An optimization-based design framework is proposed to tune the response of soft metamaterials involving both geometric instabilities and nonlinear viscoelastic material behavior. Designing the response of soft metamaterials to harness instabilities and undergo large, tailored configuration changes will enable advancements in soft robotics, shock and vibration mitigation, and flexible electronics. In line with the metamaterial concept, the response of these materials is governed to a large extent by the geometric and topological makeup of their small-scale features. However, the link between structure and response is less intuitive for soft metamaterials due to their reliance upon highly nonlinear responses triggered by geometric instabilities. This is further complicated by the effects of viscoelastic relaxation, which recent studies have shown to alter the emergence of instabilities in non-intuitive ways. Here, these effects are accounted for in our framework to achieve various design objectives, including tailored force–displacement response and maximized energy absorption from both geometric and material effects. To fully automate this process, it is essential to have a completely robust equation solver for forward problems involving instabilities and viscoelastic relaxation. We achieve this by casting the search for stable mechanical equilibrium — i.e. the forward problem — as a minimization problem and utilize a trust region algorithm to robustly handle instabilities and follow energetically-favorable equilibrium paths through critical points.
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Alberdi, Ryan, et al. "An optimization-based approach to tailor the mechanical response of soft metamaterials undergoing rate-dependent instabilities." Computer Methods in Applied Mechanics and Engineering, vol. 435, Dec. 2024. https://doi.org/10.1016/j.cma.2024.117679
Alberdi, Ryan, Hamel, Craig, Talamini, Brandon, & Tupek, Michael R. (2024). An optimization-based approach to tailor the mechanical response of soft metamaterials undergoing rate-dependent instabilities. Computer Methods in Applied Mechanics and Engineering, 435. https://doi.org/10.1016/j.cma.2024.117679
@article{osti_2498462,
author = {Alberdi, Ryan and Hamel, Craig and Talamini, Brandon and Tupek, Michael R.},
title = {An optimization-based approach to tailor the mechanical response of soft metamaterials undergoing rate-dependent instabilities},
annote = {An optimization-based design framework is proposed to tune the response of soft metamaterials involving both geometric instabilities and nonlinear viscoelastic material behavior. Designing the response of soft metamaterials to harness instabilities and undergo large, tailored configuration changes will enable advancements in soft robotics, shock and vibration mitigation, and flexible electronics. In line with the metamaterial concept, the response of these materials is governed to a large extent by the geometric and topological makeup of their small-scale features. However, the link between structure and response is less intuitive for soft metamaterials due to their reliance upon highly nonlinear responses triggered by geometric instabilities. This is further complicated by the effects of viscoelastic relaxation, which recent studies have shown to alter the emergence of instabilities in non-intuitive ways. Here, these effects are accounted for in our framework to achieve various design objectives, including tailored force–displacement response and maximized energy absorption from both geometric and material effects. To fully automate this process, it is essential to have a completely robust equation solver for forward problems involving instabilities and viscoelastic relaxation. We achieve this by casting the search for stable mechanical equilibrium — i.e. the forward problem — as a minimization problem and utilize a trust region algorithm to robustly handle instabilities and follow energetically-favorable equilibrium paths through critical points.},
doi = {10.1016/j.cma.2024.117679},
url = {https://www.osti.gov/biblio/2498462},
journal = {Computer Methods in Applied Mechanics and Engineering},
issn = {ISSN 0045-7825},
volume = {435},
place = {United States},
publisher = {Elsevier},
year = {2024},
month = {12}}