Summary
This study deals with the design of distributed internal oscillators in a metastructure to achieve its beneficial low-frequency vibration performance. First, an analytical approach is taken in which all of them are equal mutually and tuned to the first resonance of the metastructure with blocked internal oscillators. As tuning to the second resonance frequency of the metastructure of this shape could not be achieved practically, a physics-based machine learning approach is developed to design absorbers of different size and distribution along the metastructure, targeting the widest possible low-frequency vibration attenuation regions around the first and second resonance simultaneously. Such metastructure is then fabricated and its beneficial performance is verified experimentally.
