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Theoretical Framework and Experimental Procedure for Modelling Mesoscopic Volume Fraction Stochastic Fluctuations in Fiber Reinforced Composites by Johann Guilleminot; Christian Soize; Djimedo Kondo; Christophe Binetruy is a Engineering article available to read on EtoBox.
What is Theoretical Framework and Experimental Procedure for Modelling Mesoscopic Volume Fraction Stochastic Fluctuations in Fiber Reinforced Composites about?
Many engineering materials exhibit fluctuations and uncertainties on their macroscopic mechanical properties. This randomness results from random fluctuations observed at a lower scale, especially at the meso-scale where microstructural uncertainties generally occur. In the present paper, we first propose a complete theoretical stochastic framework (that is, a relevant probabilistic model as well as a non-intrusive stochastic solver) in which the volume fraction at the microscale is modelled as a random field whose statistical reduction is performed using a Karhunen-Loeve expansion. Then, an experimental procedure dedicated to the identification of the parameters involved in the probabilistic model is presented and relies on a non-destructive ultrasonic method. The combination of the experimental results with a micromechanical analysis provides realizations of the volume fraction random field. In particular, it is shown that the volume fraction can be modelled by a homogeneous random field whose spatial correlation lengths are determined and may provide conditions on the size of the meso-volumes to be considered.
Who reads Theoretical Framework and Experimental Procedure for Modelling Mesoscopic Volume Fraction Stochastic Fluctuations in Fiber Reinforced Composites?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Johann Guilleminot; Christian Soize; Djimedo Kondo; Christophe Binetruy
- Publisher
- Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0020-7683)
- Published
- 2008
- Language
- EN
- Field
- Engineering (Physical Sciences)
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