Probabilistic homogenization and sensitivity analysis for robust design of coated particulate composite material considering non-parametric geometrical uncertainty at microscale

Pin Wen, Kosho Kamijo, Daichi Kurita, Naoki Takano

Research output: Contribution to journalArticle

Abstract

The aim of this study is that with consideration of geometrical fluctuation, robust design is made to assure performance of material more reliable to fabrication process. Firstly a target microstructure is defined as the optimum solution for coated particulate material. Then a slightly fluctuated computational models are generated in which some random variables are defined. Multiscale analysis is done to obtain homogenized Young’s modulus, shear modulus and an index with respect to strength. Probabilistic sensitivity for those quantities of interest against design variables is analyzed by means of response surface method. For response surface, this paper studies a case where the scattering of sampling points is clustered. The characteristics of cluster sampling points determine the response surface strategy as quadratic polynomial and least square regression method. Finally the numerical result of a specific robust design for coated particulate composite material reveals that when the mean radius of particle is bigger and mean coating thickness is smaller, the less sensitive index is. It will provide a reliable guidance and save cost in the development of wide range of composite materials.

Original languageEnglish
Article number20160005
JournalTransactions of the Japan Society for Computational Engineering and Science
Volume2016
Publication statusPublished - 2016 Feb 22

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Sensitivity analysis
Composite materials
Elastic moduli
Sampling
Random variables
Polynomials
Scattering
Fabrication
Coatings
Microstructure
Uncertainty
Costs

Keywords

  • Composite material
  • Homogenization
  • Microstructure
  • Probabilistic analysis
  • Robust design

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

Cite this

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abstract = "The aim of this study is that with consideration of geometrical fluctuation, robust design is made to assure performance of material more reliable to fabrication process. Firstly a target microstructure is defined as the optimum solution for coated particulate material. Then a slightly fluctuated computational models are generated in which some random variables are defined. Multiscale analysis is done to obtain homogenized Young’s modulus, shear modulus and an index with respect to strength. Probabilistic sensitivity for those quantities of interest against design variables is analyzed by means of response surface method. For response surface, this paper studies a case where the scattering of sampling points is clustered. The characteristics of cluster sampling points determine the response surface strategy as quadratic polynomial and least square regression method. Finally the numerical result of a specific robust design for coated particulate composite material reveals that when the mean radius of particle is bigger and mean coating thickness is smaller, the less sensitive index is. It will provide a reliable guidance and save cost in the development of wide range of composite materials.",
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AU - Wen, Pin

AU - Kamijo, Kosho

AU - Kurita, Daichi

AU - Takano, Naoki

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N2 - The aim of this study is that with consideration of geometrical fluctuation, robust design is made to assure performance of material more reliable to fabrication process. Firstly a target microstructure is defined as the optimum solution for coated particulate material. Then a slightly fluctuated computational models are generated in which some random variables are defined. Multiscale analysis is done to obtain homogenized Young’s modulus, shear modulus and an index with respect to strength. Probabilistic sensitivity for those quantities of interest against design variables is analyzed by means of response surface method. For response surface, this paper studies a case where the scattering of sampling points is clustered. The characteristics of cluster sampling points determine the response surface strategy as quadratic polynomial and least square regression method. Finally the numerical result of a specific robust design for coated particulate composite material reveals that when the mean radius of particle is bigger and mean coating thickness is smaller, the less sensitive index is. It will provide a reliable guidance and save cost in the development of wide range of composite materials.

AB - The aim of this study is that with consideration of geometrical fluctuation, robust design is made to assure performance of material more reliable to fabrication process. Firstly a target microstructure is defined as the optimum solution for coated particulate material. Then a slightly fluctuated computational models are generated in which some random variables are defined. Multiscale analysis is done to obtain homogenized Young’s modulus, shear modulus and an index with respect to strength. Probabilistic sensitivity for those quantities of interest against design variables is analyzed by means of response surface method. For response surface, this paper studies a case where the scattering of sampling points is clustered. The characteristics of cluster sampling points determine the response surface strategy as quadratic polynomial and least square regression method. Finally the numerical result of a specific robust design for coated particulate composite material reveals that when the mean radius of particle is bigger and mean coating thickness is smaller, the less sensitive index is. It will provide a reliable guidance and save cost in the development of wide range of composite materials.

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