Chiral two-dimensional periodic blocky materials with elastic interfaces: Auxetic and acoustic properties

Bacigalupo, Andrea; Gambarotta, Luigi

doi:10.1016/j.eml.2020.100769

Cited by 36 publications

(17 citation statements)

References 34 publications

(35 reference statements)

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“…Hence, auxeticity has been observed at different scales, from macro-to nano-dimensions. Apart from examples of natural materials with an intrinsic negative Poisson's coefficient [2][3][4][5], auxetic media are generally artificiallymade systems whose microstructure is designed by exploiting different geometries and mechanisms: re-entrant unit cells [6][7][8][9], star-shaped inclusions [10,11], chiral configurations [12][13][14][15], double arrowhead honeycombs [16], perforations and cuttings [17][18][19][20][21], rotating rigid units [22], lattices [23][24][25] and elastic instabilities [26,27]. Alternative approaches to design auxetic media are presented in the reviews [28][29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical auxetic and isotropic porous medium with extremely negative Poisson’s ratio

Morvaridi

Carta

Bosia

et al. 2021

Extreme Mechanics Letters

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We propose a novel two-dimensional hierarchical auxetic structure, consisting of a porous medium in which a homogeneous matrix includes a rank-two set of cuts characterised by different scales. The six-fold symmetry of the perforations makes the medium isotropic in the plane. Remarkably, the mesoscale interaction between the first-and second-level cuts enables the attainment of a very small value of the Poisson's ratio, close to the minimum reachable limit of -1. The effective properties of the hierarchical auxetic structure are determined numerically, considering both a unit cell with periodic boundary conditions and a finite structure containing a large number of repeating cells. Further, results of the numerical study are validated experimentally on a polymeric specimen with appropriately arranged rank-two cuts, tested under uniaxial tension. We envisage that the proposed hierarchical design can be useful in numerous engineering applications exploiting an extreme auxetic effect.

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Section: Introductionmentioning

confidence: 99%

Hierarchical auxetic and isotropic porous medium with extremely negative Poisson’s ratio

Morvaridi

Carta

Bosia

et al. 2021

Extreme Mechanics Letters

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“…The constitutive parameters depend on the void size. This can also be found in the study by Bacigalupo and Gambarotta [ 50 ] where the regular microstructured composite with voids was studied but with an alternative void-generation approach. They found that the so-called overall elastic modulus and Poisson’s ratio decrease as the void size increases.…”

Section: Numerical Simulationsmentioning

confidence: 58%

“…They found that the results can be described by the elastic Cosserat model. With a homogenization technique, Bacigalupo and Gambarotta [ 50 ] studied auxetic and acoustic properties of a composite with voids as a Cosserat continuum, where the composite is made of hexagonal blocks and elastic interfaces. The effect of void size can be found in this study.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Characterization of Hexagonal Microstructured Materials with Voids from Discrete and Continuum Models

et al. 2022

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The mechanical response of materials such as fiber and particle composites, rocks, concrete, and granular materials, can be profoundly influenced by the existence of voids. The aim of the present work is to study the dynamic behavior of hexagonal microstructured composites with voids by using a discrete model and homogenizing materials, such as micropolar and classical Cauchy continua. Three kinds of hexagonal microstructures, named regular, hourglass, and skew, are considered with different length scales. The analysis of free vibration of a panel described as a discrete system, as a classical and as a micropolar continuum, and the comparison of results in terms of natural frequencies and modes show the advantage of the micropolar continuum in describing dynamic characteristics of orthotropic composites (i.e., regular and hourglass microstructures) with respect to the Cauchy continuum, which gives a higher error in frequency evaluations for all three hexagonal microstructured materials. Moreover, the micropolar model also satisfactorily predicts the behavior of skewed microstructured composites. Another advantage shown here by the micropolar continuum is that, like the discrete model, this continuum is able to present the scale effect of microstructures, while maintaining all the advantages of the field description. The effect of void size is also investigated and the results show that the first six frequencies of the current problem decrease by increasing in void size.

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“…Mechanical parts have been fabricated with characteristics that would have been infeasible using traditional manufacturing processes [ 2 ]. Moreover, a wide range of advanced materials—named metamaterials—have been developed, with tailorable effective mechanical properties [ 3 , 4 , 5 ] and design flexibility that has opened new frontiers in the control of the functional response of structural components [ 6 , 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Cellular Materials through Multiscale, Variable-Section Inner Designs: Mechanical Attributes and Neural Network Modeling

Karathanasopoulos

Rodopoulos

2022

Materials

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In the current work, the mechanical response of multiscale cellular materials with hollow variable-section inner elements is analyzed, combining experimental, numerical and machine learning techniques. At first, the effect of multiscale designs on the macroscale material attributes is quantified as a function of their inner structure. To that scope, analytical, closed-form expressions for the axial and bending inner element-scale stiffness are elaborated. The multiscale metamaterial performance is numerically probed for variable-section, multiscale honeycomb, square and re-entrant star-shaped lattice architectures. It is observed that a substantial normal, bulk and shear specific stiffness increase can be achieved, which differs depending on the upper-scale lattice pattern. Subsequently, extended mechanical datasets are created for the training of machine learning models of the metamaterial performance. Thereupon, neural network (NN) architectures and modeling parameters that can robustly capture the multiscale material response are identified. It is demonstrated that rather low-numerical-cost NN models can assess the complete set of elastic properties with substantial accuracy, providing a direct link between the underlying design parameters and the macroscale metamaterial performance. Moreover, inverse, multi-objective engineering tasks become feasible. It is shown that unified machine-learning-based representation allows for the inverse identification of the inner multiscale structural topology and base material parameters that optimally meet multiple macroscale performance objectives, coupling the NN metamaterial models with genetic algorithm-based optimization schemes.

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Chiral two-dimensional periodic blocky materials with elastic interfaces: Auxetic and acoustic properties

Cited by 36 publications

References 34 publications

Hierarchical auxetic and isotropic porous medium with extremely negative Poisson’s ratio

Hierarchical auxetic and isotropic porous medium with extremely negative Poisson’s ratio

Dynamic Characterization of Hexagonal Microstructured Materials with Voids from Discrete and Continuum Models

Enhanced Cellular Materials through Multiscale, Variable-Section Inner Designs: Mechanical Attributes and Neural Network Modeling

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