Download Free Concrete Bridge Deck Condition Assessment Guidelines Book in PDF and EPUB Free Download. You can read online Concrete Bridge Deck Condition Assessment Guidelines and write the review.

Although the substructures and superstructures of bridges in Utah are in relatively good structural condition, the bridge decks are experiencing observable deterioration due to the routine application of deicing salts and repeated freeze-thaw cycling. This manual describes condition assessment methods and threshold values that may be used to determine whether rehabilitation or replacement of a given bridge deck is more appropriate when the severity and extent of deterioration warrant deck improvement. Threshold values given in the manual are based on a questionnaire survey conducted of state departments of transportation nationwide, as well as on standards and guidelines published by the American Society for Testing and Materials, American Association of State Highway and Transportation Officials, and Strategic Highway Research Program.
" 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.
Recently developed corrosion-resistant reinforcing structural design guidelines were used to design, construct, and assess a reinforced concrete bridge deck with high-strength ASTM A1035 CS steel bars. The bridge replacement is located along the North Scenic Highway over the Wolf Creek in Bland County, Virginia. The bridge deck design used the higher yield stress available from ASTM A1035 CS steel to replace No. 5 bars with No. 4 bars that saved 23% by weight of steel in the deck and reduced reinforcement bar congestion, especially near the traffic barrier-bridge deck splice. The material cost savings was also 23% compared to a standard Virginia Department of Transportation bridge deck since the bars were bid as a cost per unit weight. The Wolf Creek Bridge deck surface (i.e., cracks, slope, and surface profile) was documented using an automated computer vision system assembled with off-the-shelf cameras that accurately surveyed the bridge deck in less than 10 minutes, providing a high resolution 3D digital state model before and after the bridge was opened to traffic. The bridge deck is in excellent condition after 2 months in service, with only one crack of 0.004 in observed near a construction joint. The study concluded that concrete bridge decks can be designed with No. 4 bars and constructed considering the structural benefits of gradually yielding, high-strength ASTM A1035 CS reinforcement bars with satisfactory in-service performance and some cost savings.
Several evaluation techniques were employed to assess concrete bridge deck condition, including visual inspection, hammer sounding and chaining, dielectric measurements, ground-penetrating radar imaging, resistivity testing, half-cell potential testing, and chloride concentration testing. The condition assessment testing confirmed that chloride-induced corrosion of reinforcing steel is the primary mechanism of deck deterioration and that inadequate cover over the upper steel mat facilitated accelerated corrosion damage in many instances. The bridge deck condition analyses produced from the results of non-destructive testing were compared to the visual inspection ratings assigned to each deck by UDOT.
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 key elements in the US transportation system. There are more than six hundred thousand bridges on the highway system in the United States. Approximately one third of these bridges are in need of maintenance and will cost more than $120 billion to rehabilitate or repair. Several factors affect the performance of bridges over their life spans. Identifying these factors and accurately assessing the condition of bridges are critical in the development of an effective maintenance program. While there are several methods available for condition assessment, selecting the best technique remains a challenge. Therefore, developing an accurate and reliable model for concrete bridge deck deterioration is a key step towards improving the overall bridge condition assessment process. Consequently, the main goal of this dissertation is to develop an improved bridge deck deterioration prediction model that is based on the National Bridge Inventory (NBI) database. To achieve the goal, deterministic and stochastic approaches have been investigated to model the condition of bridge decks. While the literatures have typically proposed the Markov chain method as the best technique for the condition assessment of bridges, this dissertation reveals that some probability distribution functions, such as Lognormal and Weibull, could be better prediction models for concrete bridge decks under certain condition ratings. A new universal framework for optimizing the performance of prediction of concrete bridge deck condition was developed for this study. The framework is based on a nonlinear regression model that combines the Markov chain method with a state-specific probability distribution function. In this dissertation, it was observed that on average, bridge decks could stay much longer in their condition ratings than the typical 2-year inspection interval, suggesting that inspection schedules might be extended beyond 2 years for bridges in certain condition rating ranges. The results also showed that the best statistical model varied from one state to another and there was no universal statistical prediction model that can be developed for all states. The new framework was implemented on Michigan data and demonstrated that the prediction error in the combined model was less than each of the two models (i.e. Markov and Lognormal). The results also showed that average daily traffic, age, deck area, structure type, skew angle, and environmental factors have significant impact on the deterioration of concrete bridge decks. The contributions of the work presented in this dissertation include: 1) the identification of the significant factors that impact concrete bridge deck deterioration; 2) the development of a universal deterioration prediction framework that can be uniquely tailored for each state’s data; and 3) supporting the possibility of extending inspection schedules beyond the typical 2-year cycles. Future work may involve: 1) evaluating each of the factors that impact the deterioration rates in more depth by refining the investigation ranges; 2) investigating the possibility of revising the regular bridge deck inspection intervals beyond the 2-year cycles; and 3) developing deterioration prediction models for other bridge elements (i.e. superstructure and substructure) using the framework developed in this dissertation.
NCHRP Report 566 is designed to help facilitate the use of supplementary cementitious materials to enhance durability of concrete used in highway construction, especially bridge decks. The report includes a methodology for selecting optimum concrete mixture proportions that focuses on durability aspects of concrete and the performance requirements for specific environmental conditions. The methodology is presented in a text format and as a computational tool, in the form of a Visual Basic?driven Microsoft Excel spreadsheet. Background information and a hypothetical case study was published as NCHRP Web-Only Document 110: Supplementary Cementitious Materials to Enhance Durability of Concrete Bridge Decks. The Statistical Experimental Design for Optimizing Concrete (SEDOC), the computational tool for the concrete mixture optimization methodology, and the user?s guide are available in a ZIP format for download.