A large number of our nation’s bridges must be replaced or are in need of major repair/rehabilitation because they do not conform to current demands due to deterioration caused by aging or environmental conditions, heavier vehicles and increased traffic volume. Since a replacement alternative usually involves high costs and/or substantial interference with the normal traffic flows, strengthening is many times one of the most effective alternatives. As many bridges remain in continuous service despite aging and associated potential for damage accumulation and/or collapse, the Federal Railroad Administration (FRA) has identified as one of its strategic priorities the health monitoring of these structures to ensure a safe mode of operation. As such, a research program funded by FRA was initiated at the University of Missouri Rolla (Missouri S&T). The main objectives of this research program are as follows: (1) demonstrate the use of fiber reinforced polymers (FRP) composites in the repair/rehabilitation of railroad steel bridges with highly corroded steel members, and (2) health monitoring of railroad steel bridges to ensure a safe mode of operation of these bridges.

Compared to the application of FRP composites to other traditional materials, research examining the prospects of the combination of FRP and steel has been limited. Considering the fact that many bridges that are in need of rehabilitation and strengthening are steel bridges, it is imperative to increase the amount of research in this area. In this research project, the following strengthening issues applied to steel structures were investigated; (i) bond characterization, (ii) flexural strengthening, and (iii) strengthening of highly corroded axially loaded steel members using carbon FRP (CFRP). Development of health monitoring technologies capable of continuously monitoring the structural performance of the civil infrastructure on a real-time basis is becoming an important research area. In this research program, the main components used in the development of a field deployable remote system for health monitoring consisted of: (i) wireless sensors for data collection, and (ii) soft computing tools for data processing, which involved classification, decision, pattern recognition and process control of the collected data.