Probabilistic multiscale analysis of three-phase composite material considering uncertainties in both physical and geometrical parameters at microscale

Wen, Pin; Takano, Naoki; Kurita, Daichi

doi:10.1007/s00707-016-1640-3

Cited by 13 publications

(11 citation statements)

References 17 publications

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“…The size of RVE over real specimen showed a scaling ratio smaller than 1/1000. Asymptotic homogenization theory (Supporting Note 1) [40][41][42][43][44] could be employed to compute threedimensional voxel model with 2.5 million elements and 4.08 million nodes. The 4% tension strain was then applied on right side along z-direction while constraint was put on the other side.…”

Section: Resultsmentioning

confidence: 99%

Customizable fabrication for auxetic graphene assembled macrofilms with high conductivity and flexibility

Wang

Song

Qian

et al. 2020

Carbon

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Auxetic materials with negative Poisson's ratios unusually exhibit intuitive mechanical behaviors, such as cross-section expansion instead of contraction during tension. Such behaviors are interesting because they may enhance unusual mechanical properties. However, controllable preparation of materials with negative Poisson's ratio is still a major challenge.In this study, we report the synthesis of a flexible auxetic graphene assembled macrofilm (GAMF) from graphene oxide nanosheets by a thermal annealing and press assistant method.The obtained materials exhibit good flexibility and significantly wide tunable negative Poisson s ratios ranging from -0.11 to -0.53. We also develop a reconstruction model for characterization the uniaxial tension of GAMF based on X-ray tomographic images. The tensile simulation result predicts the function relationship between Poisson's ratio and critical thickness of pore channels, which is in good agreement with the experimental data. As a result, an effective tunable way is proposed for customizable fabrication of GAMF with tunable negative Poisson's ratios, and the GAMF materials with good flexibility, high electrical conductivity and superior auxetic behavior looks promising for future development of wearable electronics.

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Section: Resultsmentioning

confidence: 99%

Customizable fabrication for auxetic graphene assembled macrofilms with high conductivity and flexibility

Wang

Song

Qian

et al. 2020

Carbon

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“…To express the randomness in the physical parameters of constituents, = 1 , 2 , … is used. In this formulation,f ( ) complies with a normal distribution corresponding to Exp(f ( )) = 0 and Var(f ( )) = 2 [8]. Usually, depends on λ and therefore is defined at the microscopic scale.…”

Section: First-order Perturbation Based Stochastic Homogenization (Fpmentioning

confidence: 99%

“…One of the authors introduced a first-order perturbation based stochastic homogenization (FPSH) method for random modelling in the estimation of mechanical properties of human vertebral trabecular bone [5]. Afterward, this method was applied to analyze three-phase composite material considering randomness in both physical and geometrical parameters at the microscale [8]. The FPSH method has been developed for considering many random physical parameters in constituent materials to clarify the effect of randomness in each engineering constant of constituent mechanical properties [9].…”

Section: Introductionmentioning

confidence: 99%

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Stochastic nonlinear multiscale computational scheme for short fiber reinforced composites to study the influence of microstructural variability on damage propagation

Hoang

Abe

Nakamura³

et al. 2020

SN Appl. Sci.

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In this paper, a stochastic nonlinear multiscale computational scheme is proposed to study the influence of the variability in both physical parameters of constituent materials and geometrical parameters such as fiber orientation, fiber arrangement of short fiber reinforced composites on the damage propagation. The aim is to predict many probable damage patterns in a huge number of scenarios under complex strain conditions and to discuss the influential level of variability in the physical and geometrical parameters for short fiber reinforced composites. The parameterization and numerical modelling for short fiber reinforced plastics made by injection molding are conducted. The random physical parameters are considered theoretically by the first-order perturbation based stochastic homogenization method, while sampling is used for the random geometrical parameters. When the scenario becomes huge in the stochastic nonlinear analysis, a computational scheme using sub-sampling is proposed. Moreover, the stochastic prediction of the homogenized properties of the composite material and their probable degradation are discussed. The stochastic computation of microscopic strains is analyzed though the damage propagation simulation. When the geometrical variability is considered, a definition of an average strain distribution among many samples is also presented. The efficiency of the accelerated element-by-element scaled conjugate gradient iterative solver is shown by solving many three-dimension random short fiber reinforced models with hundreds of thousands of degrees of freedom. The stochastic computational scheme provides a suitable reference to predict failure under specific reliability requirements of short fiber reinforced composites or other composite materials.

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“…The former means the parameters to express the uncertainty in the elastic moduli of fiber, fiber bundle and matrix resin. One of the authors has so far presented the formulation of first-order perturbation based stochastic homogenization (FPSH) method and its applications to porous material (Miyauchi, et al, 2015 and particulate embedded composite materials (Wen, et al, 2016). The main contribution of this paper lies in the parameterization of geometrical features of plain woven fabric composite laminate made by hand layup and the model generation algorithm based on the statistically measured data.…”

Section: Multiscale Modeling Framework For Stochastic Homogenization mentioning

confidence: 99%

Parameterization, statistical measurement and numerical modeling of fluctuated meso/micro-structure of plain woven fabric GFRP laminate for quantification of geometrical variability

Hagiwara

Ishijima

Takano

et al. 2017

Mechanical Engineering Journal

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Probabilistic multiscale analysis of three-phase composite material considering uncertainties in both physical and geometrical parameters at microscale

Cited by 13 publications

References 17 publications

Customizable fabrication for auxetic graphene assembled macrofilms with high conductivity and flexibility

Customizable fabrication for auxetic graphene assembled macrofilms with high conductivity and flexibility

Stochastic nonlinear multiscale computational scheme for short fiber reinforced composites to study the influence of microstructural variability on damage propagation

Parameterization, statistical measurement and numerical modeling of fluctuated meso/micro-structure of plain woven fabric GFRP laminate for quantification of geometrical variability

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