Date of Award
2024
Document Type
Open Access Dissertation
Degree Name
Doctor of Philosophy in Mechanical Engineering-Engineering Mechanics (PhD)
Administrative Home Department
Department of Mechanical and Aerospace Engineering
Advisor 1
Vijaya V. N. Sriram Malladi
Committee Member 1
Jason R. Blough
Committee Member 2
Pablo A. Tarazaga
Committee Member 3
Trisha Sain
Abstract
The effective attenuation of wave propagation in specific frequency ranges, known as bandgaps, makes metastructures valuable in various engineering applications. Traditionally, bandgap estimation has relied on physics-based models, which present challenges for complex metastructures where accurate material properties and geometric complexities make precise modeling difficult. This work introduces data-driven techniques for bandgap estimation, leveraging the dynamic behavior, particularly the Frequency Response Functions (FRFs) of unit cells, to calculate dispersion relations and couple unit cells through dynamic substructuring. This approach addresses the limitations of traditional methods by directly utilizing experimental data to characterize both longitudinal and flexural bandgaps.
To evaluate data-driven techniques, this research applies the transfer matrix method to estimate longitudinal bandgaps, using an innovative method to quantify energy loss in these frequency regions. For flexural bandgaps, a curve-fitting technique estimates rotational responses from translational data, enabling effective coupling and facilitating dynamic substructuring in complex configurations. Further, a new method for calculating rigid body modes using the Polymax algorithm refines flexural bandgap estimation from minimal measurement points, advancing the robustness and applicability of data-driven bandgap analysis.
Expanding on metastructural applications, this work presents the design of a frequency-selective locally resonant metastructure, inspired by the frequency-tuning properties of the mammalian cochlea. Utilizing data-driven optimization, resonators tuned to multiple frequencies are strategically arranged to produce broad-range attenuation. Finally, the study explores the Kresling origami metastructure, examining its nonlinear dynamic behavior and bandgap properties in both simulation and experimental settings.
In summary, this work demonstrates that data-driven techniques can effectively overcome the limitations of traditional bandgap estimation methods, offering a novel approach for tailoring metastructures in applications requiring precise frequency-selective behavior. This framework has broad potential in advancing metastructure design for diverse engineering solutions.
Recommended Citation
Gosavi, Hrishikesh Suhas, "DATA TO PHYSICS: BRIDGING MODELING FRAMEWORKS FOR METASTRUCTURES", Open Access Dissertation, Michigan Technological University, 2024.