An effort is currently underway to create an Engineering Research Consortium Initiative (ERCI) focused on engineering and management of the highway transportation infrastructure. The goal of the ERCI will be to provide administrative and logistical support for a coordinated, problem-focused research program on the highway transportation infrastructure system. The cornerstone of the initiative will be field test-sites. Example sites might include major long span bridges, sample populations of operating bridges, decommissioned bridges, a regional network of highways and bridges, various types of pavement and geotechnical structures, or a major transportation hub serving a metropolitan area. Sites would be instrumented to collect a broad range of engineering (structural, geotechnical, hydraulic), human (traffic) and natural (climatological, seismological) response data. The field sites would be networked to provide real-time access to test facilities across the country; a secure central repository would be established for collecting data from the sites. The data and information gathered from these sites would be used by engineers and scientists to study the complex interactions and cause-and-effect relations of the various engineered, human and natural components of the highway hyper-system. A major research thrust of the ERCI will be security of the highway infrastructure system, with particular emphasis on bridges. The National Science Foundation and the Federal Highway Administration are expected to provide funding for the program through a joint agency initiative. Two workshops were recently held with experts from around the world to discuss the plans for the ERCI. The paper provides more details on the ERCI and the status of the effort to date.
Proc. SPIE. 4337, Health Monitoring and Management of Civil Infrastructure Systems
KEYWORDS: Genetic algorithms, Aerospace engineering, Monte Carlo methods, Telecommunications, Damage detection, Genetics, Chemical elements, Optimization (mathematics), Environmental sensing, Binary data
A method is presented for detecting damage in a clamped-clamped beam based on redistribution of dead load in the member. The approach is based on measuring static strains due to dead load only, at three locations on the beam. In the event of damage (modeled as a local reduction in flexural stiffness at a single location in the beam) the bending moment in the beam redistributes and is no longer symmetric. Using the measured strains, a genetic optimization algorithm is used to determine the location and severity of damage in the beam. Four different damage scenarios are tested, these include: no damage (to test for false positive results); varying levels of damage near mid-span; equal levels of damage near the support, quarter point and mid-span; and damage near the support with 'noisy' measurement data. The technique is found to work well under a broad range of circumstances: the accuracy and success of the method depends on the damage location and the level of measurement noise in the data. Damage near the support and center of the beam can be identified with good accuracy. As one might expect, damage at or near to the point of inflection in the beam is more difficult to identify because the dead load strain in this vicinity is small. The technique is found to work well even with measurement noise on the order of 3 to 5%.
A long-term, structural health monitoring system has been designed and installed on the firs polymer composite bridge to be built in Delaware. The system is designed to monitor and record strains and deflections of the bridge, and the temperature and humidity of the surrounding area. Two types of information are gathered, 'monitor' data and 'event' data. The monitor data records very slow gradual changes in the bridge behavior, while the event data captures the bridge response due to truck loads. The system has been on- line since June, 1998. Sample result are presented in the paper of event and monitor data. The event data shows that the transverse strain of the deck is greater than the longitudinal strain, by a factor of about 1.5, and that the absolute deflection of the deck at mid-span is due mostly to the deflection of the edge girder. Monitor data from a one month period is presented that shows the thermal variations in strain due to daily temperature changes, and the gradual, changes due to the average daily temperature. The long-term monitoring system should provide valuable data for assessing the long-term performance and durability of this unique polymer composite bridge.