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Dryad

Optimizing properties on the critical rigidity manifold of underconstrained central-force networks

Data files

Feb 01, 2025 version files 2.19 MB

Abstract

This dataset can be used to generate the figures from the article of the same name published in Physical Review E. These include images of examples of optimized network configurations, distributions and size scaling of several metrics describing network structure and elastic response, optimization time series data, and movies of the optimization process for several objective functions.

Our goal is to develop a design framework for multifunctional mechanical metamaterials that can tune their rigidity while optimizing other desired properties. Towards this goal, we first demonstrate that underconstrained central force networks possess a critical rigidity manifold of codimension one in the space of their physical constraints. We describe how the geometry of this manifold generates a natural parameterization in terms of the states of self-stress, and then use this parameterization to numerically generate disordered network structures that are on the critical rigidity manifold and also optimize various objective functions, such as maximizing the bulk stiffness under dilation, or minimizing length variance to find networks that can be self-assembled from equal-length parts. This framework can be used to design mechanical metamaterials that can tune their rigidity and also exhibit other desired properties.