Qi Wei, Chiu Tzu-Heng, Kao Yi-Kai, Yao Yuan, Chen Yu-Ho, Yang Hsun, Wang Chen-Chieh, Hsu Chia-Hsiang, Chang Rong-Yeu
School of Information and Electrical Engineering, Zhejiang University City College, Hangzhou 310015, China.
Department of Chemical Engineering, National Tsing Hua University, Hsinchu City 30013, Taiwan.
Polymers (Basel). 2022 Jun 29;14(13):2652. doi: 10.3390/polym14132652.
To meet the expectation of the industry, resin transfer molding (RTM) has become one of the most promising polymer processing methods to manufacture fiber-reinforced plastics (FRPs) with light weight, high strength, and multifunctional features. The permeability and porosity of fiber reinforcements are two of the primary properties that control the flow of resin in fibers and are critical to numerical simulations of RTM. In the past, various permeability measurement methods have been developed in the literature. However, limitations still exist. Furthermore, porosity is often measured independently of permeability. As a result, the two measurements do not necessarily relate to the same entity, which may increase the time and labor costs associated with experiments and affect result interpretation. In this work, a measurement system was developed by fusing the signals from capacitive sensing and flow visualization, based on which a novel algorithm was developed. Without complicated sensor design or expensive instrumentation, both in-plane permeability and porosity can be simultaneously estimated. The feasibility of the proposed method was illustrated by experiments and verified with numerical simulations.
为满足行业期望，树脂传递模塑（RTM）已成为制造具有轻质、高强度和多功能特性的纤维增强塑料（FRP）最具前景的聚合物加工方法之一。纤维增强材料的渗透率和孔隙率是控制树脂在纤维中流动的两个主要特性，对RTM的数值模拟至关重要。过去，文献中已开发出各种渗透率测量方法。然而，仍然存在局限性。此外，孔隙率通常独立于渗透率进行测量。因此，这两种测量不一定与同一实体相关，这可能会增加与实验相关的时间和劳动力成本，并影响结果解释。在这项工作中，通过融合电容传感和流动可视化的信号开发了一种测量系统，并在此基础上开发了一种新颖的算法。无需复杂的传感器设计或昂贵的仪器，即可同时估计面内渗透率和孔隙率。通过实验说明了该方法的可行性，并通过数值模拟进行了验证。
