UNIVERSITY PARK, Pa. — Researchers at Penn State and the University of Cincinnati received a $500,000 National Science Foundation (NSF) grant to advance quality control methods for parts produced through additive manufacturing, or 3D printing.
The grant will support three years of experimental research and model development.
Currently, researchers can use ultrasonic waves to evaluate internal product features without damaging the product itself. However, this nondestructive evaluation (NDE) method is sometimes hindered by unwanted interference with curved edges, corners and other non-uniform features typical of 3D-printed parts.
The researchers want to change this by developing a model that can simulate wave movement in complex-shaped 3D-printed parts. To achieve this, they will use a recently developed NDE technique known as cryoultrasonic NDE. Pioneered by Francesco Simonetti, co-principal investigator and professor at the University of Cincinnati, cryoultrasonic NDE involves encasing an object in ice to facilitate the movement of ultrasonic waves for highlighting defects. In this project, the researchers will develop an acoustically tuned form of the ice to allow seamless movement of the wave from the ice to the product part. The researchers will analyze the improved ice to inform its optimization.
“This project will allow us to dig deep into the fundamental science,” said Andrea Arguelles, principal investigator and assistant professor of engineering science and mechanics at Penn State. “We want to focus on advancing the way wave propagation is modeled in complex media by developing a new modeling framework.”
The experimental portion of the research — creating and testing the ice — will take place at the University of Cincinnati. At Penn State’s University Park campus, Arguelles and Christian Peco, co-principal investigator and assistant professor of engineering science and mechanics, will employ a unique combination of approaches to build a model validated by the experimental data. A numerical model can provide highly detailed information about small areas, while an analytical approach can be used to apply that information to much larger scales. Arguelles and Peco aim to combine these methods to create a comprehensive, multi-scale model that can predict the behavior of a wave through a part.
“The objective is to extract rules that allow us to accurately simulate the behavior of wave propagation through this medium,” Peco said. “At that point, it becomes possible to design a particular microstructure that can provide us with the acoustic properties we need.”
In the future, the findings from this project could make additive manufacturing more feasible by making complex or irregularly shaped parts easier to evaluate. This could also improve applications for parts in fields where safety is critical, such as construction or aeronautics.
“The models we will develop are not just intended for the inspection of complex-shaped parts,” Arguelles said. “They can allow us to explore more and more complicated microscale features in different materials for a variety of applications.”