"This study investigates two bridge decks in the state of Missouri using both nondestructive and destructive testing methods. The Missouri Department of Transportation (MoDOT) is responsible for the monitoring and maintenance of over 10,000 bridges. Currently monitoring of these bridges includes a comprehensive visual inspection. In this study, ground-coupled ground penetrating radar (GPR) is used to estimate deterioration, along with other traditional methods, including visual inspection, and core evaluation. Extracted core samples were carefully examined, and the volume of permeable pore space was determined for each core. After the initial investigation, the two bridges underwent rehabilitation using hydrodemolition as a method to remove loose or deteriorated concrete. Depths and locations of material removal were determined using light detection and ranging (lidar). Data sets were compared to determine the accuracy of GPR to predict deterioration for condition monitoring and rehabilitation planning of bridge decks. As shown by the lidar survey of the material removed during rehabilitation, the GPR top reinforcement reflection amplitude accurately predicted regions of deterioration within the bridge decks. In general, regions with lower reflection amplitudes, indicating more evidence of deterioration, corresponded to regions with greater depths of material removal during the rehabilitation. Also, the GPR top reinforcement reflection amplitude indicated deterioration in areas where visual deterioration was noticed from the top surface of the deck. The majority of cores with delaminations were extracted from sections where the GPR top reinforcement reflection amplitude indicated greater evidence of deterioration based on lower amplitude values."--Abstract, page iii.

"The dissertation is composed of three papers, which cover the lack of information on the specific aspects of non-destructive and destructive bridge deck assessment. In the first paper, appropriate data acquisition and processing parameters for concrete bridge deck condition assessment using ground-coupled ground penetrating radar are developed. The use of proposed parameters helps to significantly reduce acquisition and processing time, while providing engineers with reliable and detailed information on the condition of bridge deck. In the second paper, a novel approach to develop relationship between GPR data and concrete removal depth measurements collected after hydrodemolition is proposed. A linear relationship between the two is assumed, justified and corrected. Two case studies are used to verify the proposed approach. In the third paper, an integrated approach in assessing bridge deck condition is introduced. Four techniques -- visual inspection, GPR, USW, and core control -- were used to perform a bridge deck assessment. LiDAR measurement of concrete depth removal collected after hydrodemolition were used as ground truth. The advantages and disadvantages of each method are discussed. Qualitative and quantitative comparisons of data collected using non-destructive and destructive techniques are performed"--Abstract, page iv.

" TRB's second Strategic Highway Research Program (SHRP 2) Report S2-R06A-RR-1: Nondestructive Testing to Identify Concrete Bridge Deck Deterioration identifies nondestructive testing technologies for detecting and characterizing common forms of deterioration in concrete bridge decks.The report also documents the validation of promising technologies, and grades and ranks the technologies based on results of the validations.The main product of this project will be an electronic repository for practitioners, known as the NDToolbox, which will provide information regarding recommended technologies for the detection of a particular deterioration. " -- publisher's description.

Bridge management system (BMS) is an effective mean for managing bridges throughout their design life. BMS requires accurate collection of data pertinent to bridge conditions. Non Destructive Evaluation methods (NDE) are automated accurate tools used in BMS to supplement visual inspection. This research provides overview of current practices in bridge inspection and in-depth study of thirteen NDE methods for condition assessment of concrete bridges and eleven for structural steel bridges. The unique characteristics, advantages and limitations of each method are identified along with feedback on their use in practice. Comparative study of current practices in bridge condition rating, with emphasis on the United States and Canada is also performed. The study includes 4 main criteria: inspection levels, inspection principles, inspection frequencies and numerical ratings for 4 provinces and states in North America and 5 countries outside North America. Considerable work has been carried out using a number of sensing technologies for condition assessment of civil infrastructure. Fewer efforts, however, have been directed for integrating the use of these technologies. This research presents a newly developed method for automated condition assessment and rating of concrete bridge decks. The method integrates the use of ground penetrating radar (GPR) and infrared thermography (IR) technologies. It utilizes data fusion at pixel and feature levels to improve the accuracy of detecting defects and, accordingly, that of condition assessment. Dynamic Bayesian Network (DBN) is utilized at the decision level of data fusion to overcome cited limitations of Markov chain type models in predicting bridge conditions based on prior inspection results. Pixel level image fusion is applied to assess the condition of a bridge deck in Montreal, Canada using GPR and IR inspection results. GPR data are displayed as 3D from 24 scans equally spaced by 0.33m to interpret a section of the bridge deck surface. The GPR data is fused with IR images using wavelet transform technique. Four scenarios based on image processing are studied and their application before and after data fusion is assessed in relation to accuracy of the employed fusion process. Analysis of the results showed that bridge condition assessment can be improved with image fusion and, accordingly, support inspectors in interpretation of the results obtained. The results also indicate that predicted bridge deck condition using the developed method is very close to the actual condition assessment and rating reported by independent inspection. The developed method was also applied and validated using three case studies of reinforced concrete bridge decks. Data and measurements of multiple NDE methods are extracted from Iowa, Highway research board project, 2011. The method utilizes data collected from ground penetrating radar (GPR), impact echo (IE), Half-cell potential (HCP) and electrical resistivity (ER). The analysis results of the three cases indicate that each level of data fusion has its unique advantage. The power of pixel level fusion lies in combining the location of bridge deck deterioration in one map as it appears in the fused image. While, feature fusion works in identification of specific types of defects, such as corrosion, delamination and deterioration. The main findings of this research recommend utilization of data fusion within two levels as a new method to facilitate and enhance the capabilities of inspectors in interpretation of the results obtained. To demonstrate the use of the developed method and its model at the decision level of data fusion an additional case study of a bridge deck in New Jersey, USA is selected. Measurements of NDE methods for years 2008 and 2013 for that bridge deck are used as input to the developed method. The developed method is expected to improve current practice in forecasting bridge deck deterioration and in estimating the frequency of inspection. The results generated from the developed method demonstrate its comprehensive and relatively more accurate diagnostics of defects.

