Liquid Moulding Research Articles

4D-XCT monitoring of void formation in thick methacrylic composites produced by infusion

Void formation in fibre-reinforced polymer composites processed by liquid moulding is a persistent issue in composite research and development. Not only may several void formation mechanisms come into play, but these defects can also accumulate and grow over the course of the manufacturing process. Mitigation methods can be applied once the underlying causes of voiding are identified, which is impossible through post-mortem characterisation. Here, void formation is dynamically monitored in miniaturised glass fibre-reinforced thermoplastic polymer composite samples manufactured by vacuum infusion and in-situ polymerisation, using laboratory-based X-ray computed tomography (XCT). The method allows the characterisation of the evolution of void patterns as the resin polymerises and cools down within the fibre preform. With a time resolution of 2 min and a voxel size close to 20 µm, this first-of-a-kind XCT experiment provides insights into the evolution of the void volume fraction, void size and location. The root causes leading to void formation in the system of interest were successfully identified as a combination of flow-related air entrapment during preform filling and, mostly, of chemical shrinkage of the matrix upon polymerisation. Additionally, thermal shrinkage during the cooling of the preform results in a slight decrease in the final void volume fraction.

A Numerical Framework of Simulating Flow-Induced Deformation during Liquid Composite Moulding

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.

A DOPO-eugenol linear siloxane as a highly effective liquid flame retardant also imparting improved mechanical properties to an epoxy amine network

A liquid bio-derived eugenol-containing phosphorus silicone hybrid molecule (EGDS-DOPO) that endows excellent flame-retardancy and enhanced mechanical performance to an epoxy amine network at low levels of addition was successfully synthesized and characterised. The EGDS-DOPO significantly improved the flame retardancy requiring only 5 wt% of EGDS-DOPO to achieve a limiting oxygen index (LOI) of 34.9 % and a UL 94 V-0 rating. Cone calorimetry measurements reveal a reduction of the peak heat release rate, the total heat release, and total smoke production by 62.2 %, 34.0 % and 47.5 %, respectively when EGDS-DOPO concentration was 20 wt%, compared to the unmodified epoxy network. Viscosity remained low throughout cure, and despite some retardation of reactivity, the epoxy amine resin remains fast curing and suitable for liquid moulding composite fabrication technologies. Moreover, the modified EGDS-DOPO epoxy networks display a glass transition temperature (Tg) between 218.5 °C and 174.1 °C, a hydrophobic surface with water contact angle of 97.5°–106.6°, a low moisture ingress of 2.35 %–2.91 %, and improved overall mechanical properties in flexure (maximum 39.8 % increase in flexural strength and 27.0 % in flexural modulus), compression (maximum 24.5 % and 35.0 % increase in compressive strength and modulus, respectively), and fracture toughness (maximum 28.0 %).

Thermoviscoelastic modelling of highly reactive thermoset resins for liquid moulding applications

This paper presents a methodology for developing thermo-mechanical properties model for highly reactive resins and its use for Resin Transfer Moulding process (RTM) modelling and prediction of residual stresses. Cure Hardening Instantaneously Linear Elastic (CHILE), and Thermoviscoelastic (TVE) models, were implemented to analyze the mechanical behaviour of the resin. Simulation of the RTM process was developed and applied to a representative curved plate geometry. An integral approach was considered where the degree of cure gradient, generated during the filling stage due to the reactivity of the resin, was implemented as initial condition of the stress-deformation process simulation. The validation process included fabricating experimental parts with the representative geometry. The degree of cure variation of highly reactive thermosets during injection caused a significant effect on the final shape of the parts. These effects were captured by the simulations, where the TVE model showed a more accurate prediction of the part distortion.

A digital twin for smart manufacturing of structural composites by liquid moulding

A digital twin for smart manufacturing of structural composites by liquid moulding

Study on the Consumption Mechanism and Lubrication of Mold Powder Based on Non-Sinusoidal Oscillation Mode

A two-dimensional mold model coupled multiphase flow, heat transfer, solidification and mold oscillation was established based on the casting parameters of the mold of plant. The accuracy of the model was verified by comparing the measured by plant and calculated mold powder consumption under the same casting conditions. The mechanism of mold powder consumption and lubrication was analyzed based on the non-sinusoidal oscillation mode, and the effect of non-sinusoidal oscillation parameters on mold powder consumption was discussed. Mold powder consumption was determined by the downward flow velocity of liquid mold powder and the thickness of liquid mold powder film, the liquid mold powder consumption decreased with the decrease of those. When the mold moved downward, the mold powder thickness and downward flow velocity decreased, the minimum mold powder consumption reached at the middle of the negative strip time, and the variation was to opposite when the mold moved upward, the maximum mold powder consumption appeared during the positive strip time. With the decrease of casting speed and modification ratio, and increase of oscillation frequency and oscillation amplitude, the mold powder consumption had the tendency to increase. The nonlinear regression equation was fitted by the Levenberg–Marquardt method combined with the universal global optimization method to evaluate mold powder consumption.

