SHM) system. The SHM system is a fiber-optic based design with more than 120 sensors of varying type distributed throughout the bridge. The system, which not only collects data continuously during normal operation, has also been utilized during regularly scheduled controlled diagnostic load tests being used to monitor ongoing bridge performance. This paper presents results from a unique series of six diagnostic load tests which have been performed over the first 6 years of the bridge's service life (just prior to the bridge's opening, and then again at 6 months, 1, 2, 4, and 6 years). The results of this extended set of diagnostic load tests have enabled the bridge's baseline performance to be rigorously established. This in turn has provided the opportunity to develop a process for conducting future biennial tests to and adding their results to an evolving database, thereby enhancing DelDOT's ability to operate and maintain the bridge

Bridge Load Rating and Evaluation Using Digital Image Measurements

9A3551847103The use of digital imaging and other vision-based measurements offers many options for conducting load tests and obtaining the necessary data without having direct contact on the bridge via mounted sensor arrays. The results from this study revealed the sensitivity and accuracy of displacement measurements when compared to measurements from conventional string potentiometers mounted directly to the flange of the girder and 3D point cloud measurements. While there is not one optimal technique for measuring structural displacements based on a video, different techniques have different performance levels, and the applicability of these various methods may vary from case to case. The goal of this study was to compare the performance and accuracy of vision-based displacement measurements in the form of load testing on two bridges in Delaware, and how the data can be used to calibrate finite element models to assess bridge performance based on in-situ conditions. Results from the two diagnostic loads tests are presented. Using the data collected, results are compared to AASHTO live load distribution factors. A finite element bridge model is generated in ABAQUS and calibrated using the field measurements obtained from digital imaging. From the findings, a process to evaluate live load distribution using displacements obtained from vision-based measurement techniques is presented. Lessons learned and the impact of the vision-based measurement techniques deployed for load testing and evaluation are also presented

A System for Calibration of the Marshall Compaction Hammer

DTFH61-92-Y-30052The Marshall method is used by many State and local highway agencies for the design of hot-mix asphalt. Although the procedure is specified by several industry standards, round-robin testing programs have confirmed wide variability in Marshall results. Much of the scatter in the data is attributed to compaction hammer variables, such as variation in drop weight, drop height, friction, hammer alignment, pedestal support, and foundation. To reduce the variability in the test results, an easy-to-use and relatively inexpensive system has been developed for the calibration of mechanical Marshall compaction hammers. This system consists of a spring-mass device with force transducer, power supply, and data acquisition system. The spring-mass device replaces the standard specimen mold during calibration. Force-time histories from multiple hammer blows are recorded and analyzed to determine average peak force, energy, and cumulative impulse. Using this information, a proposed calibration procedure has been developed. The procedure involves adjusting the number of blows to achieve a standard cumulative impulse. A limited laboratory evaluation program has been completed to demonstrate the system. The variability of test results for specimens prepared in calibrated machines was reduced by as much as 60%, as measured by the reduction in standard deviation and range of data for 15 specimens. A draft calibration standard has been developed and formatted according to AASHTO standards