Erin Santini Bell

Instrumentation, Nondestructive Testing, and Finite-Element Model Updating for Bridge Evaluation Using Strain Measurements

A baseline finite element model was developed for bridge management and calibration using nondestructive test data. The model calibration technique was evaluated on the Vernon Avenue Bridge over the Ware River in Barre, Massachusetts. This newly constructed bridgewas instrumented throughout its construction phases in preparation for a static truck load test performed before the bridge opening. The strain data collected during the load test was used to calibrate a detailed baseline finite element model in an effort to represent the 3D system behavior of the bridge. Three methods of load ratings were used and compared: (1) conventional method, (2) conventional method updated by using NDT data, and (3) finite element model calibrated with NDT data. DOI: 10.1061/(ASCE)BE.1943-5592.0000228.

Objective Load Rating of a Steel-Girder Bridge Using Structural Modeling and Health Monitoring

AbstractThe future of highway infrastructure in the United States is at a critical junction. Nearly one-third of U.S. bridges are nearing the end of their design life, and one in ten bridges is categorized as structurally deficient. While the design and construction of the next generation of U.S. highway bridges is underway, existing bridges must be maintained through proper inspection and load rating. This paper proposes an objective load rating protocol that takes advantage of a shift in the bridge design, construction, and management paradigm to include structural modeling, instrumentation, and nondestructive testing. A baseline structural model is created and verified using structural health monitoring (SHM) data collected during a controlled static load test. The structural model is then used to calculate load rating factors of the bridge at both current and simulated damaged conditions. The resulting load rating factors are compared with the AASHTO load resistance factor rating method.

Bridge Deck Finite Element Model Updating Using Multi-Response NDT Data

A multi-response parameter estimation method, including an error function normalization procedure, is proposed to allow simultaneous estimation of stiffness and mass parameters for model updating. The initial finite element model (FEM) of the University of Cincinnati Infrastructure Institute (UCII) bridge deck was developed based on preliminary calculations using information gathered from available drawings. The unknown parameters were selected for the grid model based on the results of damage localization, and were successfully updated using structural parameter estimation methods. This paper presents both the updated structural stiffness and mass parameters of the grid model using a few subsets of static and dynamic non-destructive testing ( NDT) measurements. The static and modal response from the updated model resulted in a closer match with the NDT data than the responses from the initial FEM of the bridge deck.

Structural Modeling, Instrumentation, and Load Testing of the Tobin Memorial Bridge in Boston, Massachusetts

This paper describes analytical structural models created for various components of the Tobin Memorial Bridge, and a program of instrumentation and non-destructive testing for the Little Mystic Span. A detailed global finite element model of the Little Mystic Span, one of the two truss spans, was developed along with supporting special studies of continuity and boundary conditions. Special studies include modeling the rotational stiffness of the truss connections and consideration of the piers and bridge shoes. An instrumentation plan was developed and deployed for the Little Mystic Span to capture structural responses of key truss members. Nondestructive testing using loaded trucks was carried out for the purpose of model verification and calibration. Preliminary comparisons between experimental and analytical strains for key truss members show reasonable agreement. Special study results will be used to fine-tune the global finite element model. The verified models may be used as a condition assessment program and structural health monitoring system for the management of the Tobin Memorial Bridge.

Long-Term Thermal Performance of a CFRP-Reinforced Bridge Deck

In 2000, the Rollins Road Bridge in Rollinsford, New Hampshire was constructed with partial funding from the Innovative Bridge Research and Construction (IBRC) program administered by the Federal Highway Administration (FHWA). A requirement of the IBRC program is the use of high performance and innovative materials and instrumentation. This paper focuses on use of the collected data, from both strain and temperature sensors, to evaluate thermal performance of a CFRP-reinforced concrete deck. The sensor data will be evaluated based on its value in a long-term structural health monitoring program. The collected data will be compared with the predicted response for a finite element model created in SAP 2000. Also, a statistical analysis of the collected temperature and strain data will be presented for data quality analysis.

Analyzing Prerepair and Postrepair Vibration Data from the Sarah Mildred Long Bridge after Ship Collision

The Sarah Mildred Long Bridge, an 854-m (2,804-ft) double-deck truss bridge in Portsmouth, New Hampshire, was struck by a 144-m (473-ft) cargo ship on April 1, 2013. After days of visual inspection and assessment, it was found that the main damage, significant bending of a vertical and a diagonal truss member, required replacement of the impacted members. According to the New Hampshire Department of Transportation, the repair cost

Static Testing of Civil Structures: Data Quality and Post- Processing

2.5 million. Before and after repairs, the authors collected vibration data on the bridge. This was a rare, valuable data set of a major structure at its damaged (prerepair) and healthy (postrepair) states. In this paper, the authors detail the data analyses and results and compare data collected before and after repairs at the Sarah Mildred Long Bridge. A finite-element model (FEM) of the damaged bridge span was created to compare the field data. By studying the frequency responses of the vibration data and the FEM, the authors were able to identify and explain noticeable changes between the bridge’s healthy and damaged states.

Accounting for the Impact of Thermal Loads in Nondestructive Bridge Testing

Structural identification programs executed without appropriate methods for data interpretation usually fail to provide meaningful information to support engineering decisions. Identifying and implementing appropriate data interpretation methods represent fundamental scientific challenges in the field of structural identification. Given the many recent developments in and diversity of available sensor technologies, and the impressive gains in computing capacity, data interpretation challenges often remain as the final “bottleneck” restricting the potential of structural identification through static and quasi-static measurements. High quality data interpretation leads to a significantly increased understanding of the real structural behavior. Analytical quality and measurement data quality both need to be evaluated to establish the degree of correlation between predictive structural analysis-based responses and the collected measurements; however, an exact correlation should rarely be the objective. This paper will discuss the issues related to quality of measurements and interpretation of this data using structural analysis and structural identification algorithms. It should be noted that data interpretation methods must always respect the physical reality associated with structures, and no single approach is best for all cases.

Multiresponse Parameter Estimation for Finite-Element Model Updating Using Nondestructive Test Data

This paper presents a research project currently funded by the Research Advisory Council of the New Hampshire Department of Transportation to develop a framework for bridge condition assessment integrating instrumentation and structural modeling for highway bridge decision-making and management. Nondestructive testing on bridges is a large part of a comprehensive structural health monitoring program. Another key component of structural health monitoring is finite element model for evaluation of the measured responses through model updating and parameter estimation. One method of nondestructive testing is a controlled static load test, where a pre-weighed truck is placed at predetermined locations on the bridge and the response is measured via strain, rotation, and deflection measurements. The location, wheel weights, and time at each location are precisely recorded during the entire duration of the load test. However, there is another load that can have more of an impact on the bridge response than applied static load, and that is thermal loading due to temperature change. It has been observed in three different load tests at Rollins Road Bridge in Rollinsford, NH that temperature effects mask the load applied to the bridge over the duration of the load test. These temperature effects either need to be corrected for, using an empirical correction, or included into the structural predictive model to get accurate results for use in a parameter estimation algorithm and model updating protocol to determine the structural health of the bridge.