Bridges are at the heart of transportation systems connecting the roads to and between the mainlands. Thus, bridges are an integral part of the economic growth of any country. They are subjected to dynamic loads of the vehicles and the environmental effects. These loads cause stress and strain cycles causing its deterioration by initiating microcracking. The deterioration is then accelerated due to the chloride attack which causes the corrosion of the steel reinforcement resulting in cracking and delamination of concrete and ultimately leads to failure. It is essential to analyze the bridge with its actual condition which is difficult with a visual inspection. This analysis can help in determining the degree of repairs needed and an approximate idea about its service life. The development of the Non-Destructive Test (NDT) methods helps assess the condition of the bridge without any kind of damage to the original structure. In the past few decades, the Non-Destructive Evaluation (NDE) with the help of Ground Penetration Radar (GPR) has gained popularity due to its ease in the evaluation of the larger areas such as bridge deck and parking lot in a shorter amount of time with sufficient training. The NDE using GPR for Structural Health Monitoring (SHM) has been still evolving with new improvements in its technology as well as the development of new methods for the analysis of its data. A positive step towards detecting the subsurface materials present in the cracks has been undertaken in this study. A methodology to detect the subsurface cracks/gaps in concrete using GPR has been developed here by preparing three concrete samples of dimensions 50 x 25 x 5 cm3, 50 x 25 x 10 cm3, and 50 x 25 x 20 cm3 in the laboratory. The detection of reinforcement of 6 mm, 10 mm, 18 mm, 20 mm diameter, as well as a 21.8 mm Fiber Reinforcement Polymer (FRP) bar, are studied along with the detection of the air gap, water gap, and gap with the salt solutions of thickness 3 mm, 4 mm, 4.8 mm, 5.8 mm and 8.8 mm under the depth of 5 cm, 10 cm, and 15 cm. The amplitude values of these parameters are studied, and a comparison is made to check the ability of GPR to detect this material in cracks and/or delamination with changes in depths. This will be helpful in analyzing the GPR data with more reliability. Along with this, a non-linear finite element model (FEM) of a bridge superstructure using a fiber element is developed. The FE model of the bridge deck is updated and analyzed using a GPR defect map. This procedure of model updating is less tedious than the previous method available in the literature and proves to be time-saving. This model updating procedure will prove to be helpful in estimating the capacity of the bridge and make a prediction for future deterioration with the help of NDE methods (here GPR).

This project piloted the findings from an initial research and development project pertaining to the detection, quantification, and visualization of bridge deck distresses through the use of remote sensing techniques, specifically combining optical and thermal imagery, and expanded by increasing the rate of data collection to near-highway speed (speeds of at least 45 mph). Specifically, six large deck bridges (>90,000 sf) were assessed, without closing lanes to traffic, and are presented. Top deck concrete surfaces were evaluated for spalls and delaminations, and were recapped in map-based and table-based element level summaries with percentage and area by condition state and by span. Personnel and computing times were documented, and costs were estimated for a similar future bridge deck condition assessment for a large deck bridge. Additionally, this pilot project conducted a 3-D Optical Bridge-evaluation System (3DOBS) accuracy assessment, and provided training and demonstration sessions to help MDOT personnel understand and implement these technologies. By identifying element level condition states of concrete decks through innovative methods of data collection and advanced data processing, implementation of these combined remote sensing technologies has the potential to become a standard MDOT business practice.