Term of Award

Summer 2023

Degree Name

Master of Science, Mechanical Engineering

Document Type and Release Option

Thesis (restricted to Georgia Southern)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Department

Department of Mechanical Engineering

Committee Chair

Jinki Kim

Committee Member 1

JungHun Choi

Committee Member 2

Biswanath Samanta

Committee Member 3

Valentin Soloiu

Abstract

Soft materials play an increasingly vital role in a wide range of applications, such as tissue engineering, additive manufacturing, and infrastructure design. Therefore, understanding their mechanical properties and behavior is crucial. This study explores the potential of vibration analysis for identifying the material properties of soft materials and the health state of additively manufactured systems. Specifically, gelatin-based hydrogels and cohesive soils are the focal points of this research due to their extensive usage in the aforementioned domains. To explore the material properties of hydrogels, an innovative vibration-based approach is proposed. This method allows for non-contact and simultaneous measurement of the elastic moduli. By employing phase-based motion estimation, the modal characteristics of gelatin-based hydrogels are extracted, which, in turn, are used to determine the material properties using an analytical model. Experimental and numerical investigation results confirm the reliable identification of the material properties using the proposed approach. Expanding on these findings, a video-based method is introduced to determine the liquid limit of cohesive soils which enables non-contact, non-destructive, and objective assessment of the mechanical properties. Experimental results further validate the precise identification of the liquid limit, demonstrating the potential for a simple implementation utilizing readily available digital cameras or smartphones. This eliminates the need for specialized equipment and removes the dependence on the operator's proficiency. Additionally, this study harnesses the power of LSTM and GRU models to characterize anomalies in random vibration signals of additively manufactured structures. A novel amplitude-based filtering algorithm is proposed, demonstrating improved accuracy and efficiency in characterizing structural health when compared to using raw displacement signals. Power spectral density analysis provides further evidence of the algorithm's efficacy, showcasing its exceptional potential for defect identification. In summary, this study pioneers innovative non-contact methods for characterizing the mechanical properties of non-rigid materials and identifying defects in additively manufactured structures. The proposed techniques present significant advancements in the field, enabling more accurate and efficient assessments of material behavior and structural integrity. These findings hold immense promise for various applications, facilitating advancements in tissue engineering, bio-fabrication, and infrastructure design.

OCLC Number

1411227541

Research Data and Supplementary Material

No

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