Void content reduction of composites with sensor-aided injection strategy in liquid composite molding process

Abstract

Abstract Void is one of the critical issues affecting the mechanical performance of fiber-reinforced polymer composites. Aiming at the composite parts formed by Liquid Composite Molding, this develops a sensor-aided injection strategy, including a real-time online monitoring module and a sensor-aided injection system, which realizes continuous detection of resin flow and the automatic injection flow rate adjustment to minimize void content. Flow front profile continuously recorded by the monitoring module in resin flow direction is reconstructed in real-time. It provides a digital representation of the saturation state of the fibrous preform, which is referred to Digital Process Twin (DPT) in present work. The local flow front velocity is then extracted from the DPT, thus the sensor-aided injection system can maintain the flow front velocity at a optimal level, regardless of the cross-sectional geometry. Experimental investigation confirms the representative of DPT to actual flow. Characterization of void content by micro-computed tomography shows that the proposed sensor-aided injection strategy not only effectively decreases the void content from 0.32%, 0.34%, and 0.79% to 0.18%, 0.18%, and 0.19%, but also significantly improves the part quality consistency. Furthermore, to the best knowledge of the authors, This work is the first to use micro CT to investigate the effect of velocity on void content from the mesoscopic and microscopic scales, although the topic has been widely investigated theoretically.