Random Fiber Array Generation Considering Actual Noncircular Fibers with a Particle-Shape Library

Abstract

In this work, we generated a set of random representative volume elements (RVEs) of unidirectional composites considering actual noncircular cross-sections and positions of fibers with the aid of a shape-library approach. The cross-section of the noncircular carbon fiber was extracted from the M55J/M18 composite using image processing and a signed-distance-based mesh trimming scheme, and they were stored in a particle-shape library. The obtained noncircular fibers randomly chosen from the particle-shape library were applied to random fiber array generation algorithms to generate RVEs of various fiber volume fractions. To check the randomness of the proposed RVEs, we calculated spatial and physical metrics, and concluded that the proposed method is sufficiently random. Furthermore, to compare the effective elastic properties and the maximum von Mises stress in the matrix, it was applied to composite materials with different relative ratios of elastic moduli of M55J/M18 and T300/PR319. In the case of T300/PR319 having a high RRT (relative ratio of the transverse elastic moduli), simulation results were deviated up to about 5% in the effective elastic properties and 13% in the maximum von Mises stress in the matrix according to the fiber shapes.

Prediction of the transverse elastic modulus of the unidirectional composites by an artificial neural network with fiber positions and volume fraction

“…To confirm the randomness of the RVEs in this work, it was checked by computing spatial metrics, such as the nearest neighbor orientation, Ripley's K function, and pair distribution function [7,10]. The three statistical spatial metrics for the generated RVEs were very close to the complete spatial random pattern, similar to the results reported in the literature [7].…”

“…To generate RVEs with V f of 40%, 50%, and 60%, the RSE algorithm was adopted [7,10]. The cross-section of the fiber is assumed to be circular with a constant radius, even if the radii of the actual fiber show some deviation.…”

“…In order to overcome this hurdle, we changed the fiber radii to 0.37, 0.41 and 0.45 µm for V f of 40%, 50% and 60% with the same number of fibers as 93. In our work, the number of fibers was set to 93 and the size of RVEs was set to 10 µm, which is sufficient because 30 fibers with V f = 50% in the RVE have been proved to be sufficient to represent the microstructure of UD composites [10]. The Abaqus Python script [22] was used to generate the corresponding FE models of RVEs composed of the fiber and matrix.…”

“…To overcome such technical hurdles, theoretical and numerical approaches to the prediction of material properties have been actively taken [3][4][5][6][7][8][9][10] with theoretical or empirical formulae or finite-element (FE) analysis. For the prediction of the effective properties of a material using FE analysis, a representative volume element (RVE) similar to the microstructure of the actual composite material is used.…”