Session: 16-01-01: Government Agency Student Poster Competition

Paper Number: 149611

149611 - Guided Wave Dispersion Analysis-Based Mechanical Property Characterization for Additive Manufactured Structures 

The evolution of additive manufacturing (AM) has catalyzed a transformative shift in the production of various components, heralding a new era of efficiency and precision in the creation of toolless manufacturing and high-strength structures. The emergence of such techniques has highlighted the critical importance of accurately assessing the mechanical properties of additively manufactured materials to meet rigorous industry standards. However, conventional testing methodologies often fall short of providing precise characterizations of additively manufactured structures. This discrepancy arises not only from the unique challenges presented by layer-wise manufacturing but also from inconsistencies in microstructure, the presence of porosity, and variations in material properties due to thermal gradients and cooling rates during the manufacturing process. Moreover, there is a risk of compromising the integrity of the material during the testing phase, further complicating the assessment of these advanced AM structures.

This study presents an innovative approach that combines nondestructive ultrasound wave sensing and optimization algorithm-enhanced frequency-wavenumber analysis for characterizing the multi-directional mechanical properties of additively manufactured panels. The fabricated materials include, but are not limited to, polymer materials, metals, composite materials, etc. To develop this method, we established a guided wave sensing system, which utilized a piezoelectric actuator (PZT actuator) to generate guided waves in the testing AM panel. A laser Doppler vibrometer (LDV) integrated into a 3D robotic stage acquired guided waves in a non-contact manner. By automatically moving the laser focus point and collecting guided wave signals through 2D grid scanning, our system was able to acquire multiple time-space wavefields. The anisotropic behavior of the 3D printed structure means the scanned time-space wavefield contains a wealth of information about guided waves propagating in all directions and layers. To analyze the acquired wavefield and determine the material properties in different directions or layers, we established a novel inverse method combining multi-directional frequency-wavenumber analysis and a fast dispersion curve regression method based on an optimization algorithm. The material's mechanical properties in each direction were obtained after applying our curve regression method to the experimental dispersion curves. For proof of concept, we conducted a series of experiments to measure the mechanical properties of AM plate structures, including SLS 3D-printed steel panels, material-extrusion thermoset composites, and UV-cured ceramic plates. The experimental results demonstrated that our system could successfully generate guided waves in a testing plate using PZT actuators with programmed excitation signals. Meanwhile, the LDV, integrated with the 3D robotic stage, could acquire time-space wavefields of guided waves in our testing sample. Furthermore, our wavefield analysis method successfully determined multi-directional material properties (e.g., Poisson's ratio and shear wave velocity). This experimental study proves the feasibility of our guided wave sensing system for characterizing the mechanical properties of additive-manufactured plate structures. We anticipate that this research will advance quality monitoring processes in additive manufacturing and may even provide real-time production quality feedback during the AM process.

Presenting Author: Bowen Cai Mississippi State University

Presenting Author Biography: Bowen Cai is a Ph.D. Candidate in Aerospace Engineering at Mississippi State University studying under Dr. Rani Sullivan and Dr. Zhenhua Tian. He is also a research assistant at the Advanced Composite Institute of MSU. His main research direction is acoustic nondestructive testing. He also explores the application of ultrasound and vibration technologies in various fields, including composites and biomaterials. Before pursuing his doctorate, Bowen conducted research in vibration control and finite element analysis of materials. He holds an M.S. in Mechanical Engineering from the University of Dayton and a B.S. in Mechanical Engineering from Tianjin University of Technology.

Authors:

Bowen Cai Mississippi State University
Hunter Watts Mississippi State University
Chuangchuang Sun Mississippi State University
Luyu Bo Virginia Tech
Wayne Huberty Mississippi State University
Zhenhua Tian Virginia Tech