Session: SYMP 7-1: Energy Harvesting with Metamaterials

Paper Number: 137019

137019 - Damping Optimization in Locally Resonant Metastructures via Hybrid Ga-Pso Algorithms and Modal Analysis 

This paper focuses on improving vibration suppression within locally resonant metastructures by optimizing their bandgap responses. The primary aim is to enhance damping estimation through the combined use of modal analysis and computational algorithms. A method is presented, merging a Hybrid Genetic Algorithm-Particle Swarm Optimization (GA-PSO) with conventional methods such as the Nelder-Mead simplex, in estimating parameters accurately. This hybrid technique undergoes thorough testing against theoretical models that include noise elements and is further substantiated through a series of detailed experimental validations.

The research primarily examines an aluminum rectangular beam metastructure, uniquely fitted with internal local resonators. To effectively analyze the modal dynamics and the system's transfer functions, a distributed parameter model is employed. This model is instrumental in unraveling the nuances of natural frequencies, mode shapes, and their consequent influence on the bandgap characteristics of the structure. A sophisticated mathematical framework is constructed, consisting of a series of partial differential equations. These equations are crucial in capturing the intricate dynamics of the system, with a particular focus on the interaction between the local resonators and the main beam. For a more streamlined analysis of the system's behavior, the modal decomposition method is utilized. This technique greatly simplifies the examination of the dynamics inherent in the flexible beam integrated with resonators.

A significant part of the experiment concentrates on accurately estimating the structural modal damping ratio, denoted as $\zeta_m$, by using the Hybrid GA-PSO algorithm. The results from this experiment strikingly demonstrate the algorithm's precision in predicting the dynamic behavior of the system, thereby underscoring its practical utility in the realm of vibration control.

One of the research's pivotal aspects is the comparative analysis of various optimization algorithms. This comparison crucially highlights the superior efficacy of the Hybrid GA-PSO algorithm in accurately estimating both the resonator damping ratio ($\zeta_r$) and the structural modal damping ratio ($\zeta_m$). The high degree of correlation between the algorithm's predictions and the empirical data gathered from experiments solidifies its effectiveness in navigating the complexities of dynamic systems.

In conclusion, this study marks a significant advancement in the field of metamaterials, with a specific focus on vibration suppression. The findings shed light on the transformative impact of AI-driven optimization algorithms in the conceptualization and dynamic management of metastructures. The research not only deepens the understanding of metamaterial dynamics but also paves the way for innovative approaches in materials engineering and vibration control. This exploration into the integration of computational algorithms with physical models opens new frontiers in the design and optimization of advanced materials, potentially revolutionizing how we approach material engineering and related fields.

 

 

 

 

 

 

 

Presenting Author: Eduard Petlenkov Tallinn University of Technology

Presenting Author Biography: Eduard Petlenkov

Authors:

Hossein Alimohammadi
Kristina Vassiljeva
S. Hassan HosseinNia
Peeter Ellervee
Eduard Petlenkov