Search Results (7)

In the field of liquid composite moulding (LCM) simulations, a long-standing assumption has dominated–the belief in constant resin viscosity. While effective in many cases, this assumption may not hold for the infusion process, which lasts for an extended period. This impacts the mechanical properties of the cured epoxy, which are crucial for load transfer in polymer structures. The majority of epoxy resins operate on a bipartite foundation, wherein their viscosity undergoes dynamic alterations during the process of cross-linking. Temperature and cross-linking intricately interact, with elevated temperatures initially reducing viscosity due to kinetic energy but later increasing it as cross-linking accelerates. This interplay significantly influences the efficiency of the infusion process, especially in large and intricate moulds. This article explores the significant temperature dependence of epoxy resin viscosity, proposing an accurate model rooted in its non-linear evolution. This model aligns with empirical evidence, offering insights into determining the optimal starting temperature for efficient mould filling. This study presents an advanced infusion model that extends existing non-linear dual-split viscosity approaches by incorporating the experimental validation of viscosity variations. Unlike previous models that primarily focus on theoretical or numerical frameworks, this work integrates experimental insights to optimize infusion temperature for efficient resin infusion in large and complex parts. Building on these findings, a novel mould-filling technique is proposed to enhance efficiency and reduce material waste. Full article

Fibre deformation (or shearing of yarns) can develop during the liquid moulding of composites due to injection pressures or polymerisation (cross-linking) reactions (e.g., chemical shrinkage). On that premise, this may also induce potential residual stress–strain, warpage, and design defects in the composite part. In this paper, a developed numerical framework is customised to analyse deformations and the residual stress–strain of fibre (at a micro-scale) and yarns (at a meso-scale) during a liquid composite moulding (LCM) process cycle (fill and cure stages). This is achieved by linking flow simulations (coupled filling–curing simulation) to a transient structural model using ANSYS software. This work develops advanced User-Defined Functions (UDFs) and User-Defined Scalers (UDSs) to enhance the commercial CFD code with extra models for chemorheology, cure kinetics, heat generation, and permeability. Such models will be hooked within the conservation equations in the thermo-chemo-flow model and hence reflected by the structural model. In doing so, the knowledge of permeability, polymerisation, rheology, and mechanical response can be digitally obtained for more coherent and optimised manufacturing processes of advanced composites. Full article

The present numerical study proposes a framework to determine the heat flow parameters—specific heat and thermal conductivity—of resin–graphene nanoplatelets (GNPs) (modified) as well as non-modified resin (with no GNPs). This is performed by evaluating the exothermic reaction which occurs during both the filling and post-filling stages of Liquid Composite Moulding (LCM). The proposed model uses ANSYS Fluent to solve the Stokes–Brinkman (momentum and mass), energy, and chemical species conservation equations to a describe nano-filled resin infusion, chemo-rheological changes, and heat release/transfer simultaneously on a Representative Volume Element (RVE). The transient Volume-of-Fluid (VOF) method is employed to track free-surface propagation (resin–air interface) throughout the computational domain. A User-Defined Function (UDF) is developed together with a User-Defined Scaler (UDS) to incorporate the heat generation (polymerisation), which is added as an extra source term into the energy equation. A separate UDF is used to capture intra-tow (microscopic) flow by adding a source term into the momentum equation. The numerical findings indicate that the incorporation of GNPs can accelerate the curing of the resin system due to the high thermal conductivity of the nanofiller. Furthermore, the model proves its capability in predicting the specific heat and thermal conductivity of the modified and non-modified resin systems utilising the computed heat of reaction data. The analysis shows an increase of ∼15% in the specific heat and thermal conductivity due to different mould temperatures applied (110–170 °C). This, furthermore, stresses the fact that the addition of GNPs (0.2 wt.%) improves the resin-specific heat by $3.68\%$ and thermal conductivity by $58\%$ in comparison to the non-modified thermoset resin. The numerical findings show a satisfactory agreement with and in the range of experimental data available in the literature. Full article

