Development and Validation of a Liquid Composite Molding Model

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In composite manufacturing, Vacuum Assisted Resin Transfer Molding (VARTM) is becoming increasingly important as a cost effective manufacturing method of structural composites. In this process the dry preform (reinforcement) is placed on a rigid tool and covered by a flexible film to form an airtight vacuum bag. Liquid resin is drawn under vacuum through the preform inside the vacuum bag. Modeling of this process relies on a good understanding of closely coupled phenomena. The resin flow depends on the preform permeability, which in turn depends on the local fluid pressure and the preform compaction behavior. VARTM models for predicting the flow rate in this process do exist, however, they are not able to properly predict the flow for all classes of reinforcement material. In this thesis, the continuity equation used in VARTM models is reexamined and a modified form proposed. In addition, the compaction behavior of the preform in both saturated and dry states is studied in detail and new models are proposed for the compaction behavior. To assess the validity of the proposed models, the shadow moiré method was adapted and used to perform full field measurement of the preform thickness during infusion, in addition to the usual measurements of flow front position. A new method was developed and evaluated for the analysis of the moiré data related to the VARTM process, however, the method has wider applicability to other full field thickness measurements. The use of this measurement method demonstrated that although the new compaction models work well in the characterization tests, they do not properly describe all the preform features required for modeling the process. In particular the effect of varying saturation on the preform's behavior requires additional study. The flow models developed did, however, improve the prediction of the flow rate for the more compliant preform material tested, and the experimental techniques have shown where additional test methods will be required to further improve the models

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  • 05/30/2018
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