The Federal Highway Administration’s (FHWA’s) Advanced Sensing Technology (FAST) Nondestructive Evaluation (NDE) Laboratory is carrying out several new research concepts within its research program. Projects are largely determined based on the FHWA NDE Program Strategic Plan.

• Evaluation of the latest phased array ultrasonic bridge weld inspection technologies and generating the qualification data to enable ultrasonic test techniques to replace the radiography requirements in the American Welding Society (AWS) bridge welding code, D1.5. Tasks include: evaluating full matrix capture (FMC) and total focusing method (TFM) technology to improve AWS D1.5 ultrasonic flaw characterization; ultrasonic modeling to evaluate AWS D1.5 flaw detection performance, including the generation of virtual qualification data using simulation software; and the evaluation of new advanced technologies for potential incorporation in AWS D1.5, including two- dimensional phased array ultrasonic testing (PAUT) arrays and time-of-flight diffraction (TOFD) techniques.
   
• Validating Density Profiling Systems (DPS) for Asphalt Compaction Assessment: As the DPS technology needs to be proven as a tool for quality assurance of asphalt compaction, the measured values of dielectric should be accurately converted to the pavement properties related value (percent air voids - Va%). Therefore, the scope of this research is to evaluate the development of DPS data collection protocols by assessing:
  • Sensitivity of asphalt mixture design on the dielectric measurements, including effects of aggregate type, size and gradation, and binder.
  • Correlation between asphalt density and dielectric measurements
  • Evaluating the laboratory dielectric measurement procedure of gyratory compacted specimens
  • Investigating the effect of the uniformity of gyratory compacted specimen on the dielectric measurement
• Collaborative Highway Asset Research: Integrated Sensor-Model Application (CHARISMA): This project develops a non-proprietary, open-source repository of algorithms (CHARISMA) to analyze and visualize NDE and other infrastructure data with a long-term goal to fuse sensor data with digital twin / physics-based BIM models. The CHARISMA infrastructure acts as a repository of traditional and machine -learning analysis algorithms that can be shared between stakeholders and improved following open-source principles. CHARISMA can be leveraged by industry to foster the integration of asset inspection, management, and project delivery data for better asset management decision making and facilitating stakeholder collaboration and participation to advance NDT/E and BIM research.

• NDE Data Fusion and Visualization: The purpose of a data fusion and visualization study is to investigate visualization schemes and fusion of NDE data, and to develop a holistic NDE visualization scheme that (1) conveys meaningful and actionable information about the infrastructure that would trigger an intervention, and (2) is understandable by individuals without an extensive background in NDE. With this focus on visualization, it is of interest to develop NDE data fusion strategies and algorithms that enhance the ability of the data visualization scheme to convey information related to the condition, performance, and safety of bridges.

• Current Practices and Policies of State Highway Agency Bridge and Tunnel Units on the use of Deployment-ready NDE Technologies in Complementing Visual Bridge and Tunnel Safety Inspections.  In an effort to develop data driven asset management programs, many stakeholders require extensive bridge and tunnel inspection condition information. These owners have turned to nondestructive evaluation (NDE) technologies as a means of acquiring bridge and tunnel condition data that will allow them to be informed with regards to the performance and condition of their assets. In 2009, a joint American Society of Civil Engineers Structural Engineering Institute and American Association of State Highway and Transportation Officials ad hoc group was created to study how current bridge practices could be improved for the future. Among their recommendations was the wider use of NDE technologies. In addition, with the start of the National Tunnel Inspection Program (NTIP), there is an interest in leveraging NDE technologies to supplement the NTIP data.
   
• Structural Monitoring (SM) Current Practice and Web Manual. In the past two decades, more bridges have been instrumented and monitored during and after construction to determine their performances and responses to various loading and environmental conditions. However, lack of guidelines and specifications or standards have prevented the widespread use of SM in civil infrastructure assets. The objective of this project is to: 1) review existing SM cases and standards/specifications; 2) develop a return of investment tool; and 3) develop a SM web-manual
   
• Incorporating NDE and SM Methods into Bridge Deck Preservation Strategies. The assessment of bridges by nondestructive evaluation (NDE) and structural monitoring (SM) technologies is a growing application area that has significant potential to both reduce the operating costs and extend the lifecycle of concrete bridge decks through the application of the most cost-effective intervention at the most opportune time. The objective of this study is to determine the feasibility and economics of deploying proven NDE and SM technologies for early detection of defects to trigger timely preservation treatments, to determine the quality of the preservation treatment, and to guide bridge owners when considering bridge preservation strategies for concrete bridge decks. All types of wearing surfaces or protective overlay systems should be considered in  this project.
   
• Linking NDE Data and Bridge Deck Performance. The goal of this study is to investigate appropriate use of NDE data to better understand bridge deck performance using data from Bridge Evaluation and Accelerated Structural Testing. The objectives of the research are to:
  (1) demonstrate how NDE data may be analyzed and interpreted to further understand bridge performance and provide bridge owners with tools for predicting future bridge performance; (2) characterize and rank the types of NDE data that are most effective at answering questions related to bridge performance and management; (3) assess the quality and reliability of NDE data collected during accelerated aging of an untreated bare concrete bridge deck; and (4) identify and provide recommendations of other ways in which NDE data (obtained using methods practical for field-collection) may be used to further understanding of bridge performance and advancing bridge deck performance modeling and asset management strategies.