2004
DOI: 10.1016/j.actamat.2004.04.007
|View full text |Cite
|
Sign up to set email alerts
|

Micromechanics-based elastic model for functionally graded materials with particle interactions

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

2
69
0
2

Year Published

2006
2006
2015
2015

Publication Types

Select...
5
4

Relationship

0
9

Authors

Journals

citations
Cited by 109 publications
(73 citation statements)
references
References 25 publications
2
69
0
2
Order By: Relevance
“…), it is possible to describe the behaviour of each macroscopic material point by means of its relevant effective properties obtained via standard homogenisation techniques for statistically homogeneous aggregates. Instead, care must be taken in estimating the effective properties within regions where the microstructure varies rapidly (see, e.g., Reiter et al 1997;Yin et al 2004).…”
Section: Introductionmentioning
confidence: 99%
“…), it is possible to describe the behaviour of each macroscopic material point by means of its relevant effective properties obtained via standard homogenisation techniques for statistically homogeneous aggregates. Instead, care must be taken in estimating the effective properties within regions where the microstructure varies rapidly (see, e.g., Reiter et al 1997;Yin et al 2004).…”
Section: Introductionmentioning
confidence: 99%
“…Thus, focusing on this issue, some specific material models were developed to estimate the effective properties of FGMs. For instance, Yin et al [27] developed a material model based on the Eshelby's equivalent inclusion method with pairwise particle interaction, and Aboudi et al [26] developed a higherorder numerical cell theory. In this work, a rather simple and generic type of material model will be applied to estimate the effective properties of FGMs.…”
Section: A Functionally Graded Materials Modelmentioning
confidence: 99%
“…Thus, some specific FGMs speciahzed material models have been developed such as Yin et al [13] and Aboudi et al [12].…”
Section: A Functionally Graded Materlvl Modelmentioning
confidence: 99%