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ABSTRACT Economic bridge management requires accurate information about the condition of bridges in the network. Nondestructive evaluation (NDE) has shown high potential in providing accurate condition assessment and, through periodic surveys, development of accurate deterioration, predictive, and life-cycle cost models. To achieve wide adoption by transportation agencies, further advances should be made that would lead to the accuracy of NDE-based condition assessment, reduced costs and traffic interruptions, and minimized risk to transportation workers. The paper discusses the following areas of improvement: increased speed and safety of data collection through the use of robotic systems, and improved data interpretation through visualization and joint analysis of data collected by multiple NDE technologies. KEYWORDS: reinforced concrete, bridges, GPR, impact echo, ultrasonic surface waves, ultrasonic tomography, electrical resistivity, half-cell potential, visualization Introduction Deterioration in reinforced concrete (RC) bridge components is a result of a multitude of actions. Some of the physical factors include repeated application of heavy traffic loading, thermal effects, shrinkage, and freeze-thaw cycles. However, and more often, chemical factors like reinforcement corrosion, alkali-silica reaction, or carbonation have a dominant influ- ence on the deterioration processes. As a result of all these described actions, multiple deterioration and defects will be generated in bridge elements. According to the ASCE 2021 Infrastructure Report (ASCE 2021), nearly 231 000 bridges in the United States need repair and preservation work, and about 5.5% of the bridge deck area is designated as structurally defi- cient or poor. To improve bridge conditions in the next decade, it is estimated that an increase in annual spending on bridge rehabilitation from US$14.4B to US$22.7B will be needed. Improving the accuracy in the detection and characteriza- tion of deterioration and defects of reinforced concrete bridge elements using nondestructive evaluation (NDE) methods is essential for an accurate assessment of best rehabilitation and repair procedures. The condition assessment, paired with an improved speed of NDE data collection and interpretation, will allow economical periodical evaluation of bridges. Such periodical assessments will enable the capture of deterioration processes and defect formation, leading to the development of more accurate deterioration, predictive, and life-cycle cost models (Gucunski et al. 2016 Kim et al. 2019). Ultimately, these will lead to better bridge management. This paper provides an overview of the current practice of bridge evaluation by NDE methods, recent efforts to improve the speed of NDE data collection through automation and robotics, and improved condition interpretation through advanced visualization and combined analysis of results of multiple NDE technologies. Automation of NDE data collection for bridges in the past 10 years concentrated on the assessment of bridge decks, because they deteriorate faster than other bridge components and the deployment of NDE technologies is simpler. Several automated and robotic systems deploying single or multiple NDE technologies have been developed. ADVANCING CONDITION ASSESSMENT OF REINFORCED CONCRETE BRIDGE ELEMENTS THROUGH AUTOMATION, VISUALIZATION, AND IMPROVED INTERPRETATION OF MULTI- NDE TECHNOLOGY DATA NENAD GUCUNSKI*, HUNG MANH LA†, KIEN DINH‡, AND MUSTAFA KHUDHAIR§ * Rutgers University, Department of Civil and Environmental Engineering gucunski@soe.rutgers.edu † University of Nevada-Reno, Department of Computer Science and Engineering ‡ NDT Concrete LLC § Rutgers University, Department of Civil and Environmental Engineering Materials Evaluation 81 (1): 56–66 https://doi.org/10.32548/2023.me-04289 ©2023 American Society for Nondestructive Testing ME | TECHNICALPAPER 56 M AT E R I A L S E V A L U AT I O N • J A N U A R Y 2 0 2 3 2301 ME Jan New.indd 56 12/20/22 8:15 AM