Lalita Udpa, email@example.com | Satish Udpa, firstname.lastname@example.org | Yiming Deng, email@example.com
The Nondestructive Evaluation (NDE) Laboratory, one of the largest and most active in the country, has a long and sustained record of being at the forefront in developing novel electromagnetic and acoustic NDE technologies for both the defense and civilian sectors.
The NDE group focuses on design and development of sensors and systems for monitoring and evaluating structural integrity of parts and components. The varied nature of materials to be inspected have led to the need for new low-cost sensors with high sensitivity to detect flaws buried deep in materials before they reach critical dimensions. Some of the aging infrastructures in the nation range from fleet of aircrafts that fly beyond their design life, nuclear power plants, natural gas transmission pipelines, bridges, etc. NDE sensing technology range from electromagnetic (magnetic flux, eddy current, microwave methods), Ultrasonic (Lamb wave, acoustic), X-ray, IR thermography and Optical and electromagneto-acoustic (EMAT) sensors.
NDE is a multi-disciplinary field and comprise three major research activities; 1) computational modeling, 2) inverse problem solution and 3) Sensor system design. Two examples of currently funded research projects are described.
1) Under EPRI sponsorship NDEL research group has developed a simulation model that predicts eddy current signals from realistic SG tube, defect and probe geometries. Steam generator (SG) tubes in nuclear power plants are continuously exposed to harsh environmental conditions including high temperatures, pressures, fluid flow rates and material interactions resulting in various types of degradation mechanisms such as mechanical wear, stress corrosion cracking (SCC), pitting, and inter granular attack.
The model helps visualize field/flaw interactions and thereby optimize probe designs and inspection parameters. Further the model can be used as a test bed for studying signal formation that can be used in training pattern classification algorithms used in automated signal analysis.
2) Under AFRL sponsored MSU and Boeing was awarded $4 million to create new sensors for detecting cracks in the second layer of a complex multilayer airframe geometry. The challenges in this project are that the cracks are embedded deep in the geometry under the fastener head and can be in arbitrary orientation. Further the strong signal from steel fasteners completely masks small indications from cracks. A novel sensor system with a rotating eddy current excitation and GMR sensor array has been designed and optimized using simulation models. A proof of concept prototype has been built for experimental validation.