A unified framework for stochastic predictions of mechanical properties of polymeric nanocomposites

N. Vu-Bac, M. Silani, T. Lahmer, X. Zhuang, Timon Rabczuk

Research output: Contribution to journalArticle

89 Citations (Scopus)

Abstract

We propose a stochastic framework based on sensitivity analysist (SA) methods to quantify the key-input parameters influencing the Young's modulus of polymer (epoxy) clay nanocomposites (PCNs). The input parameters include the clay volume fraction, clay aspect ratio, clay curvature, clay stiffness and epoxy stiffness. All stochastic methods predict that the key parameters for the Young's modulus are the epoxy stiffness followed by the clay volume fraction. On the other hand, the clay aspect ratio, clay curvature and the clay stiffness have an insignificant effect on the Young's modulus of PCNs. Besides the results on the sensitivity of the input parameters, this work includes a comparative study of a series of stochastic methods to predict mechanical properties of PCNs with respect to their performance.

Original languageEnglish
Pages (from-to)520-535
Number of pages16
JournalComputational Materials Science
Volume96
Issue numberPB
DOIs
Publication statusPublished - 2015 Jan 1
Externally publishedYes

Fingerprint

Epoxy
Nanocomposites
clays
Mechanical Properties
nanocomposites
Clay
mechanical properties
Stiffness
Young's Modulus
Mechanical properties
Prediction
predictions
Stochastic Methods
Volume Fraction
Aspect Ratio
stiffness
Curvature
Predict
modulus of elasticity
Elastic moduli

Cite this

A unified framework for stochastic predictions of mechanical properties of polymeric nanocomposites. / Vu-Bac, N.; Silani, M.; Lahmer, T.; Zhuang, X.; Rabczuk, Timon.

In: Computational Materials Science, Vol. 96, No. PB, 01.01.2015, p. 520-535.

Research output: Contribution to journalArticle

Vu-Bac, N. ; Silani, M. ; Lahmer, T. ; Zhuang, X. ; Rabczuk, Timon. / A unified framework for stochastic predictions of mechanical properties of polymeric nanocomposites. In: Computational Materials Science. 2015 ; Vol. 96, No. PB. pp. 520-535.
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