Multiscale modeling and optimization of the mechanics of hierarchical metamaterials
- PDF / 3,984,155 Bytes
- 9 Pages / 585 x 783 pts Page_size
- 56 Downloads / 228 Views
Introduction At the beginnings of metamaterials stood a theoretical prediction1 regarding negative-refractive-index photonic materials whose experimental realization was to follow only decades later.2 When it comes to mechanical metamaterials, theoreticalcomputational predictions also play a significant role in guiding the metamaterial design and optimization process. Yet, recent accelerated advances in small-scale fabrication3 have made it challenging for theory and simulations to keep up with the pace of new experimental opportunities. Considerable challenges stem from, among others, (1) the various scales involved4 (from nanometer-scale features to macroscale samples), (2) the failure of separating material-level from structural-level behavior in small-scale structures,4–6 (3) the multiphysics nature of the phenomena at play, (4) the tremendous multiscale design space, and (5) the growing importance of imperfections with decreasing length scale.7 The goal of any modeling approach is the accurate prediction of the effective (meta)materials properties in order to replace expensive trial-and-error experimentation by a simulationguided exploration and optimization of the design space, as
well as to assist in shedding light on the observed physical principles at play. This article focuses on modeling cellular metamaterials (including the broad and popular classes of truss-, plate-, and shell-based architectures), while many of the techniques are widely applicable beyond the scope of this contribution. Further, we treat perfect systems, while imperfections are discussed elsewhere.7 Cellular metamaterials are intriguing for a number of reasons. Their low relative density offers lightweight solutions for applications ranging from aerospace and transportation to clothing, medical devices, and personal protection. Large surface-to-volume ratios make them ideal for multiphysics applications such as catalysis, heat exchange, and fluid mixing. Additionally (and essential here), the underlying structural architecture allows simulation approaches pioneered at classical engineering scales without the statistical complications of atomic-scale simulations, which makes for intuitive design guidelines. One may further differentiate between periodic architectures (based on the tessellation of a unit cell, so that modeling techniques may exploit the periodicity and symmetries of the system), aperiodic, random
Dennis M. Kochmann, ETH Zürich, Switzerland; [email protected] Jonathan B. Hopkins, University of California, Los Angeles, USA; [email protected] Lorenzo Valdevit, University of California, Irvine, USA; [email protected] doi:10.1557/mrs.2019.228
• VOLUME © 2019 Materials Research Society MRS BULLETIN 44 • OCTOBER 2019 • www.mrs.org/bulletin Downloaded from https://www.cambridge.org/core. University of Otago Library, on 13 Oct 2019 at 07:12:11, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1557/mrs.2019.228
773
MULTISCALE MODELING AND OPTIMIZATION OF THE MECHANI
Data Loading...