Cure kinetics, glass transition advancement and chemo-rheological modelling of an epoxy vitrimer based on disulphide metathesis

This study develops cure and chemo-rheological models for a vitrimeric system appropriate for use as matrix in continuous fibre composites based on a disulphide-endowed amine/epoxy formulation. The focus is on the processing conditions relevant to liquid composite moulding. Kinetics is investigated using Differential Scanning Calorimetry. An autocatalytic model is developed, simulating the reaction with an average reaction rate error of 5.2 % and degree of cure error of 3 %. The viscosity development is modelled at relatively low degrees of cure, focusing on the liquid moulding infusion window, yielding results with an average relative error of 4.8 %. The glass transition temperature advancement is represented by the Di Benedetto equation, whilst the topological transition temperature of the system is determined using stress relaxation experiments and found to be 149.5 °C. These results set the scene for the development of composites based on the matrix system investigated in this work.

Synthesis of silica aerogel films in liquid molds

By virtue of their low density and thermal conductivity, aerogels constitute attractive thermal insulators. Of those, aerogel films are best suited for thermal insulation in microsystems. Processes for the synthesis of aerogel films with thicknesses smaller than 2 µm or thicker than 1 mm are well established. However, for microsystems films in the range of a few microns and up to several hundred microns would be beneficial. To circumvent the present limitations, we describe a liquid mold made of two immiscible liquids, used here to produce aerogel films thicker than 2 µm in a single molding step. Following gelation and aging, the gels were removed from the liquids and dried using supercritical carbon dioxide. In contrast to spin/dip coating, liquid molding avoids solvent evaporation from the gel’s outer surface during gelation and aging, films are free-standing and have smooth surfaces. The choice of liquids determines the aerogel film thickness. As a proof of concept, 130 µm thick homogeneous and high porosity (>90%) silica aerogel films were synthesized in a liquid mold with fluorine oil and octanol. The resemblance of the liquid mold approach to the float glass technique offers the prospect of mass production of large sheets of aerogel films.

Thermochemical and rheological characterization of highly reactive thermoset resins for liquid moulding.

Highly reactive thermosets are currently expanding the processability of high-performance structures for transportation industry. The short polymerization time makes it a suitable process to replace metallic structures with polymer matrix-based composite materials. The resin characterization is a fundamental step to obtain the properties and the associated constitutive models, which are required to design and optimize the manufacturing process parameters of composite materials. However, the short time on polymerization requires to use the characterization equipment at their performance capability limits. This work presents a comprehensive methodology to characterize the thermo-chemical properties of highly reactive resin systems, which are relevant for resin impregnation into the preform for liquid injection processes. Four different commercial resin systems are analyzed in this study. Experimental methodologies are analyzed and adapted for best data acquisition at high temperature isothermals. Based on the experimental data, Cure kinetics and viscosity equation-based models are used to describe the behaviour of these complex resin systems. Processing maps are developed based on the cure kinetics and viscosity models to predict the processability time for specific process conditions than can be used on liquid injection moulding processes.

A deep encoder-decoder for surrogate modelling of liquid moulding of composites

A deep encoder-decoder for surrogate modelling of liquid moulding of composites

Improvement of the heat resistance of a liquid mold compound by bismaleimide resin

For next-generation power semiconductors, a highly heat-resistant liquid mold compound was developed based on an epoxy resin having a functional group that can react with bismaleimide (BMI) resin. A liquid resin with a maleimide skeleton was created by prereacting BMI, which has a low melting point of 70–150 °C, with an epoxy resin having allyl and epoxide groups. The maleimide-skeleton epoxy resin was able to precure at ≤150 °C using peroxide and imidazole curing agents. The liquid maleimide-modified epoxy mold compound (EMC) containing silica filler had not a clear glass transition temperature, so the change in physical properties to temperature is very small. This study compared the heat resistance of the developed maleimide-modified liquid mold compound with a general-purpose EMC and silicone gel. The weight loss at 200 °C was less than that of the EMC, and changes in physical properties, which are important for mold compounds, were also small, indicating excellent heat resistance. Therefore, a liquid mold compound containing maleimide resin is likely to be suitable as a mold compound for power semiconductor devices operating at 200 °C.

Low Cost, Ease-of-Access Fabrication of Microfluidic Devices Using Wet Paper Molds.

