2015
DOI: 10.1299/mel.15-00389
|View full text |Cite
|
Sign up to set email alerts
|

Stochastic homogenization analysis of FIB-SEM image-based hierarchical model of sprayed porous ZrO<sub>2</sub>

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2

Citation Types

0
4
0

Year Published

2016
2016
2024
2024

Publication Types

Select...
5

Relationship

3
2

Authors

Journals

citations
Cited by 5 publications
(4 citation statements)
references
References 15 publications
0
4
0
Order By: Relevance
“…The modified FPSH technique can predict large scattering of Young's modulus in mandibular trabecular bone by random parameters as probabilistic characteristics. We also reported that the FPSH could be adapted to porous materials, and its applicability was confirmed [Miyauchi et al, 2015]. Using the FPSH technique and the force-sensitive device, prediction of the relation between the drilling force and drilling depth, and determining the changes in the drilling force caused by changes in bone quality, could be established.…”
Section: Introductionmentioning
confidence: 79%
“…The modified FPSH technique can predict large scattering of Young's modulus in mandibular trabecular bone by random parameters as probabilistic characteristics. We also reported that the FPSH could be adapted to porous materials, and its applicability was confirmed [Miyauchi et al, 2015]. Using the FPSH technique and the force-sensitive device, prediction of the relation between the drilling force and drilling depth, and determining the changes in the drilling force caused by changes in bone quality, could be established.…”
Section: Introductionmentioning
confidence: 79%
“…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%
“…Finally, a nesting function is defined to generate realistic RVE (representative volume element) models of woven fabric composite laminate. The fiber bundles are subdivided into sub-regions that have different fiber volume fraction called microscopic fiber volume fraction, Hagiwara, Ishijima, Takano, Ohtani and Nakai, Mechanical Engineering Journal, Vol.4, No.4 (2017) denote the probabilistic density function, and the following equations express the stochastic modeling of the elastic tensor of composite and constituent materials (Basaruddin, et al, 2013, Miyauchi, et al, 2015. Note here that different type of distribution can be calculated using the characteristic displacements, which is specific in the conventional homogenization theory.…”
Section: Multiscale Modeling Framework For Stochastic Homogenization mentioning
confidence: 99%
“…However, its computational cost is generally huge because many random sampling points should be calculated. To reduce the computational cost, we can find many studies on the probabilistic FEM recently (Stavroulakis, et al, 2014, Miyauchi, et al, 2015. When, first-order perturbation based scheme was used, the drawback is that large scattering can't be solved accurately.…”
Section: Introductionmentioning
confidence: 99%