Sebastian Rodriguez, Eric Monteiro, Nazih Mechbal, Marc Rebillat, Francisco Chinesta
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引用次数: 0
Abstract
To ensure correct filling in the resin transfer molding (RTM) process, adequate numerical models have to be developed in order to correctly capture its physics, so that this model can be considered for process optimization. However, the complexity of the phenomenon often makes it impossible for numerical models to accurately predict its behavior, limiting its usage. To overcome this limitation, numerical models are enriched with measured data to ensure their correct predictability. Nevertheless, the data used is often limited due to practical constraints, such as a limited number of sensors or the high costs of experimental campaigns. In this context, the present paper demonstrates the implementation of a numerical model enriched with data, called Hybrid Twin applied to the RTM process when few sensors are considered in the mold to be injected. The performances of the developed hybrid twin are tested in a virtual test for the injection of a 2D mold, where the hybrid twin constructed using a simplified numerical model allows to accurately predict a complex model’s resin flow-front over its entire time history.
期刊介绍:
The Journal publishes and disseminates original research in the field of material forming. The research should constitute major achievements in the understanding, modeling or simulation of material forming processes. In this respect ‘forming’ implies a deliberate deformation of material.
The journal establishes a platform of communication between engineers and scientists, covering all forming processes, including sheet forming, bulk forming, powder forming, forming in near-melt conditions (injection moulding, thixoforming, film blowing etc.), micro-forming, hydro-forming, thermo-forming, incremental forming etc. Other manufacturing technologies like machining and cutting can be included if the focus of the work is on plastic deformations.
All materials (metals, ceramics, polymers, composites, glass, wood, fibre reinforced materials, materials in food processing, biomaterials, nano-materials, shape memory alloys etc.) and approaches (micro-macro modelling, thermo-mechanical modelling, numerical simulation including new and advanced numerical strategies, experimental analysis, inverse analysis, model identification, optimization, design and control of forming tools and machines, wear and friction, mechanical behavior and formability of materials etc.) are concerned.