Rapid prototyping methods enable the widespread adoption of microfluidic technologies by empowering end-users from non-engineering disciplines to make devices using processes that are rapid, simple and inexpensive. In this work, we developed a liquid molding technique to create silicone/PDMS microfluidic devices by replica molding. To construct a liquid mold, we use inexpensive adhesive-backed paper, an acetate backing sheet, and an off-the-shelf digital cutter to create paper molds, which we then wet with predetermined amounts of water. Due to the immiscibility of water and PDMS, mold patterns can be effectively transferred onto PDMS similarly to solid molds. We demonstrate the feasibility of these wet paper molds for the fabrication of PDMS microfluidic devices and assess the influence of various process parameters on device yield and quality. This method possesses some distinct benefits compared to conventional techniques such as photolithography and 3D printing. First, we demonstrate that the shape of a channel’s cross-section may be altered from rectangular to semicircular by merely modifying the wetting parameters. Second, we illustrate how electrical impedance can be utilized as a marker for inspecting mold quality and identifying defects in a non-invasive manner without using visual tools such as microscopes or cameras. As a proof-of-concept device, we created a microfluidic T-junction droplet generator to produce water droplets in mineral oil ranging in size from 1.2 µL to 75 µL. We feel that this technology is an excellent addition to the microfluidic rapid prototyping toolbox and will find several applications in biological research.

A Machine Learning Strategy for Race-Tracking Detection During Manufacturing of Composites by Liquid Moulding

This work presents a supervised machine learning (ML) model to detect race-tracking disturbances during the liquid moulding manufacturing of structural composites. Race-tracking is generated by unexpected resin channels at mould edges that may induce dry spots and porosity formation. The ML model uses the pressure signals recorded by a sensor network as input, providing a classification of the race-tracking event from a set of possible scenarios, and a subsequent variable regression for their position, size and strength. Such a model is based on the residual network (ResNet), a well-known artificial intelligence architecture that makes use of convolutional neural networks for image recognition. Training of the ML classifier and regressors was carried out with the aid of a synthetically generated simulation data set obtained throughout computational fluid dynamics simulations. The time evolution of the pressure sensors was used as grey-level images, or footprints, as inputs to the ResNet ML. The trained model was able to recognise the presence of race-tracking channels from the pressure data yielding good accuracy in terms of label prediction as well as position, size and strength. The model correlation was carried out with a set of injection experiments performed with a constant thickness closed mould containing induced race-tracking channels. The ability of ML models to provide an approximation to the inverse problem, relating the pressure sensor distortions to the cause of such events, is analysed and discussed.

The effect of preforming and infusing bindered and unbindered carbon non-crimp-fabrics on the final quality of composites parts

Vacuum infusion (VI) is a liquid moulding process used to manufacture fibre-reinforced polymer composite parts. The VI process for non-crimp fabric (NCF) preforms is one of the most promising processes for improving the quality and cost efficiency of traditional processes using prepregs and autoclave curing. An understanding of the preform thickness behaviour in the compaction, wetting, and curing stages is necessary to optimise the overall process and obtain high-performance composite parts. In this study, the influence of the material, preforming, and infusion parameters on the thickness of four different carbon NCF laminates were investigated. The preforming behaviour includes the influence of the NCF composition, such as the presence of an organic binder or the number of compaction steps. Infusion was characterised using dielectric analysis (DEA). The properties of the resulting composites were analysed in terms of the fibre volume fraction (FVF) and porosity, as measured using X-ray computed tomography (CT). The main consequence of the outcome of the present study is that, from a manufacturing point of view, downward through-thickness resin infusion offers benefits in terms of thickness, FVF, and porosity tolerance. In addition, the acquired results allow for the identification of the main settings for an optimised consolidation strategy, which could be used for manufacturing NCF composite parts.

A microlevel capillary study in composite materials by X-ray tomography

One of the main problems associated with the manufacture of composite materials by liquid moulding (injection, infusion, etc.) is the generation of porosity. The optimization of the properties of the composites passes through a better understanding of the mechanisms of pore formation and transport. This pore formation is associated with a non-homogeneity of resin flow during the manufacturing process as a consequence of the double-scale porosity present in textile preforms. In the channels between bundles of fibers, the resin flows controlled by the pressure gradient and its viscosity. However, within the fiber bundles, the resin flows as a result of the capillary pressure. As a consequence, if the viscous and capillary forces are not balanced, non-homogeneous local flow occurs and the formation of pores, either between the fiber bundles, or internally to the bundles is produced.In this work a systematic study of the spontaneous wetting process of an E glass fiber bundle through wicking tests, using several fluids with different properties, viscosity, surface tension and contact angle is presented. The visualization of the front position of the resin flow at microscopic scale, as well as the formation of the menisci between fibers has been performed using X-ray tomography techniques using synchrotron radiation. The reconstructed volumes have made it possible to obtain detailed quantitative information on the geometry of the menisci which occur as a consequence of the surface tension operating at such scale. These characterization techniques constitute a fundamental tool for the optimization of the processing of composite materials buy liquid moulding.

