Generating Woven Textile Models with Induced Fiber Entanglement for Achieving Realistic Tow Fiber Volume Fraction

Abstract

Meso-scale modeling can be an effective way to predict textile-reinforced composite performance when the geometry of the textile is known. Digital element fiber models can be used to obtain the textile reinforcement by allowing for the simulation of the manufacturing process of the textile to be replicated. While helpful, these textiles frequently become over compacted to a smaller than desired thickness due to the lower resistance an ideal unentangled fiber bundle provides to compaction. A bundle that contains entangled fibers as found in manufactured textiles provides greater resistance to compaction. A novel entanglement generation procedure was created to obtain textile geometry with higher resistance to compaction. To introduce fiber entanglement into a tow, select fibers are swapped with each other in the tow at a cross-section. This allows entanglement to be introduced after the basic textile structure is already made and prevents individual fibers from leaving the tow and getting entangled into neighboring tows. By combining artificial fiber entanglement with manufacturing process simulation, a method was developed to create fiber bundle models using entanglement to control the compaction behavior. This fiber entanglement process was controlled by three parameters, which dictate how many, how often, and how far away from each other fibers are swapped. The method was applied to a woven textile model, where it was found that increasing the amount of entanglement within the tows increased the compacted thickness of the textile under the same load. This method for artificial fiber entanglement and manufacturing process simulation shows the potential to control the compaction response of a textile by controlling the amount of entanglement introduced to the textile.