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Abstract – Polymer-based additive manufacturing (AM) has found extensive application in various industries, including medical and aerospace, owing to its rapid and cost-effective process. Nevertheless, real-time monitoring of the printed parts continues to face challenges and issues. This study compares the effectiveness of three near-field millimeter wave probes – open-ended rectangular waveguide (OERW), dielectric-loaded waveguide (DLW), and extended dielectric-loaded waveguide (EDLW) – in detecting small voids and moisture absorption in polylactic acid (PLA) filaments commonly used in polymeric AM. Dielectric inserts serve as a field concentration tool, potentially improving the spatial resolution of the probes. Numerical electromagnetic simulations were performed at Ka-band (26.5-40 GHz) and V-band (50-75 GHz) using CST Studio Suite® to detect small hemispherical voids and moisture absorption in the feedstock, respectively, followed by experimental validation. The results of the study indicated that, at V-band (50-75 GHz), the spatial resolution of the standard OERW probe was deemed sufficient for detecting small surface voids in stock PLA filaments. In terms of moisture detection, the EDLW probe at Ka-band (26.5-40 GHz), exhibited the highest sensitivity, when loaded with a material possessing a dielectric constant similar to that of the inspected filament.
Bio: Farzaneh Ahmadi received her B.S. degrees in electrical engineering from Shahid Rajaee University (Tehran, Iran) in 2010 and her M.S. degree in electrical engineering from Tarbiat Modares University (Tehran, Iran) in 2012. She is currently working towards her Ph.D. degree in Electrical and Computer Engineering (ECpE) at Iowa State University (ISU). Her research at the ISU Center for Nondestructive Evaluation (CNDE) involves developing In-line nondestructive evaluation methods for 3D printed structures, especially polymers and metals. She is a recipient of CNDE R. B. Thompson Fellowship, the 2023 American Society for Nondestructive Testing (ASNT) Student Travel Grant Award, and the 2022 ASNT Best Student Paper Award (2nd place).
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