Precast Concrete Elements for Accelerated Bridge Construction Final Report, Volume 1-1. Laboratory Testing of Precast Substructure Components: Boone County Bridge, January 2009

In July 2006, construction began on an accelerated bridge project in Boone County, Iowa that was composed of precast substructure elements and an innovative, precast deck panel system. The superstructure system consisted of full-depth deck panels that were prestressed in the transverse direction, and after installation on the prestressed concrete girders, post-tensioned in the longitudinal direction. Prior to construction, laboratory tests were completed on the precast abutment and pier cap elements. The substructure testing was to determine the punching shear strength of the elements. Post-tensioning testing and verification of the precast deck system was performed in the field. The forces in the tendons provided by the contractor were verified and losses due to the post-tensioning operation were measured. The stress (strain) distribution in the deck panels due to the post-tensioning was also measured and analyzed. The entire construction process for this bridge system was documented. Representatives from the Boone County Engineers Office, the prime contractor, precast fabricator, and researchers from Iowa State University provided feedback and suggestions for improving the constructability of this design.

Integration of Bridge Damage Detection Concepts and Components (3 volumes), TR-636, 2013

This work is divided into three volumes: Volume I: Strain-Based Damage Detection; Volume II: Acceleration-Based Damage Detection; Volume III: Wireless Bridge Monitoring Hardware. Volume I: In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The statistical damage-detection tool, control-chart-based damage-detection methodologies, were further investigated and advanced. For the validation of the damage-detection approaches, strain data were obtained from a sacrificial specimen attached to the previously-utilized US 30 Bridge over the South Skunk River (in Ames, Iowa), which had simulated damage,. To provide for an enhanced ability to detect changes in the behavior of the structural system, various control chart rules were evaluated. False indications and true indications were studied to compare the damage detection ability in regard to each methodology and each control chart rule. An autonomous software program called Bridge Engineering Center Assessment Software (BECAS) was developed to control all aspects of the damage detection processes. BECAS requires no user intervention after initial configuration and training. Volume II: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The objective of this part of the project was to validate/integrate a vibration-based damage-detection algorithm with the strain-based methodology formulated by the Iowa State University Bridge Engineering Center. This report volume (Volume II) presents the use of vibration-based damage-detection approaches as local methods to quantify damage at critical areas in structures. Acceleration data were collected and analyzed to evaluate the relationships between sensors and with changes in environmental conditions. A sacrificial specimen was investigated to verify the damage-detection capabilities and this volume presents a transmissibility concept and damage-detection algorithm that show potential to sense local changes in the dynamic stiffness between points across a joint of a real structure. The validation and integration of the vibration-based and strain-based damage-detection methodologies will add significant value to Iowa’s current and future bridge maintenance, planning, and management Volume III: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. This report volume (Volume III) summarizes the energy harvesting techniques and prototype development for a bridge monitoring system that uses wireless sensors. The wireless sensor nodes are used to collect strain measurements at critical locations on a bridge. The bridge monitoring hardware system consists of a base station and multiple self-powered wireless sensor nodes. The base station is responsible for the synchronization of data sampling on all nodes and data aggregation. Each wireless sensor node include a sensing element, a processing and wireless communication module, and an energy harvesting module. The hardware prototype for a wireless bridge monitoring system was developed and tested on the US 30 Bridge over the South Skunk River in Ames, Iowa. The functions and performance of the developed system, including strain data, energy harvesting capacity, and wireless transmission quality, were studied and are covered in this volume.

Autonomous Measurements of Bridge Pier and Abutment Scour using Motion-Sensing Radio Transmitters, TR-595, 2010

Two portable Radio Frequency IDentification (RFID) systems (made by Texas Instruments and HiTAG) were developed and tested for bridge scour monitoring by the Department of Civil and Environmental Engineering at the University of Iowa (UI). Both systems consist of three similar components: 1) a passive cylindrical transponder of 2.2 cm in length (derived from transmitter/responder); 2) a low frequency reader (~134.2 kHz frequency); and 3) an antenna (of rectangular or hexagonal loop). The Texas Instruments system can only read one smart particle per time, while the HiTAG system was successfully modified here at UI by adding the anti-collision feature. The HiTAG system was equipped with four antennas and could simultaneously detect 1,000s of smart particles located in a close proximity. A computer code was written in C++ at the UI for the HiTAG system to allow simultaneous, multiple readouts of smart particles under different flow conditions. The code is written for the Windows XP operational system which has a user-friendly windows interface that provides detailed information regarding the smart particle that includes: identification number, location (orientation in x,y,z), and the instance the particle was detected.. These systems were examined within the context of this innovative research in order to identify the best suited RFID system for performing autonomous bridge scour monitoring. A comprehensive laboratory study that included 142 experimental runs and limited field testing was performed to test the code and determine the performance of each system in terms of transponder orientation, transponder housing material, maximum antenna-transponder detection distance, minimum inter-particle distance and antenna sweep angle. The two RFID systems capabilities to predict scour depth were also examined using pier models. The findings can be summarized as follows: 1) The first system (Texas Instruments) read one smart particle per time, and its effective read range was about 3ft (~1m). The second system (HiTAG) had similar detection ranges but permitted the addition of an anti-collision system to facilitate the simultaneous identification of multiple smart particles (transponders placed into marbles). Therefore, it was sought that the HiTAG system, with the anti-collision feature (or a system with similar features), would be preferable when compared to a single-read-out system for bridge scour monitoring, as the former could provide repetitive readings at multiple locations, which could help in predicting the scour-hole bathymetry along with maximum scour depth. 2) The HiTAG system provided reliable measures of the scour depth (z-direction) and the locations of the smart particles on the x-y plane within a distance of about 3ft (~1m) from the 4 antennas. A Multiplexer HTM4-I allowed the simultaneous use of four antennas for the HiTAG system. The four Hexagonal Loop antennas permitted the complete identification of the smart particles in an x, y, z orthogonal system as function of time. The HiTAG system can be also used to measure the rate of sediment movement (in kg/s or tones/hr). 3) The maximum detection distance of the antenna did not change significantly for the buried particles compared to the particles tested in the air. Thus, the low frequency RFID systems (~134.2 kHz) are appropriate for monitoring bridge scour because their waves can penetrate water and sand bodies without significant loss of their signal strength. 4) The pier model experiments in a flume with first RFID system showed that the system was able to successfully predict the maximum scour depth when the system was used with a single particle in the vicinity of pier model where scour-hole was expected. The pier model experiments with the second RFID system, performed in a sandbox, showed that system was able to successfully predict the maximum scour depth when two scour balls were used in the vicinity of the pier model where scour-hole was developed. 5) The preliminary field experiments with the second RFID system, at the Raccoon River, IA near the Railroad Bridge (located upstream of 360th street Bridge, near Booneville), showed that the RFID technology is transferable to the field. A practical method would be developed for facilitating the placement of the smart particles within the river bed. This method needs to be straightforward for the Department of Transportation (DOT) and county road working crews so it can be easily implemented at different locations. 6) Since the inception of this project, further research showed that there is significant progress in RFID technology. This includes the availability of waterproof RFID systems with passive or active transponders of detection ranges up to 60 ft (~20 m) within the water–sediment column. These systems do have anti-collision and can facilitate up to 8 powerful antennas which can significantly increase the detection range. Such systems need to be further considered and modified for performing automatic bridge scour monitoring. The knowledge gained from the two systems, including the software, needs to be adapted to the new systems.