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Flow simulation of particle-filled resins in LCM processes

News International-French

12 Apr 2011

When employing Liquid Composite Moulding (LCM) to mould composite parts, using particle- filled resins, certain problems may arise, such as the increased viscosity of the resin or the filtration of the particles. When the particle-filled resin is flowing, the fibrous reinforcement may act as a filter and so give rise to manufacturing defects. Injection process simulation may help to prevent such defects. The proposed simulation is based on the coupling of flow and filtration models.

(Published on March - April 2008 – JEC Magazine #39)





The manufacturers of polymer-matrix composite parts are increasingly using particle fillers in order to improve the performance of materials, to functionalize them or, quite simply, to substitute some of the resin for a less costly material. This is the case, for example, in the field of public transport, where flame retardants are added to the organic resin to meet fire safety requirements. The use of nanofillers (carbon nanotube type) is another example of the addition of particles to the resin. What is more, composite manufacturing techniques are evolving and LCM (Liquid Composite Moulding) is taking over from more traditional techniques such as hand lay-up.


When the filled resin is processed in an LCM process, the problem of the flow of the resin/filler mix through the fibrous reinforcement arises.



Figure 1 illustrates the various possible scenarios. If the size of the particles is greater than a certain critical threshold (which depends on the architecture of the reinforcement and its initial compression state within the mould), the particles will not be able to penetrate into the reinforcement and are blocked at the mould gate, making injection impossible. If, on the other hand, the size of the particles is below this first critical diameter, the resin/filler mix is able to flow into the reinforcement. If these particles are particularly small (below a second critical diameter), they will be able to flow with ease into the reinforcement. However, the smaller the fillers the more the viscosity of the mix increases. Considering the often high filler content (20- 40% by volume), the viscosity of the mix can then quite easily exceed the acceptable viscosity limits for the manufacturing process concerned. The last scenario corresponds to fillers that are small enough to penetrate into the reinforcement but are as large as possible for the viscosity of the mix to remain acceptable. In this case, the particles may be filtered by the reinforcement during flow, leading to their heterogeneous distribution in the part at the end of the injection process.


Filtration model

To control this phenomenon, a study has been carried out in order to understand, characterize and model the filtration of fillers by fibres during the manufacture of composite parts with particle-filled resin.



The resin-particles-fibres system can be considered as the overlaying of two distinct sub-assemblies (Figure 2): the filter (stationary) and the suspension (in motion with respect to the filter). The initial permeability of the filter (K) is equal to the permeability of the fibrous preform (KF). Similarly, the initial porosity of the filter is identical to that of the preform, ε0. Furthermore, the suspension (resin/filler mix) is characterized by its initial concentration (C0) and its initial viscosity (η0), the latter in turn depending on the nature of the fluid and of the particles and on C0. During flow, the particles are trapped in the preform. The retention that takes place is then considered as the transfer of some of the particles from the suspension to the filter. These particles, which were in motion with the suspension, then become stationary. In its intermediate state, the filter sub-assembly now consists of the fibres of the preform and the trapped particles. Since the volume of the filter is increased by the volume of the retained particles, its porosity is reduced along with its permeability (K). Similarly, the suspension “loses” some of its particles. In the intermediate state, the suspension is therefore characterized by a concentration (C) that is different from the initial concentration (C0) and, consequently, by a viscosity (η) that is also different from η0 . Thanks to the development of a system of equations based on the conservation of mass and retention kinetics, a finite element analysis allows the total quantity of filler particles present at each point of the part and at each instant to be modelled.


1-D injection simulation

The simulation of particle-filled resin flow through a fibrous preform requires the simultaneous resolution of two interlinked problems: the flow problem (modelled with the Darcy equation) and the filtration problem (Figure 3). The Darcy equation relates the injection pressure to the fluid velocity, the fluid viscosity and the permeability of the fibrous reinforcements. On the basis of the system’s input data (material properties, injection parameters), the simulation is run using an iteration loop carrying out a series of calculations for each element of the mesh. The total injection time and the filler profile in the finished part can thus be estimated.


The study is complemented by the development of an experimental methodology enabling the filler concentration in the part to be measured and the model input parameters to be identified.



Conclusions and outlook

The study presented in this article offers real advances in the understanding of the physical phenomena involved in the flow of a particle-filled resin through a fibrous reinforcement. This has led to the development of an injection simulation tool for composite parts, combining analysis and measurements, which for the time being is limited to unidirectional flows. This study has also opened up various paths for development, offering a number of possibilities for process enhancement. In particular, from an industrial perspective, this tool can be used for:

  • selecting fillers (particle size)
  • selecting and/or optimizing the architecture of the fibrous reinforcement
  • defining the best injection strategy.