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

Zerhouni, Othmane; Tarantino, M.G.; Danas, Kostas

doi:10.1016/j.compositesb.2018.08.032

Cited by 47 publications

(43 citation statements)

References 53 publications

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“…For the magnetostrictive two-phase composites at hand, we consider a three dimensional cubic periodic RVE, which occupies a reference volume of V # 0 = L 3 . We then generate a random distribution of non-overlapping spherical particles of different size in the RVE using the random sequential adsorption (RSA) algorithm (Rintoul and Torquato, 1997;Segurado and Llorca, 2002;Anoukou et al, 2018;Zerhouni et al, 2019). For efficient meshing and to avoid excessive mesh distortions, the minimum distance between two particles is considered to be 1.05 times the average diameter of the two particles.…”

Section: Numerical Computations Of the Effective Responsementioning

confidence: 99%

“…The primary variables that define a polydisperse RVE is given by the particle volume fraction c, the equivalent number of monodisperse particles N mono , the size ratio of different families and their relative volume proportions. For a detailed discussion of these RVE constructions the reader is referred to the recent works of Anoukou et al (2018), Zerhouni et al (2019) and Tarantino et al (2019).…”

Section: Appendix B: Particle and Mesh Convergencementioning

confidence: 99%

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Microstructurally-guided explicit continuum models for isotropic magnetorheological elastomers with iron particles

Mukherjee

Bodelot

Danas

2020

International Journal of Non-Linear Mechanics

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To cite this version:Dipayan Mukherjee, Laurence Bodelot, Kostas Danas. Microstructurally-guided explicit continuum models for isotropic magnetorheological elastomers with iron particles. AbstractThis work provides a family of explicit phenomenological models both in the F − H and F − B variable space. These models are derived directly from an analytical implicit homogenization model for isotropic magnetorheological elastomers (MREs), which, in turn, is assessed via full-field numerical simulations. The proposed phenomenological models are constructed so that they recover the same purely mechanical, initial and saturation magnetization and initial magnetostriction response of the analytical homogenization model for all sets of material parameters, such as the particle volume fraction and the material properties of the constituents (e.g., the matrix shear modulus, the magnetic susceptibility and magnetization saturation of the particles). The functional form of the proposed phenomenological models is based on simple energy functions with small number of calibration parameters thus allowing for the description of magnetoelastic solids more generally such as anisotropic (with particle-chains) ones, polymers comprising ferrofluid particles or particle clusters. This, in turn, makes them suitable to probe a large set of experimental or numerical results. The models of the present study show that in isotropic MREs, the entire magnetization response is insensitive to the shear modulus of the matrix material even when the latter ranges between 0.003-0.3MPa, while the magnetostriction response is extremely sensitive to the mechanical properties of the matrix material.two-dimensional MREs. Moreover, in an effort to resolve some of the surrounding air and specimen effects, Kalina et al. (2016) have modeled directly the specimen, the surrounding air and the microstructure at the same scale. While this study has led to satisfactory qualitative agreement with experiments, it did not resolve the different length scales as one goes from specimen to microstructure, since that would require an untractable mesh size. Along this effort, Keip and Rambausek (2015) proposed a two-scale finite element approach in order to solve simultaneously the magneto-mechanical boundary value problem and the microstructural problem by properly resolving the separation of the very different length scales. While this last approach is the more complete one, it still remains numerically demanding, especially if complex unit cells with large number of particles are considered. Moreover, in all these approaches, it is very hard to decouple from the estimated response the relative effect of the specimen geometry and that of the microstructure.In this regard, the recent study of Lefèvre et al. (2017) proposes an alternative view to the problem by first solving the homogenization problem at the RVE scale analytically and then using these estimates at the macroscopic scale to analyze the specimen shape effects. In that effort, the authors obtained a very usef...

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Section: Numerical Computations Of the Effective Responsementioning

confidence: 99%

Section: Appendix B: Particle and Mesh Convergencementioning

confidence: 99%

Microstructurally-guided explicit continuum models for isotropic magnetorheological elastomers with iron particles

Mukherjee

Bodelot

Danas

2020

International Journal of Non-Linear Mechanics

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“…The algorithm is highly versatile, and to date it has been used to generate systems containing random distributions of monodisperse (i.e. single sized) [42], [44] and polydisperse spheres [43], and more recently also mono-and polydisperse ellipsoids of arbitrary aspect ratios and orientations [45]. Polydisperse spherical inclusions are generated from the inclusion center and diameter D i , and those intersecting the cell outer surfaces are cut off and copied to the opposite face of the cube.…”

Section: A Modified Rsa Algorithm For the Generation Of Multi-inclusimentioning

confidence: 99%

“…In order to achieve such high volume fractions of inclusions, especially up to 0.82, we need to modify the RSA algorithm adopted in Refs. [43]- [44]. Specifically, the modified RSA algorithm (which is described in detail in Refs.…”

Section: A Modified Rsa Algorithm For the Generation Of Multi-inclusimentioning

confidence: 99%

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Random 3D-printed isotropic composites with high volume fraction of pore-like polydisperse inclusions and near-optimal elastic stiffness

2019

Self Cite

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Highly porous materials with random closed-cell architecture combine isotropy with high stiffness. Yet in practice, the complexity of their manufacturing limits the experimental exploration of these materials, for which studies of the elastic response remain to date mainly theoretical. In this study, we measure experimentally the elastic moduli of random closed-cell porous-like composites fabricated by 3Dprinting. These materials contain a high volume fraction (up to 82 vol pct) of nonoverlapping, polydisperse void-like spherical inclusions, which are randomly dispersed in a homogeneous polymer matrix. We first generate the virtual microstructures of these materials using a random sequential adsorption (RSA) algorithm, and then use numerical homogenization to compute the size of the material representative volume element (RVE). The latter is used to assemble the test samples, whereby the void-like inclusions are 3D-printed using a gel-like polymer with mechanical properties that are in high contrast with those of the base polymer thus behaving mechanically as pores. Experiments reveal that the proposed isotropic

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Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation

Zhao,

Wang,

Zhai

et al. 2024

Advanced Science

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Mechanical metamaterials represent a distinct category of engineered materials characterized by their tailored density distributions to have unique properties. It is challenging to create continuous density distributions to design a smooth mechanical metamaterial sequence in which each metamaterial possesses stiffness close to the theoretical limit in all directions. This study proposes three near‐isotropic, extreme‐stiffness, and continuous 3D mechanical metamaterial sequences by combining topology optimization and data‐driven design. Through innovative structural design, the sequences achieve over 98% of the Hashin–Shtrikman upper bounds in the most unfavorable direction. This performance spans a relative density range of 0.2–1, surpassing previous designs, which fall short at medium and higher densities. Moreover, the metamaterial sequence is innovatively represented by the implicit neural function; thus, it is resolution‐free to exhibit continuously varying densities. Experimental validation demonstrates the manufacturability and high stiffness of the three sequences.

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

Cited by 47 publications

References 53 publications

Microstructurally-guided explicit continuum models for isotropic magnetorheological elastomers with iron particles

Microstructurally-guided explicit continuum models for isotropic magnetorheological elastomers with iron particles

Random 3D-printed isotropic composites with high volume fraction of pore-like polydisperse inclusions and near-optimal elastic stiffness

Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation

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