Ms. Jnsun Lee Profile

Jnsun Lee

at Georgia Southern Univ

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Proceedings Article | 28 April 2020 Paper

Ultrasonic evaluation of polymer additively manufactured parts for defect inspection and structural integrity assessment

Jinsun Lee, Mostafa Hasanian, Hossain Saboonchi, Maggie Baechle, Hossein Taheri

Proceedings Volume 11380, 113801Q (2020) https://doi.org/10.1117/12.2572463

KEYWORDS: Ultrasonics, Polymers, Nondestructive evaluation, Inspection, Additive manufacturing, Signal attenuation, Computer aided design, Defect detection, Manufacturing, Ultrasonography

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Quality assurance and structural integrity evaluation are the crucial parts of the successful design and service of additively manufactured (AM) components. Discontinuities and flaws in AM parts can affect the mechanical properties of a component during manufacturing and service. It is very important to identify the discontinuities in AM parts in terms of location, size, and geometrical properties using nondestructive testing (NDT) techniques. Existing research in both mechanical testing and nondestructive evaluation involves developing methods for characterizing and inspecting AM components as the use of such materials continues to rise. Although there exist relatively mature ultrasonic inspection techniques for defect detection, AM polymer components face the challenge of considerable internal inhomogeneities caused by the design and printing strategies. It has been shown that the ultrasonic signals are very sensitive to the material inhomogeneities, consequently the reflection/diffractions from the defects will be significantly influenced and defect detection will be very challenging. This work aims to present the potentials and challenges in ultrasonic detection of defects in polymer AM parts. Air-coupled ultrasonic tests to be demonstrated and followed by results and discussions. The role of porosity on detectability in the ultrasonic NDT tests is described and a possible way for attenuation assessment is demonstrated. Finally, the effect of AM part inhomogeneities on detection probability of seeded defects with different sizes and locations in AM parts is presented.

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