Improving Computational Efficiency in LCM by Using Computational Geometry and Model Reduction Techniques

Abstract:

LCM simulation is computationally expensive because it needs an accurate solution of flowequations during the mold filling process. When simulating large computing times are not compatiblewith standard optimization techniques (for example for locating optimally the injection nozzles)or with process control that in general requires fast decision-makings. In this work, inspired by theconcept of medial axis, we propose a numerical technique that computes numerically approximatedistance fields by invoking computational geometry concepts that can be used for the optimal locationof injection nozzles in infusion processes. On the other hand we also analyze the possibilities thatmodel order reduction offers to fast and accurate solutions of flow models in mold filling processes.

• Periodical: Key Engineering Materials (Volumes 611-612)
• Pages: 339-343
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.611-612.339
• Online since: May 2014
• Authors: Elías Cueto*, Chady Ghnatios, Francisco Chinesta, Nicolas Montes, Fernando Sanchez, Antonio Falco
• Keywords: Computational Geometry, Liquid Composite Molding, Model Order Reduction, Resin Transfer Molding

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