Microstructural Quantification and Virtual Reconstruction of Polymer Matrix Composites

Shah, Sagar; Schey, Mathew; Hu, Jie; Liu, Fuqiang; Beke, Tibor; Stapleton, Scott E.; Maiarù, Marianna

doi:10.2514/6.2020-1858

Cited by 2 publications

(3 citation statements)

References 6 publications

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“…Comprehensive statistical analysis procedures have been established using different statistical descriptors, such as nearest neighbor distances and orientations, local fiber volume fraction distribution using Voronoi tessellation, cluster analysis with Delaunay triangulation, second-order intensity function, and fiber pair distribution function to establish RVEs geometrical equivalence [7,9,48,49,[51][52][53]71,74]. In this study, statistical analysis is used to provide direct correlation between the mechanical properties and the RVE fiber packing, and to explain the standard deviation in the transverse strength as a function of the random packing.…”

Section: Discussionmentioning

confidence: 99%

“…An in-depth statistical analysis must be carried out on a larger sample set of RVEs with varying sizes for other mechanical loading conditions. Strategies for such analysis can be found in [7,9,48,49,[51][52][53]71,74].…”

Section: Discussionmentioning

confidence: 99%

“…During this process, cure-induced volumetric shrinkage of the matrix, mismatch in the thermo-mechanical properties between the fibers and the matrix, and thermal gradients due to exothermic reactions lead to significant residual stress generation and, at times, damage accumulation [ 5 ]. Random and off-axial fiber architecture, introduced during manufacturing, alters the composite stress state which may further contribute to the onset and evolution of damage [ 6 , 7 , 8 , 9 , 10 ]. Internal defects such as voids and microcracks may also occur [ 11 , 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

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Effect of Manufacturing on the Transverse Response of Polymer Matrix Composites

Shah

Maiarù

2021

Polymers

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The effect of residual stress build-up on the transverse properties of thermoset composites is studied through direct and inverse process modeling approaches. Progressive damage analysis is implemented to characterize composite stiffness and strength of cured composites microstructures. A size effect study is proposed to define the appropriate dimensions of Representative Volume Elements (RVEs). A comparison between periodic (PBCs) and flat (FBCs) boundary conditions during curing is performed on converged RVEs to establish computationally efficient methodologies. Transverse properties are analyzed as a function of the fiber packing through the nearest fiber distance statistical descriptor. A reasonable mechanical equivalence is achieved for RVEs consisting of 40 fibers. It has been found that process-induced residual stresses and fiber packing significantly contribute to the scatter in composites transverse strength. Variation of ±5% in average strength and 18% in standard deviation are observed with respect to ideally cured RVEs that neglect residual stresses. It is established that process modeling is needed to optimize the residual stress state and improve composite performance.

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