The utilisation of numerical process simulation has greatly facilitated the challenging task of liquid composite moulding (LCM) process optimisation, providing ease of solution evaluation at a significantly reduced cost compared to complete reliance on physical prototyping. However, due to the process complexity, such process simulation is still considerably expensive at present. In this paper, cost-saving approaches to minimising the computational cost of simulation-based optimisation for LCM processes are compiled and discussed. Their specific applicability, efficacy, and suitability for various optimisation/moulding scenarios are extensively explored in detail. The comprehensive analysation and assimilation of their operation alongside applicability for the problem domain of interest are accomplished in this paper to further complement and contribute to future simulation-based optimisation capabilities for composite moulding processes. The importance of balancing the cost-accuracy trade-off is also repeatedly emphasised, allowing for substantial cost reductions while ensuring a desirable level of optimization reliability. Full article

This paper presents a numerical framework for modelling and simulating convection–diffusion–reaction flows in liquid composite moulding (LCM). The model is developed in ANSYS Fluent with customised user-defined-functions (UDFs), user-defined-scalar (UDS), and user-defined memory (UDM) codes to incorporate the cure kinetics and rheological characteristics of thermoset resin impregnation. The simulations were performed adopting volume-of-fluid (VOF)—a multiphase flow solution—based on finite volume method (FVM). The developed numerical approach solves Darcy’s law, heat transfer, and chemical reactions in LCM process simultaneously. Thereby, the solution scheme shows its ability to provide information on flow-front, viscosity development, degree of cure, and rate of reaction at once unlike existing literature that commonly focuses on impregnation stage and cure stage in isolation. Furthermore, it allows online monitoring, controlled boundary conditions, and injection techniques (for design of manufacturing) during the mould filling and curing stages. To examine the validity of the model, a comparative analysis was carried out for a simple geometry, in that the numerical results indicate good agreement—3.4% difference in the degree of cure compared with previous research findings. Full article

Permeability is a crucial flow parameter in liquid composite moulding (LCM), which is required to predict fibre impregnation, void formation and resin back flow. This work investigates the dual-scale (micro- and meso-) nature of permeability during resin infusion into woven fabric by incorporating the intra tow flow where the degree of local tow curvature (tow/yarn undulation) is taken into account. The mesoscopic permeability of a dual-scale porous media in a unit cell is estimated using Darcy’s law, where the Gebart analytical model is applied for the intra tow flow in longitudinal and transverse directions with respect to distinct fibre packing arrangements. The results suggest that for a low fibre volume fraction (≤42%), the degree of local curvature at the mesoscale can be neglected. However, for a high fibre volume fraction (>42%) and a higher fibre bundle curvature, the proposed model should be adopted, since the resin flow is affected by a mesoscopic tow curvature that could result in around 14% error in predicting permeability. It is shown that the permeability results of the current study are in good agreement with and in the range of the retrieved available experimental data from the literature. Full article

Liquid composite moulding (LCM) of plant fibre composites has gained much attention for the development of structural biobased composites. To produce quality composites, better understanding of the resin impregnation process and flow behaviour in plant fibre reinforcements is vital. By reviewing the literature, we aim to identify key plant fibre reinforcement-specific factors that influence, if not govern, the mould filling stage during LCM of plant fibre composites. In particular, the differences in structure (physical and biochemical) for plant and synthetic fibres, their semi-products (i.e., yarns and rovings), and their mats and textiles are shown to have a perceptible effect on their compaction, in-plane permeability, and processing via LCM. In addition to examining the effects of dual-scale flow, resin absorption, (subsequent) fibre swelling, capillarity, and time-dependent saturated and unsaturated permeability that are specific to plant fibre reinforcements, we also review the various models utilised to predict and simulate resin impregnation during LCM of plant fibre composites. Full article