Modeling Defect Detection in 3D-Printed Structures Using Ultrasonic Guided Waves

Abstract

Carbon fiber-reinforced thermoplastic composites are widely utilized in 3D printing via the fused filament fabrication (FFF) process. However, defects within printed components can compromise their performance. This study investigates the application of ultrasonic non-destructive testing (NDT) techniques for structures manufactured through FFF. Common printing defects, such as weak interlayer bonding, surface imperfections, and internal cracks, are simulated using a finite element (FE) model. The model analyzes how guided ultrasonic waves interact with these defects. The proposed methodology incorporates digital transducer control and evaluates the energy distribution across incident, reflected, and transmitted wave modes. Three representative defect types are modeled, and the approach is applied to two structural geometries: plates and pipes. The study investigates the correlation between defect size and the behavior of energy reflection and transmission. A signal processing approach is applied, using transducers positioned symmetrically along the wave propagation axis to detect mode conversion and analyze wave reflections and transmissions. The phenomenon of mode conversion is analyzed in detail, and the results are validated by ensuring energy balance consistency.