This presentation introduces a novel remote acoustic inspection method for concrete structures using controlled water droplet impacts. The technique enables safe, non-contact detection of debonding, voids, and surface defects in large-scale infrastructure without scaffolding or direct access. Attendees will learn the fundamental principles of droplet-induced impact acoustics, practical deployment approaches, and key signal-processing methods that enhance defect sensitivity. The session applies effective adult learning principles by integrating visual demonstrations, real field data, and step-by-step explanations that connect theoretical concepts with practical inspection workflows.

Participants will be able to immediately apply several takeaways in their day-to-day work, including how to select appropriate droplet sizes and firing frequencies, how to interpret acoustic signatures to distinguish sound from defective regions, and how to integrate the technique into existing inspection routines. Field case studies—from bridge decks to building façades—will highlight implementation strategies, equipment considerations, and lessons learned. The presentation provides actionable knowledge for engineers, inspectors, and asset managers seeking safer and more efficient methods for concrete condition assessment.

Despite the common recognition of operational risk management as essential in the construction industry, construction workers face a wide array of poorly mitigated risks on the jobsite. To better mitigate these risks on construction sites, augmented reality (AR) is increasingly being used in the construction industry to improve efficiency, safety, and productivity. For example, AR is proposed for providing on-site workers with real-time instructions, information, and guidance through wearable AR devices such as smart glasses or helmets. These devices can overlay digital information, such as blueprints, measurements, or step-by-step instructions, onto the physical environment, assisting workers in executing tasks accurately and efficiently. However, current AR construction safety tools only provide passive information for the user to then decide how to use that information. This study leverages advanced computer vision coupled with AR to work with site managers and on-site workers to make operational safety decisions using real-time, visual information of potential safety risks and hazards. First, machine learning (ML) models using the YOLOv11 were implemented. These models were trained on existing personal protective equipment (PPE) datasets and are capable of real-time detection of people on video streams and whether or not they are wearing a defined set of PPE. Then the models were tested in the lab by creating a local ML computing environment on a laptop, a webcam stream, and a remote camera stream from Microsoft HoloLens to detect the presence or lack of PPE worn. The detection results were compiled and displayed in real-time on a web-based, user-friendly interface developed with Hypertext Preprocessor (PHP) and on a real-time, heads-up display using Microsoft HoloLens 2. The system was successfully field-tested on a construction site.

The use of collaborative robots (cobots) in laboratory settings enables ultrasonic inspections in immersion, air, and contact configurations through a single mechanical solution. Traditional small gantry-style immersion tanks often lack features such as force-feedback control and fully programmable axes of motion. Cobots, designed to work safely alongside humans, support streamlined workflows for complex inspections while offering unique capabilities not typically available in other inspection platforms.

Through programmable trajectories, integrated force control, and highly repeatable positioning, cobot-assisted workflows can significantly improve inspection efficiency in a flexible laboratory environment. Beyond the standard features included with most cobots, additional software tools are available to further accelerate path planning and reduce the need for operator programming skills. The pivoting base and adaptable kinematics of cobot arm systems allow for quick, seamless transitions between inspection techniques, enabling inspectors to spend more time collecting high-value data and less time on the physical labor of moving between stations.

This presentation highlights how cobots have improved workflow in our laboratory and how they can elevate nondestructive testing processes more broadly. The workflow for inspecting a new part, examples of various inspection environments, and practical tips for maximizing the value of a cobot system are all discussed.

This presentation will describe the effort it takes only by NDT to produce one tube from the start of melting steel to a finished product for the nuclear industry. Some of the inspection steps will have some more explanation in how the equipment is setup also to find the discontinuites required. It will at the same time discribe the manufacturing steps from melting steel to finished product.