The ASCE report card 2013 rated bridges at a grade of C+, implying their condition is moderate and require immediate attention. Moreover, the Federal Highway Administration reported that it is required to invest more than $20.5 billion each year to eliminate the bridge deficient backlog by 2028. In Canada 2012, more than 50% of bridges fall under fair, poor, and very poor categories, where more than $90 billion are required to replace these bridges. Therefore, government agencies should have an accurate way to inspect and assess the corrosiveness of the bridges under their management. Numerical Amplitude method is one of the most common used methods to interpret Ground Penetrating Radar (GPR) outputs, yet it does not have a fixed and informative numerical scale that is capable of accurately interpreting the condition of bridge decks. To overcome such problem, the present research aims at developing a numerical GPR-based scale with three thresholds and build deterioration models to assess the corrosiveness of bridge decks. Data, for more than 60 different bridge decks, were collected from previous research works and from surveys of bridge decks using a ground-coupled antenna with the frequency of 1.5 GHz. The amplitude values of top reinforcing rebars of each bridge deck were classified into four categories using k-means clustering technique. Statistical analysis was performed on the collected data to check the best-fit probability distribution and to choose the most appropriate parameters that affect thresholds of different categories of corrosion and deterioration. Monte-Carlo simulation technique was used to validate the value of these thresholds. Moreover, a sensitivity analysis was performed to realize the effect of changing the thresholds on the areas of corrosion. The final result of this research is a four-category GPR scale with numerical thresholds that can assess the corrosiveness of bridge decks. The developed scale has been validated using a case study on a newly constructed bridge deck and also by comparing maps created using the developed scale and other methods. The comparison shows sound and promising results that advance the state of the art of GPR output interpretation and analysis. In addition, deterioration models and curves have been developed using Weibull Distribution based on GPR outputs and corrosion areas. The developed new GPR scale and deterioration models will help the decision makers to assess accurately and objectively the corrosiveness of bridge decks. Hence, they will be able to take the right intervention decision for managing these decks.

" 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.

As the nation's infrastructure continues to age, there is a need to effectively and economically monitor and inspect bridges. With the introduction of non-destructive testing technologies such as Ground Penetrating Radar (GPR) for condition assessment of bridge decks, states will be better equipped to inspect, assess, and prioritize transportation funding to maintain, preserve, and improve infrastructure. The objective of the research is to improve the condition assessment of bridge decks through the use of GPR which can increase the speed, effectiveness, and accuracy of inspections. The non-destructive evaluation technique provides information that can be used to identify the potential amount of internal deterioration of a concrete bridge deck that cannot be identified with a visual inspection. As in many other states, New Mexico currently uses the chain drag method in which the inspection of the deck condition is solely based on inspector's subjective interpretation of the sound produced by dragging a chain over the bridge deck. The use of GPR has the potential to greatly improve the quality of the inspections by collecting more reliable and less subjective information on the condition of bridge decks. Through the collection and analysis of data acquired from the GPR on a set of reinforced concrete decks, this research seeks to provide a better understanding of GPR technology, data acquisition, and training needs for adoption of GPR in bridge deck inspections in the state of New Mexico. With a better understanding of the technology, GPR can become and indispensable tool for more informed decisions for the allocation of funds for maintenance and improved asset management. This research improves implementation and provides effective economic methods to employ this technology to improve the inspection and maintenance of bridge infrastructure.

Reinforcement concrete (RC) bridge decks are surveyed regularly to ensure that they are safe to use and to determine if they require rehabilitation or replacement. The bridge surveys include evaluating subsurface bridge condition. RC bridges have steel reinforcement bars, also called rebars, embedded in their surface, which are prone to corrosion due to factors like moisture, carbonation, use of deicing salts and aging. By the time the effect of corroded rebars is visible on deck surface in form of cracks, the damage is tremendous. If left unchecked, corroded rebars can deteriorate at a faster and significantly affect bridge integrity. So, it is very important to timely identify and repair deteriorated rebars. Ground Penetrating Radar (GPR) is a widely used non-destructive technology (NDT) for detecting subsurface anomalies in variety of structures including RC bridges. The raw GPR data is represented as images that can be processed for obtaining a deterioration map of a bridge, which indicates the level of corrosion in rebars for the entire bridge. The existing methods to generate the deterioration map using GPR data are semi-automated, time consuming and depends on expertise of the engineer analyzing the data. In this thesis, we work towards automating the process of obtaining deterioration map of RC bridge decks based on measuring signal attenuation at the upper rebar mat using GPR. Intensity and gradient-based feature vectors were explored to construct a classifier, which can detect the regions of interest (ROI) corresponding to each rebar in images. Each classifier was tested on datasets constructed from two different bridges. Further, the exact location of rebar was found in each ROI. Once all the rebars were detected throughout the bridge, depth-correction of the measured attenuation is applied so that the component of that measured attenuation caused solely by variation in rebar depth does not skew the results. Finally, a deterioration map was generated which indicates the level of corrosion in the bridge. The proposed algorithm was tested on two RC bridges and the deteriorated regions obtained are compared with the results obtained using existing tools.