Experimental realization of physical reservoir computing-based mechano-intelligence in self-adaptive phononic metastructures

Yuning Zhang; Aditya Deshmukh; K. W. Wang

doi:10.1117/12.2657277

28 April 2023 Experimental realization of physical reservoir computing-based mechano-intelligence in self-adaptive phononic metastructures

Yuning Zhang, Aditya Deshmukh, K. W. Wang

Author Affiliations +

Proceedings Volume 12483, Active and Passive Smart Structures and Integrated Systems XVII; 124830B (2023) https://doi.org/10.1117/12.2657277
Event: SPIE Smart Structures + Nondestructive Evaluation, 2023, Long Beach, California, United States

Abstract

This research experimentally investigates the integration of mechano-intelligence into mechanical metastructures for self-adaptive wave control. We created a phononic metastructure prototype utilizing periodic buckled beam modules that has highly adjustable wave propagation characteristics via length reconfiguration using a linear displacement actuator. By utilizing the physical reservoir computing framework, we show that the proposed metastructure can recognize and self-adapt to different inputs by making decisions on appropriate actuations to reconfigure itself to achieve an intelligent wave blocking task. Overall, this research provided a promising approach for constructing and integrating functional mechano-intelligence in structures harnessing physical computing and learning, and created a new direction for the next generation of adaptive structures and material systems.

Conference Presentation

Citation Download Citation

Yuning Zhang, Aditya Deshmukh, and K. W. Wang "Experimental realization of physical reservoir computing-based mechano-intelligence in self-adaptive phononic metastructures", Proc. SPIE 12483, Active and Passive Smart Structures and Integrated Systems XVII, 124830B (28 April 2023); https://doi.org/10.1117/12.2657277

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