This study introduces a hierarchical design methodology for functional waveguides, utilizing 2D honeycombs with stepwise geometric variations as foundational microstructures, focusing on the tunability of time-domain responses under impact loads. By maintaining constant homogenized density, our approach manipulates stiffness along the wave propagation path. A semi-empirical model, based on curve-fitting to finite element solutions, accurately predicts dynamic responses including wave propagation speed, force transmission to supports, and reflected velocities at the tip. Using Ashby plots, we develop a modular strategy for assembling waveguide bundles – or even bundles of bundles – to meet specific performance criteria, enhancing design efficiency. This framework, ideal for integrating with machine learning and multi-objective optimization, enables tailored designs for applications ranging from impact protection to smart actuation in aerospace, automotive, and biomedical sectors, marking significant advancements in material design for dynamic environments.
An Innovative Hierarchical Design of Hybrid Meta-Structures for Longitudinal Waveguides / Heshmati, Mahmood; Jalali, S. Kamal; Pugno, Nicola M.. - In: INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES. - ISSN 0020-7403. - 2025, 287:(2025), pp. 1-13. [10.1016/j.ijmecsci.2025.109963]
An Innovative Hierarchical Design of Hybrid Meta-Structures for Longitudinal Waveguides
Pugno, Nicola M.
Ultimo
2025-01-01
Abstract
This study introduces a hierarchical design methodology for functional waveguides, utilizing 2D honeycombs with stepwise geometric variations as foundational microstructures, focusing on the tunability of time-domain responses under impact loads. By maintaining constant homogenized density, our approach manipulates stiffness along the wave propagation path. A semi-empirical model, based on curve-fitting to finite element solutions, accurately predicts dynamic responses including wave propagation speed, force transmission to supports, and reflected velocities at the tip. Using Ashby plots, we develop a modular strategy for assembling waveguide bundles – or even bundles of bundles – to meet specific performance criteria, enhancing design efficiency. This framework, ideal for integrating with machine learning and multi-objective optimization, enables tailored designs for applications ranging from impact protection to smart actuation in aerospace, automotive, and biomedical sectors, marking significant advancements in material design for dynamic environments.| File | Dimensione | Formato | |
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