Each seminar highlights a different speaker who will discuss their latest research projects, cutting-edge technology or what is happening within certain technological industries. These industries include biomedical technologies or microsystems, assistive technologies, automation and intelligent systems, unmanned systems, advanced manufacturing and composite materials.
Abstract:
Structural Health Monitoring (SHM) is a major concern in the Department of Energy’s (DOE’s) nuclear waste sites due to the associated risks. Of particular interest are the metallic tanks and transfer systems used to store and transport the High-Level Waste (HLW). This talk will provide an overview of three sensing technologies used to detect the material erosion-corrosion and anomalies/faults in the HLW transfer pipelines. Non-destructive testing (NDT) based acoustic sensors have been experimentally evaluated in flow loops transferring simulated nuclear waste mixtures. The flow loops have been custom designed, constructed and tested at our facility by generating accelerated erosion and caustic corrosion in 3-inch and 2-inch carbon steel pipe sections as an indicator of the wear due to the waste transfer process. Sensing modalities include wave guided ultrasonic sensors, fiber optic electroacoustic sensors and a patented ultrasonic thickness/mass loss coupon technology developed by the Savannah River National Laboratory (SRNL) scientists. The experimental data captured was analyzed by the researchers manually in the first stage of the research effort. In the second stage, an automated real-time monitoring system was developed. The data obtained from experiments is used to build, train and test machine learning models to automate the process. Images and numeric data have been used to develop neural network-based machine learning models to predict material erosion/corrosion and to automate the anomaly/fault detection in pipelines. This work indicated that the DOE, nuclear industry and oil, gas & petroleum industry can benefit from the adoption of these SHM technologies to facilitate real-time infrastructure monitoring thus reducing maintenance costs, risks and ensuring safety.
Bio:
Dr. Aravelli is a Research Specialist and an adjunct faculty at Florida International University (FIU). Dr. Aravelli received her Ph.D. from University of Miami and M.S. from West Virginia University and B.S. degree from Andhra University, India – all in mechanical engineering. Her research and industrial experience span multidisciplinary areas of engineering that include sensors, robotics, building energy systems modeling, engine emissions, optimization, and structural health monitoring. Dr. Aravelli published more than 20 peer reviewed journal articles and conference papers in the areas of nuclear waste management, optimization in micro heat-exchangers, HVAC systems and a book titled “Real-Time Measurement of Oxides of Nitrogen from Heavy-Duty Diesel Engines”. She is currently a reviewer for 7 journals. Dr. Aravelli is a Principal Investigator/Co-Principal Investigator conducting research under federally funded projects supported by DOE-EM, DOE-NETL, DOE-MSIPP, DOD, NSF and private industry. She also enjoys teaching several courses in mechanical engineering.
Date:
January 27, 2023
Time:
12:00pm
Location:
Microsoft Teams