Random Auxetic Porous Materials from Parametric Growth Processes. (October 2021) - Martínez, Jonàs
Abstract: We introduce a computational approach to optimize random porous materials via parametric growth processes. We focus on the problem of minimizing the Poisson's ratio of a two-phase porous random material, which results in an auxetic material. Initially, we perform a parametric optimization of the growth process. Afterward, the optimized parametric growth process implicitly generates an auxetic random material. Namely, the growth process intrinsically entails the formation of an auxetic material. Our approach enables the computation of large-scale auxetic random materials in commodity computers. We also provide numerical results indicating that the computed auxetic materials have close to isotropic linear elastic behavior and physical tests revealing auxetic behavior. Graphical abstract: Highlights: A growth process that is able to generate a random auxetic porous materials. Randomly placed non-overlapping cells that grow according to a parametric growth law. The growth process can be computed very efficiently in commodity computers.