High Speed Reactive Resin Transfer Moulding (RTM) Process Simulation for Mass Production of Automotive Structural Parts 2015-01-0722
High speed Reactive Resin Transfer Moulding (RTM) is a promising process for the mass production of structural composite parts in the automotive industry. In this technology a low viscosity reactive thermosetting or thermoplastic polymer is injected in a fibrous preform made of glass or carbon fibres fabrics. Continuous fibre reinforcements contain two types of volume to be impregnated: microscopic voids inside the fibre tows and mesoscopic ones between the tows. Because of this double-scale structure, the saturation of fabrics with bi-disperse porous structure is not instantaneous during resin injection. The use of reactive resins aims to reduce both the resin viscosity and part cycle time by beginning curing during the filling stage. However the chemical reactions generate significant evolution in the temperature, composition and properties of the resin during injection, which can affect the filling and quality of the part. As reactive RTM is more sensitive to thermo-chemo-mechanical couplings than regular RTM, more accurate and more advanced simulation models are needed to address these new requirements in an industrial manner.
The aim of the project is twofold: i) model the thermo-chemo- mechanical coupling in the flow of reactive resin in double-scale fibrous reinforcement ii) implement this new model in ESI Group commercial software, PAM-RTM, in order to refine the filling simulation and to allow accurate definition of optimal processing windows for industrial components.
The quantities of interest: age, degree of cure, degree of crystallization, temperature and viscosity of the resin are transported and updated at each time step. Moreover, the flow is considered at the two length scales in fabrics. Flow front and quantities of interest are tracked at the macroscopic scale (observable flow in the part) and at the microscopic scale (microscopic flow within the fibre bundles). Thus potential hot spots or fully cured regions can be identified at these two scales, and the injection strategy can be adapted to ensure a complete filling of the part. Numerical simulations will be presented to illustrate the capabilities of the developed model.