Estimation of Elastic Band Gaps Using Data-Driven Modeling
Document Type
Book Chapter
Publication Date
10-5-2021
Department
Department of Mechanical Engineering-Engineering Mechanics
Abstract
The paper discusses estimation of elastic band gaps of a one-dimensional periodic structure using the frequency response functions (FRFs) of a unit cell. A unit cell considered in this paper consists of two masses with a spring between them. Such unit cells are connected with a coupled spring to design a periodic lattice structure. The paper establishes the FRF for a different number of unit cells using FRF-based sub-structuring (FBS). The wave-equation method is then used to estimate the dispersion curves and eventually band gaps. The paper follows a data-driven modeling approach to develop state-space models for estimating dispersion curves from FRFs. The vector fitting algorithm creates a data-driven model of the unit cell from noisy FRFs. A multi-unit cell lattice is simulated from data-driven models using FBS. Additionally, the paper investigates tuning of elastic band gaps by changing the mass and the stiffness of the unit cells.
Publication Title
Data Science in Engineering
Recommended Citation
Gosavi, H.,
&
Sriram Malladi, V. V.
(2021).
Estimation of Elastic Band Gaps Using Data-Driven Modeling.
Data Science in Engineering,
9, 65-69.
http://doi.org/10.1007/978-3-030-76004-5_8
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/16811