Accurately characterizing the mechanical properties of additive manufacturing (AM) materials is challenging with conventional methods, which often lack precision or are destructive. 

To overcome the challenge, we developed a nondestructive evaluation technique integrating ultrasonic guided wave sensing and advanced frequency-wavenumber analysis enhanced by optimization algorithms. Our method employs programmable ultrasonic excitation and robotic-controlled laser Doppler vibrometry to capture detailed multidimensional acoustic wavefield. This innovative approach effectively determined anisotropic mechanical properties in AM materials, including metals, composites, and ceramics. The results demonstrate the method's reliability and potential for real-time quality monitoring and process optimization in additive manufacturing.

Nuclear power plants rely on ceramic fuel cladding to safely contain radioactive fuel, making it essential to regularly inspect cladding integrity. Traditional inspection methods typically involve destructive testing, damaging the sample, or contact-based methods unable to simultaneously detect defects and evaluate material strength. 

To address the problem, we developed a robotic-assisted, non-destructive technique using guided ultrasonic waves. A robotic arm equipped with piezoelectric sensors sends guided waves through silicon carbide ceramic cladding, while a laser measures vibrations without physical contact. Analyzing wave propagation identifies defects (like cracks, notches, and surface pits ) and accurately characterizes mechanical properties such as elastic modulus and stiffness. Our approach can detect defects and measure material properties with accuracy within 5%. We hope this efficient, real-time monitoring system enhances safety in nuclear operations by proactively identifying potential structural failures.