Abstract

For resin transfer molding in a woven fabric, this study developed a novel framework for optimization by combining a multi-objective genetic algorithm and mold-filling simulation including a void-formation model, which gives us not only the spatial distribution of the mesoscopic and microscopic voids but also the correlations between molding characteristics such as fill time, total amount of void, weld line, and wasted resin. Our experiment observation of one-point radial injection successfully captured the anisotropic distribution of mesoscopic voids, which qualitatively validates the simulated result. As a result of multi-objective optimization for an arrangement of two injection positions, we found the trade-off relations of weld line with the other characteristics, which also have positive correlation with each other. Furthermore, visualization techniques such as self-organizing maps and parallel coordinate maps extracted the design rule of the arrangement. For example, a diagonal gate arrangement with an appropriate distance is required for reducing the both total amount of voids, fill time, and wasted resin; however, the total area of the weld line becomes relatively large. Our framework and the knowledge obtained from this study will enable us to determine the appropriate mold design for resin transfer molding.

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