Temperature-Driven Assessment of a Cantilever Truss Bridge

Temperature-driven assessment has the potential to advance our understanding of long-span bridge behavior. The novel approach researched as part of this study is the identification and monitoring of a long-span cantilever truss bridge using the inputoutput temperature relationship. The goal is to use this relationship to identify and monitor unknown quantifiable information with regard to an existing structure using the structural identification process (e.g. boundary conditions, continuity conditions, force distribution, etc.). Since many structural parameters on long-span bridges are highly sensitive to temperature loads, a structure such as the Hurricane Bridge is a prime candidate for this type of monitoring. The Hurricane Bridge is a four-span, cantilever truss bridge over the Caney Fork River in DeKalb County, Tennessee, with a total length of approximately 1787 feet. It was built in 1949 and rehabilitated in 2011. The rehabilitation included widening the deck, strengthening various truss members, and installing a “catch system” consisting of four stainless steel rods around each vertical at the cantilever locations. This critical structure has a great deal of uncertainty related to performance and remaining service life. Therefore, a temperature-driven monitoring system has been designed and implemented to reduce the uncertainty associated with the: “catch system”, pin and hanger effects at cantilever locations, and bearing mechanisms. The sensing technology of this system is comprised of fifty-six vibrating wire strain gages, eight vibrating wire displacement gages, and sixty-four thermistors. Long-term data collection is on-going; however, preliminary results are presented and tasks for future research are explored. INTRODUCTION & OBJECTIVES In recent years, engineering practices have transformed from a mindset of replacement to rehabilitation with regard to many structurally deficient bridges. Much of this motivation stems from funding and the amount of bridges in need of repair at this time. According to the American Road and Transportation Builders Association and the 2015 National Bridge Inventory released by the Federal Highway Administration, “there are nearly 204 million daily crossings on 58,495 U.S. structurally deficient bridges in need of repair” (ARTBA 2016). Due to the increasing number of deficient bridges, monitoring techniques are being utilized more often in order to prioritize the bridges based on their performance and need for intervention. Currently, the most prevailing technique for monitoring long-span bridges is ambient vibration monitoring. Using this method, modal parameters such as natural frequencies, mode shapes, and damping can be determined and tracked for a structure. Although this method has been utilized, ambient vibration monitoring also has challenges associated with it (Catbas 2007). Ambient vibration monitoring has difficulty dealing with environmental effects such as seasonal temperature change since they can mask damage (Peeters and De Roeck 2001). Therefore, a significant challenge for this type of approach is removing the temperature effects. The prevailing reason for the limited success of ambient vibration monitoring of long-span bridges is the limited sensitivity to structural damage (Brownjohn et al. 2011). Alternatively, a temperature-driven concept, where thermal “loads” are treated as the excitation and the corresponding static responses are correlated, shows promise to mitigate many of the shortcomings of ambient vibration monitoring (Yarnold and Moon 2015; Kromanis 2016). Logistically, a temperature-driven approach can be performed continuously over a period of time with minimal data storage and time synchronization requirements. In addition, the equipment is relatively inexpensive and generally self-sustaining with little need for man-power resources once the system is installed and operational. The results can be recorded throughout the structure’s changing environments and can potentially identify structural changes that occur as a result of seismic, wind, ice, impact, or similar nature. This is primarily due to the fact that a temperature-driven baseline is highly sensitive to many changes of structural systems (Yarnold and Moon 2015; Laory et al. 2013). Temperature-driven monitoring is particularly useful for large structures. Long-span bridges, for example, are more responsive to thermal loads than live loads, making the results easier to identify. Figure 1: Structural Identification (St-Id) Process The novel approach researched as part of this study is the identification and monitoring of a long-span, cantilever truss bridge using the input-output temperature relationship. The goal is to use this relationship to identify and monitor unknown quantifiable information with regard to an existing structure (e.g. boundary conditions, continuity conditions, force distribution, etc.) using the structural identification (St-Id) process shown in Figure 1 (Yarnold et al. 2015). “St-Id is the process of creating and updating a model of a structure based on its measured static and/or dynamic measured response which will be used for assessment of the structure’s performance for informed decision making” (Catbas et al. 2013). As shown in the figure, the process can be expanded upon to incorporate a temperature-driven approach. The temperature-driven concept is further explained below followed by illustration of the comprehensive design and implementation for the cantilever truss bridge study. TEMPERATURE-DRIVEN CONCEPT Since long-span bridges have a high sensitivity to thermal effects, everyday temperature exposure can excite a response from the structure. The temperature-driven concept utilizes this cause-and-effect relationship to develop a behavioral signature for the bridge. This process is detailed in Figure 2 below. The temperature variations (input) are quantifiable and can be measured simultaneously with the member strains, displacements, and/or rotations (output) that the bridge experiences in response to the thermal load. Once the behavioral signature has been determined, it can be used to update a model to represent the current condition of the structure. This process can be used for both St-Id as mentioned previously and structural health monitoring (SHM) for long-term performance tracking. Figure 2: Temperature-Driven Concept ASSESSMENT OF THE HURRICANE BRIDGE Bridge collapses are not prevalent in today’s age; however, they can happen. One such occurrence was the I-35W bridge collapse in Minnesota in 2007. This structure was a long-span, steel truss bridge that experienced a catastrophic failure due to a poor design and lack of redundancy (National Transportation Safety Board 2008). Motivated by this disaster, Tennessee Department of Transportation initiated a review of similar bridges in Tennessee, one of which being the Hurricane Bridge shown in Figure 3. Located in DeKalb County, Tennessee, the Hurricane Bridge is a four-span, Warren deck truss bridge that is approximately 1787 feet in total length. Two suspended sections comprise the middle of the bridge as shown in Figure 4. One end of each section rests atop the middle pier while the other end is connected to a cantilever and the rest of the bridge via a pin and hanger detail. This bridge was built in 1949 by the U.S. Army Corps of Engineers and was rehabilitated in 1977 and 2011. The primary goals of the 2011 rehabilitation were to widen the deck, strengthen several structural members, and install a “catch system” to increase redundancy at the cantilever locations. The “catch system” consists of four, 3-inch diameter stainless steel rods installed around each of the vertical hanger members at the cantilever locations to essentially “catch” the suspended section in the event of a failure. The “catch system” is not a commonly used rehabilitation method; therefore, a large degree of uncertainty exists regarding the behavior. Recall, the intent of this study was to use a temperature-driven monitoring approach to minimize the uncertainty of the bridge with regard to the behavior of the pin and hanger, the “catch system”, and the bearings. Figure 4: Hurricane Bridge Overview Figure 3: Hurricane Bridge Following the St-Id process shown previously, an element-level 3D finite element model of the Hurricane Bridge was created. The model includes all primary superstructure and substructure components as shown in Figure 5. A thermal load was applied to the entire structure, and the bearing mechanisms were characterized by connection elements with variable translational stiffness. The variable stiffness elements allowed for simulation of varying stiffnesses of continuity conditions such as bearings and the pin and hanger connections. Figure 5: Finite Element Model of Hurricane Bridge After the finite element model was complete and checked, design of the temperature-driven experiment was performed. The sensing equipment used for this project required the ability to capture the results for any scenario and the ruggedness to withstand prolonged weather exposure. Due to increased demand for monitoring assessments, sensing equipment specifically designed for this purpose was readily available. Vibrating wire strain and displacement gages were decided upon and used to identify the behavior of the bridge. Vibrating wire gages measure frequency from the excitation of a small wire within the gage. The frequency can then be directly correlated to the strain or displacement being measured. Sensitivity studies were performed for various scenarios to determine the optimum location for sensing equipment. For example, Figure 6 shows two scenarios compared to the “As Drawn Conditions” specified in the original and rehabilitation plans. The “As Drawn Conditions” have free movement at the pin and hanger and the expansion bearings of Pier 5 and Pier 7. The scenario “Pier 7 Bearings Seized” has free movement at the Pier 5