Three-dimensional reconstruction of resin flow using capacitance sensor data assimilation during a liquid composite molding process: A numerical study |
| |
| Affiliation: | 1. Department of Mechanical Sciences and Engineering, Tokyo Institute of Technology, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552, Japan;2. Department of Mechanical Engineering, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan;1. Department of Mechanical Engineering and Center for Composite Materials, University of Delaware, Newark, DE 19716, USA;2. School of Mechanical and Aerospace Engineering, Research Center for Aerospace Parts Technology, Gyeongsang National University, Jinju, Republic of Korea;1. School of Applied Sciences, Manufacturing and Materials Department, Composites Centre, Cranfield University, Bedford MK43 0AL, UK;2. Faculty of Engineering, Division of Materials, Mechanics & Structures, University of Nottingham, University Park, Nottingham NG7 2RD, UK;1. Department of Aerospace Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates;2. Centre for Future Materials, University of Southern Queensland, Toowoomba, Queensland, 4350 Australia;3. Cambridge Graphene Centre, Electrical Engineering Division, The University of Cambridge, 9 JJ Thomson Avenue, Cambridge, UK;1. Laboratory of Composite Materials and Adaptive Structures, ETH Zürich, Leonhardstrasse 27, Zurich 8092, Switzerland;2. Centre on Composites of High Performance, École Polytechnique de Montréal, P.O. Box 6079, Station “Centre-Ville”, Montreal, Canada |
| |
| Abstract: | Liquid composite molding (LCM) is a method to manufacture fiber-reinforced composites, where dry fabric reinforcement is impregnated with a resin in a molding apparatus. However, the inherent process variability changes resin flow patterns during mold filling, which in turn may cause void formation. We propose a method to reconstruct three-dimensional resin flow in LCM, without embedding sensors into the composite structure. Capacitance measured from pairs of electrodes on molding tools and the stochastic simulation of resin flow during an LCM process are integrated by a sequential data assimilation method based on the ensemble Kalman filter; then, three-dimensional resin flow and permeability distribution are estimated simultaneously. The applicability of this method is investigated by numerical experiments, characterized by different spatial distributions of permeability. We confirmed that changes in resin flow caused by spatial permeability variations could be captured and the spatial distribution of permeability could be estimated by the proposed method. |
| |
| Keywords: | B. Electrical properties C. Computational modeling D. Process monitoring E. Resin flow |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
