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Numerically-aided 3D printed random isotropic porous materials approaching the Hashin-Shtrikman bounds

机译:接近Hashin-Shtrikman边界的数字辅助3D打印随机各向同性多孔材料

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The present study introduces a methodology that allows to combine 3D printing, experimental testing, numerical and analytical modeling to create random closed-cell porous materials with statistically controlled and isotropic overall elastic properties that are extremely close to the relevant Hashin-Shtrikman bounds. In this first study, we focus our experimental and 3D printing efforts to isotropic random microstructures consisting of single-sized (i.e. monodisperse) spherical voids embedded in a homogeneous solid matrix. The 3D printed specimens are realized by use of the random sequential adsorption method. A detailed FE numerical study allows to define a cubic representative volume element (RVE) by combined periodic and kinematically uniform (i.e. average strain or affine) boundary conditions. The resulting cubic RVE is subsequently assembled to form a standard dog-bone uniaxial tension specimen, which is 3D printed by use of a photopolymeric resin material. The specimens are then tested at relatively small strains by a proper multi-step relaxation procedure to obtain the effective elastic properties of the porous specimens.
机译:本研究介绍了一种方法,该方法可以将3D打印,实验测试,数值模型和分析模型相结合,以创建具有统计控制和各向同性的整体弹性特性的随机闭孔多孔材料,这些材料非常接近相关的Hashin-Shtrikman边界。在这项第一项研究中,我们将实验和3D打印工作重点放在各向同性的随机微结构上,该结构由嵌入均质固体基质中的单一尺寸(即单分散)球形空隙组成。通过使用随机顺序吸附方法可以实现3D打印样品。详尽的有限元数值研究可通过组合周期性的和运动学上一致的(即平均应变或仿射)边界条件来定义立方代表体积元素(RVE)。随后组装得到的立方RVE,以形成标准的狗骨头单轴拉伸试样,并使用光聚合树脂材料对其进行3D打印。然后通过适当的多步松弛程序在相对较小的应变下测试样品,以获得多孔样品的有效弹性。

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