We propose a methodology to monitor the progressive saturation of a non-translucent unidirectional carbon fabric stack through its thickness by means of X-ray radiography and extract the dynamic saturation curves using image analysis. Four constant flow rate injections with increasing flow speed were carried out. These were simulated by a numerical two-phase flow model for both capillary and viscous leading flow conditions. The hydraulic functions describing pressure and relative permeability versus saturation were determined by fitting the saturation curves using a heuristic optimization routine. As the fluid velocity increases and the flow regime at the flow front shifts from capillary to hydrodynamically driven, the resulting capillary pressure curves for a given saturation level are shifted to higher values, from negative to positive. These as well as the capillary pressure calculated from the pressure drop within the unsaturated region of the fabric correlate well with a corresponding change in the averaged dynamic contact angle.

@en

We seek to address how air entrapment mechanisms during infiltration are influenced by the wetting characteristics of the fluid and the pore network formed by the reinforcement. To this end, we evaluated the behavior of two model fluids with different surface tensions, infiltrating three carbon fiber reinforcements, by means of X-ray radiography. We also assessed initial (dry) and final (wetted) states for each experiment by performing X-ray CT scans. We found that the fluid characteristics strongly affect the flow front patterns and pore filling events for a given fabric architecture. Two main promoters of snap-off events are involved in capillary dominated flows: a very wetting system leading to corner flows and the fabric bundles oriented perpendicular to the flow acting as obstacles, specifically in fabric architectures prone to variations in nesting. Finally, we evaluated the applicability of a pore network model to further link preform architecture and void formation.

@en

Capillarity plays a crucial role in many natural and engineered systems, ranging from nutrient delivery in plants to functional textiles for wear comfort or thermal heat pipes for heat dissipation. Unlike nano- or microfluidic systems with well-defined pore network geometries and well-understood capillary flow, fiber textiles or preforms used in composite structures exhibit highly anisotropic pore networks that span from micron scale pores between fibers to millimeter scale pores between fiber yarns that are woven or stitched into a textile preform. Owing to the nature of the composite manufacturing processes, capillary action taking place in the complex network is usually coupled with hydrodynamics as well as the (chemo) rheology of the polymer matrices; these phenomena are known to play a crucial role in producing high quality composites. Despite its importance, the role of capillary effects in composite processing largely remained overlooked. Their magnitude is indeed rather low as compared to hydrodynamic effects, and it is difficult to characterize them due to a lack of adequate monitoring techniques to capture the time and spatial scale on which the capillary effects take place. There is a renewed interest in this topic, due to a combination of increasing demand for high performance composites and recent advances in experimental techniques as well as numerical modeling methods. The present review covers the developments in the identification, measurement and exploitation of capillary effects in composite manufacturing. A special focus is placed on Liquid Composite Molding processes, where a dry stack is impregnated with a low viscosity thermoset resin mainly via in-plane flow, thus exacerbating the capillary effects within the anisotropic pore network of the reinforcements. Experimental techniques to investigate the capillary effects and their evolution from post-mortem analyses to in-situ/rapid techniques compatible with both translucent and non-translucent reinforcements are reviewed. Approaches to control and enhance the capillary effects for improving composite quality are then introduced. This is complemented by a survey of numerical techniques to incorporate capillary effects in process simulation, material characterization and by the remaining challenges in the study of capillary effects in composite manufacturing.

@en

Visualization of resin flow progression through fibrous preforms is often sought to elucidate flow patterns and validate models for filling prediction for liquid composite molding processes. Here, conventional X-ray radiography is compared to X-ray phase contrast technique to image in-situ constant flow rate impregnation of a non-translucent unidirectional carbon fabric. X-ray attenuation of the fluid phase was increased by using a ZnI2-based contrasting agent, leading to enough contrast between the liquid and the low density fibers. We proved the suitability of conventional X-ray transmission to visualize fluid paths by elucidating different flow patterns, spanning from capillary to viscous regimes and a macro-void entrapment phenomenon @en

Direct visualization is often sought to elucidate flow patterns and validate models to predict the filling kinetics during processes whereby a liquid resin infiltrates a textile porous preform. Here, X-ray phase contrast interferometry is evaluated to image in-operando constant flow rate impregnation experiments of a model fluid into glass, carbon and flax fabrics and a 3D printed structure. A methodology is presented to build the dynamic saturation curve based on image analysis of the dark field images, in which the pixel intensity values are transformed into saturation level versus position and time. The results prove the suitability of this technique to observe the progressive saturation averaged through the thickness of translucent and non-translucent preforms. The porosity network formed by the layers of fabric, the refractive properties of the material, the fabric geometry and its position relative to the X-ray setup are reported to be the main parameters affecting image contrast.

@en