An acoustic approach for effective estimation of dynamic elastic properties of 3D-printed Nylon 11 structures

With the increasing adoption of additive manufacturing (3D printing) methods across industries and daily life, characterizing the mechanical integrity (e.g., elastic properties) of 3D-printed solid structures has become an indispensable part of their engineering applications. Conventional mechanical testing methods can provide reliable characterization of static elastic properties, but are destructive and expensive. Typical nondestructive methods, such as the ultrasound pulse-echo method and resonance ultrasound spectrometry, can provide reliable dynamic elastic properties, but their application is limited by strict requirements for specimen preparation, experimental operation, and the availability of required equipment. To address these challenges, this study proposes an effective acoustic method, namely the natural frequency-informed finite element modal analysis method, which is non-destructive, low-cost, easy to implement, and does not require dedicated equipment for determining the elastic properties of 3D-printed solid structures. The effectiveness of the proposed acoustic method was evaluated through a comparative study of 3D-printed Nylon 11 structures using three methods: the proposed acoustic method, the conventional ultrasound pulse-echo method, and the standard mechanical tensile testing. The results show a good match (a 1.13% and 2.05% difference for Young’s modulus and Poisson’s ratio, respectively) between the dynamic elastic properties measured by the acoustic and ultrasound methods, and these dynamic elastic properties are reasonable compared with the static elastic properties measured by the mechanical tensile testing. These results demonstrate the feasibility and reliability of the proposed acoustic method for characterizing 3D-printed solid structures, offering a nondestructive, effective, and cost-effective solution for elastic property characterization in additive manufacturing applications.