General formulation of the first-order perturbation-based stochastic homogenization method using many random physical parameters for multi-phase composite materials

Wen, Pin; Takano, Naoki; Akimoto, Shusuke

doi:10.1007/s00707-017-2096-9

Cited by 7 publications

(2 citation statements)

References 46 publications

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“…Similarly, the SVE strain field can be decomposed into a homogeneous term and a fluctuation term. Because the volume average of this strain field is equal to the macroscopic strain, the volume average of the displacement fluctuation term or the strain fluctuation term needs to equal 0 [9].…”

Section: First-order Perturbation Based Stochastic Homogenization (Fpmentioning

confidence: 99%

“…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]. Additionally, the accuracy of the FPSH was verified and compared with the MCS.…”

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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Section: First-order Perturbation Based Stochastic Homogenization (Fpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%