Laminate thickness and resin pressure evolution during axisymmetric liquid composite moulding with flexible tooling

Abstract

This paper presents experimental observations from the filling and post-filling stages of 1D axisymmetric Resin Infusion (VARTM) and RTM Light. A series of experiments have been performed to investigate the influence of mould flexural stiffness and fill mode on fluid pressure, cavity thickness, filling stage time, and post-filling stage time. Observations are also made on the effect of those parameters on the repeatability of nominally identical experiments. This paper helps identify the circumstances where a RTM simulation would be sufficiently accurate for an RTM Light process, and consequently where a full flexible tooling simulation is necessary.

Introduction

Liquid Composite Moulding (LCM) describes a range of composites manufacturing processes where dry fibrous reinforcements are compacted in a mould before being impregnated with a liquid thermosetting matrix. Although all LCM processes use closed moulds, they vary in stiffness from fully rigid to fully flexible, with the heavy tooling of Resin Transfer Moulding (RTM) and Compression RTM (CRTM) processes at one end of the spectrum, and the thin films used in Resin Infusion (a.k.a. VARTM) at the other.

This paper focuses on LCM processes with flexible tooling, in particular RTM Light and Resin Infusion (Fig. 1). RTM Light differs from RTM by replacing one rigid mould half with a lighter, less rigid component, often manufactured from an isotropic glass fibre composite. Clamping is usually provided by application of vacuum to a region at the periphery of the mould cavity, and resin flow is driven by a cavity vacuum, an external injection system, or a combination of the two. RTM Light can provide significant reductions in tooling costs when compared to RTM, while at the same time allowing for higher injection pressures, higher volume fractions, and reduced cycle times when compared to flexible film processes. RTM Light has been employed in the manufacture of a variety of composites products, including boat hulls, bath tubs and automobile chassis components, where part size or volume of production makes rigid tool processes economically or technically unfeasible, and lack of process control or slow cycle times rule out Resin Infusion.

Numerical simulations of rigid tool LCM processes have been in development for over 20 years, with several academic and commercial packages now available [1], [2], [3], [4]. In the last decade a number of Resin Infusion simulations have also been developed [5], [6], [7], [8], [9], [10], along with numerous advances in the areas of computational efficiency, process control and optimisation, and part quality prediction [11], [12], [13], [14], [15], [16], [17]. These simulations are predominantly based on the Finite Element/Control Volume (FE/CV) method because of its efficiency and the ease with which it can model complex part geometries [1], [4], [6].

Extending a rigid tool simulation to flexible tooling processes such as Resin Infusion and RTM Light introduces a number of complexities attributable to the deforming mould and the resulting coupling between laminate thickness and the fluid pressure field in the saturated portion of the part. In particular, a simulation requires a constitutive model for the fibrous reinforcement to link applied stresses to deformations in the fluid–fibre system. Given that reinforcements typically exhibit non-linear load–deformation behaviour with rate and path dependencies [18], [19], [20], [21], [22], either a non-linear solution technique or some form of linearisation is necessary to solve the resulting problem within a FE/CV framework. Even under linear compaction behaviour, the coupling between deformation and flow creates a separate level of non-linearity [23]. Further complication arises in the form of a consolidation process that occurs subsequent to the saturation of the part (Fig. 1). At the completion of filling, mould deflection and part thickness vary spatially, even between regions with the same initial thickness. This post-filling stage, which is not present in RTM, involves the equilibration of fluid pressure and part thickness through bleeding of excess resin. Because the speed at which this process occurs dictates the final part thickness at gelation, it is an important phenomenon for parts where consistency or control of final part thickness is necessary.

Clearly, the interactions between fluid pressure, flow evolution, reinforcement deformation behaviour, and the structural response of the tooling present challenges to the modelling and simulation of flexible tool LCM processes. Despite this, there are still a number of benefits to be had from developing a good simulation of flexible tooling processes, including accurate predictions of filling and post-filling time, guidance over mould design, and laminate thickness predictions throughout the process. It must be recognised that the utility of a flexible tooling simulation extends well beyond fill time prediction, where the improvements over RTM based predictions may be small, by providing estimates of part thickness variation during and at the completion of processing. RTM simulations are unable to account for these effects, and as a consequence will not indicate when they can, and cannot, be discounted.

An important and necessary step in the simulation development process is performing experimental studies to guide model design and to validate simulation results. Such studies help identify the effects of mould compliance and the point at which they necessitate inclusion in a simulation. While a number of experimental studies on Resin Infusion have been presented in the literature [24], [25], [26], [27], there is a paucity of experimental work regarding RTM Light [28], [29]. This paper presents the results of a comprehensive experimental study on the Resin Infusion and RTM Light manufacturing processes, investigating the effect of mould stiffness and injection scheme on variables relevant to industrial process design and numerical simulation development, such as fill time, post-filling time, and cycle-to-cycle variability.