3D in situ observations of the compressibility and pore transport in Sheet Moulding Compounds during the early stages of compression moulding

Mechanical characterization of anisotropy on a carbon fiber sheet molding compound composite under quasi-static and fatigue loading

“…4,5 Thanks to the vinyl-ester thermoset resin; those advanced sheet molding compounds (A-SMCs) allow a higher content of reinforcement. Classical SMC 3,[6][7][8] have a fiber content below 35% weight when the developed vinyl-ester resin allows a reinforcement weight content up to 60% weight. Such improvement offers new perspectives in terms of applications, especially in the automotive industry.…”

Review of the Numerical Modeling of Compression Molding of Sheet Molding Compound

“…Larger amounts of voids may influence the pressure build-up, the viscosity distribution and the flow of the compound. The transport of voids during compression was studied by Sentis [34] using 3D synchrotron X-ray for compounds with weight fiber contents of 29% and 50%. It was shown that the initial volume void contents of 1.5%-5.5% and 23% for the respective cases were reduced to nearly zero during the compression.…”

“…A rheological aspect which has more recently been suggested by experiments by Ferré-Sentis et al [34,41] is that considering the SMC charge as incompressible might be an unrealistic assumption. This is likely connected to air both inside the sheets and between them.…”

Analysis of Impregnation Mechanism of Weft-Knitted Commingled Yarn Composites by Staged Consolidation and Laboratory X-Ray Computed Tomography

“…Higher energy X-ray beams, such as those in synchrotron facilities are more adapted to the in-situ µCT imaging which is required for the in-situ characterization at high time resolution and at resolutions lower than one micrometer. In-situ µCT analyses are more suitable to monitor damage (Böhm et al, 2015;Rolland et al, 2017;Yang et al, 2017;Jespersen et al, 2018;Wang et al, 2018), to characterize time dependent phenomena taking place during the process, such as the impregnation of reinforcement (Vilà et al, 2015;Sisodia et al, 2016;Larson and Zok, 2018) and the fiber bed compression (Latil et al, 2011;Ferré Sentis et al, 2017). In case the readers need more information about application of µCT characterization of polymer matrix composites, some reviews are already available in the literature (Maire and Withers, 2014;Duchene et al, 2018;Garcea et al, 2018).…”

“…Berg et al provided an overview of potential segmentation methods including absolute thresholding, region growing, contour detection and automatic clustering method involving machine learning (Berg et al, 2018). For composite materials, segmentation techniques are required to separate the constituents of the composite for numerous reasons, such as monitoring the geometric changes of the cross-sectional shapes of reinforcement yarns (Liu et al, 2017b), monitoring the compressibility of a fiber bed (Ferré Sentis et al, 2017) and inspecting the impregnation quality (Madra et al, 2014;Patou et al, 2019). Nevertheless, the aforementioned µCT flaws prohibit the existence of a standard segmentation method and thus, may limit the reliability of quantitative analyses (Berg et al, 2018).…”