Chen Li

Doctorant du groupe Matériaux et Structures Composites (MSC)
IUT, 1 rue Lautréamont
65016 Tarbes

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Activités de recherche

Simulation numérique de la fabrication de composites à renfort fibreux 3D par le procédé d'infusion

Doctorant: Chen LI1

Encadrants: Xiaojing GONG2, Arthur CANTAREL3


2, 3

Résumé — La fabrication de pièces composites structurales aéronautiques nécessite l’utilisation de renforts complexes et notamment des renforts tridimensionnels. Le procédé d’infusion permettrait la fabrication de ces pièces tout en maitrisant leur qualité et les coûts. L’objectif de la thèse est de développer un modèle, à différentes échelles, de l’écoulement de résine à traverse le réseau fibreux du renfort et de proposer une simulation numérique plus fine du procédé d’infusion. L'influence des structures de renforts 2D et 3D, sera ainsi étudié aux différentes échelles: micro (intra-mèches), méso (inter-mèches) et macro (renfort, pièce).

Abstract — The manufacture of composite aeronautical structural parts requires the use of more complex reinforcements, especially the 3D reinforcements. Resin infusion is the key process of Liquid Composites Molding (LCM) which will determine the quality and cost of the parts. The target of this thesis is to develop models at different scales of fibrous network of the reinforcement and to propose a finer numerical simulation of the infusion process. The influence of the 2D and 3D reinforcement structures on the infusion process will be studied at the different scales: micro (intra-tow), meso (inter-tows) and macro (reinforcement, part).

1. Introduction

LCM is a promising method for composites manufacture with various advantages. It has four main steps including preform set, resin infusion, curing and disclosing process. Among all these processes, infusion is the most important step which will determine the final quality of the part. Thus, numerical simulation of the resin infusion is meaningful [1]. The work performed and the results obtained will be presented in the second part, which mainly focus on the permeability estimation on random fiber models [2] and dual scales models and then the future work is listed in the perspective.

2. Permeability estimation intra tow in the section (2D)

For porous media, permeability tensor K is the most significant parameter to describe the property of the reinforcement for infusion processing. As an intrinsic property of the porous material, K can be calculated by Darcy’s law based on the velocity field obtained by solving Navier-Stokes equation and continuity equation together. Hence, the Stokes equation can be used for free flow with the consideration of incompressible fluid and the inertial term can be neglected in micro, meso and macro scales.

The random position and size of the fiber producing codes are developed to set up realistic geometrical models. Numerical simulation has been realized based on these models.

In fact, we have studied the influences of several parameters on the flow of the resin during infusion. It includes 3 micro-structural parameters: δmin, L, Δr and a macro parameter: ε. Here δmin is defined as the minimum distance between two neighbor fibers among all the fibers; ∆r is the range of the fiber radius, L is the length of the square domain and ε is the porosity. We have also used Morris sensitivity method to analyze the influences of these parameters. Porosity ε has the most obvious influence on permeability while L has a significant effect on average velocity compared with other parameters. These influences observed in a Representative Elementary Volume (REV) can be generated to whole structure.

3. Permeability estimation of dual scales in 3 directions

In order to estimate the permeability in 3 directions using dual scales: intra and inter tows, the model with random position codes have been developed in this work. The idea of this model is to generate the real position of the fibers, the determination of the permeability of 3 directions can be achieved by applying the calculation method mentioned above for intra as well as inter tow. The results from this model seem very promising, because the permeability obtained in the transverse section (Fig. 1) correlate well with the results published in the reference [3]. Moreover, the permeability in the longitudinal direction obtained from this model is much closed to that calculated by traditional method. Actually, to our knowledge no any other works has been realized in the literature on the determination of 3D permeability at dual scales.

4. Perspective

(1) Adaptable 3D geometrical models of braided and woven fiber will be studied to set up for numerical simulation.

(2) The two phases coupling free flow and porous flow will be studied to detect the infusion character on both of 2D and 3D models. Parameters of structure which may influence the infusion process will be defined. Their interactive influences on the infusion will also be explored.

(3) A final method will be developed for flow front prediction at macro scale  with various local permeability on different position of the part(Fig. 2 for 3D simple part and Fig. 3 for 3D car bonnet).

Figure. 2. Macro porous flow at part level (3D simple part)

Figure. 3. Macro infusion process at part level (3D car bonnet)


[1]R. Gantois, A. Cantarel, B. Cosson, G. Dusserre, J.-N. Félices, F. Schmidt, BEM-based models to simulate the resin flow at macroscale and microscale in LCM processes, Polymer Composites, 34 (8), 2013

[2]F. Zhang, B. Cosson, S. Comas-Cardona, C. Binetruy, Efficient stochastic simulation approach for RTM process with random fibrous permeability. Composites Science and Technology, 71, 2011.

[3]W.R. Hwang, S.G. Advani. Numerical simulations of Stokes–Brinkman equations for permeability prediction of dual scale fibrous porous media. Physics of Fluids, 22 (11), 2010

Production scientifique

1 contributions

Communication avec actes dans un congrès international ou national

[ACT1]C. Li, A. Cantarel, X. Gong and D. Liang. Numerical Simulation of Infusion at Microscale Permeability Calculation. Proceedings of 21th International Conference on Composite Materials 2017 (ICCM-21) p.11 pages 2017

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