.png){kind=icon}
.png){kind=icon}
Return
Efficient quantification of composite spatial variability: A multiscale framework that captures intercorrelation
.png){kind=icon}
OA
AI
DOI：10.1016/j.compstruct.2023.117462.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Composite structures suffer from material imperfections. Non-deterministic models at the micro- and mesoscale propagate this spatial variability. However, they become impractical when the structure size increases. This paper proposes a numerically efficient multiscale methodology that links structural behaviour with the spatial variability of material imperfections on smaller scales. Fibre strength variability is accounted for through a fibre break model. A mesoscale model considers fibre volume fraction and fibre misalignment variability using random fields. Measurements provide probabilistic data for these imperfections. Subsequent homogenisation results in intercorrelated material properties on the structural macroscale that are modelled effectively with vine copulas. The methodology is verified by predicting the failure load of a coupon model. Predictions are very similar to those obtained by directly modelling spatial variability on the structural scale.
Keywords:
Multiscale
Reliability analysis
Finite element analysis (FEA)
Spatial variability
Vine copula modelling
Unidirectional (UD)
Carbon-fibre-reinforced polymers (CFRP)
Strength prediction
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.1
Papers:
1.8W
Citations:
8.0W