Uncertainty modeling in the prediction of effective mechanical properties using stochastic homogenization method with application to porous trabecular bone

Khairul Salleh Basaruddin, Naoki Takano, Hikaru Akiyama, Takayoshi Nakano

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

A systematic modeling of uncertainty due to image processing, material characteristics and experimental works was developed in order to propose a novel stochastic image-based multi-scale method for heterogeneous media. The effective mechanical properties with application to three porous trabecular bone models were predicted by introducing the correction factor (β) to represent the miscellaneous errors or unknown factors. Finally, the probability density was obtained for the effective mechanical properties, which could evaluate the reliability of scattered experimental results. It has been concluded that variation in effective properties of heterogeneous media can be predicted even when only limited measured values are available by using the present extrapolation technique based on verified simulation results.

Original languageEnglish
Pages (from-to)1250-1256
Number of pages7
JournalMaterials Transactions
Volume54
Issue number8
DOIs
Publication statusPublished - 2013

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Homogenization method
homogenizing
bones
Bone
mechanical properties
Mechanical properties
predictions
Extrapolation
image processing
extrapolation
Image processing
simulation
Uncertainty

Keywords

  • Image-based modeling
  • Porous microstructure
  • Stochastic homogenization method
  • Uncertainty

ASJC Scopus subject areas

  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanical Engineering
  • Mechanics of Materials

Cite this

Uncertainty modeling in the prediction of effective mechanical properties using stochastic homogenization method with application to porous trabecular bone. / Basaruddin, Khairul Salleh; Takano, Naoki; Akiyama, Hikaru; Nakano, Takayoshi.

In: Materials Transactions, Vol. 54, No. 8, 2013, p. 1250-1256.

Research output: Contribution to journalArticle

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