Optimisation of intra-ply stitch removal for improved formability of biaxial non-crimp fabrics

Automated fabric forming solutions are required to meet the demand of liquid moulding processes, but wrinkling is a common problem for double-curvature parts due to a combination of the reinforcement type, manufacturing parameters and the part geometry. Local intra-ply stitch removal is introduced in the current work to improve the formability of a pillar-stitched biaxial NCF. An optimisation method is developed to remove stitches selectively, using a genetic algorithm coupled with a finite element model. Two criteria are defined to reduce the occurrence of forming defects whilst maintaining the integrity of the fabric. The first is to minimise the local shear angle across the surface of the ply and the second is to minimise the total stitch removal area. These criteria are combined into a single objective function and validated using a hemisphere forming case study. Experimental results confirm that macro-scale wrinkling can be successfully eliminated when intra-ply stitches are removed according to the optimised pattern. The stitch removal regions are distributed across both the positive and negative shear areas of the optimised NCF blank, indicating that local stitch removal can have a global effect on the formability. Perimeter shapes show that the optimum local stitch removal pattern enables a more balanced global material draw-in, demonstrating that the effect of stitch removal is not limited to the high shear regions. Removing stitches from just the over-sheared regions is therefore insufficient to fully mitigate wrinkles, justifying the need for the optimisation algorithm, as the optimised stitch removal pattern appears to be non-intuitive.

In situ local imaging and analysis of impregnation during liquid moulding of composite materials using synchrotron radiation computed laminography

Analysis of the impregnation process during injection experiments in fibre-reinforced polymer composites has been carried out via a three-dimensional in-situ imaging method, namely Synchrotron Radiation Computed Laminography (SR-CL). A resin transfer moulding device was designed to perform injection experiments at different flow rates while, at the same time, the evolution of the flow front was inspected by SR-CL. Injections with flow rates of 50 μL/min and 300 μL/min in plain woven E-glass fabrics were carried out, resulting in small capillary number fluid propagation with capillary forces dominant over viscous ones. Intratow and intertow voids were accurately segmented by using a machine learning algorithm that enabled the direct measurement of their time and spatial distribution from the raw XCT volumes. The saturation evolution, void content, shape and spatial distribution quantification are reported. Intratow void formation and transport mechanisms were accurately described, in particular those related with large void splitting including the subsequent flow dragging. Advantages and limitations of the use of SR-CL for the analysis of the impregnation process of dry preforms in liquid moulding are discussed in detail, and in particular, those aspects related with the time acquisition limitations.

Isothermal and Non-isothermal Crystallization Kinetics of Mold Fluxes used in Continuous Casting of Steel: A Review

Casting powders or mold fluxes, as they are more commonly known, are used in the continuous casting of steel to prevent the steel shell from sticking to the copper mold. The powders first melt and create a pool of liquid flux above the liquid steel in the mold, and then the liquid mold fluxes penetrate into the gap between water-cooled copper mold and steel shell, where crystallization of solid phases takes place as the temperatures gradually drop. It is important to understand the crystallization behavior of these mold fluxes used in the continuous casting of steel because the crystalline phase fraction in the slag films plays a crucial role in determining the horizontal heat flux during the casting process. In this work, the existing literature on the crystallization kinetics of conventional and fluoride-free mold fluxes used in the continuous casting of steel has been reviewed. The review has been divided into two main sections viz. the isothermal crystallization kinetics and non-isothermal crystallization kinetics. Under each of these sections, three of the most widely used techniques for studying the crystallization kinetics have been included viz. thermoanalytical techniques such as differential scanning calorimetry/differential thermal analysis (DSC/DTA), the single and double hot thermocouple technique (SHTT and DHTT), and the confocal scanning laser microscopy (CSLM). For each of these techniques, the available literature related to the crystallization kinetics of mold fluxes has been summarized thereby encompassing a wide range of investigations comprising of both conventional and fluoride-free fluxes. Summaries have been included after each section with critical comments and insights by the authors. Finally, the relative merits and demerits of these methods vis-à-vis their application in studying the crystallization kinetics of mold fluxes have been discussed.

Composite temperature profile and tooling optimization via Deep Reinforcement Learning

Carbon Fibre Reinforced Plastic (CFRP) manufacturing cycle time is a major driver of production rate and cost for aerospace manufacturers and manufacturers in other composite heavy industries. One major thread in optimizing liquid moulding manufacturing processes such as VARTM involves modifying variables affecting heat transfer while the composite is being processed. Modelling and control of these curing processes is known to be challenging as the temperature response during cure is dependent on many variables including resin cure kinetics, carbon perform thickness and material properties, tooling thickness and material properties, and autoclave or oven heat transfer coefficients. In this work, we introduce a novel optimization method for composite cures taking into account both air temperature and tooling. Framing oven air profile optimization as optimal control, we are able to learn an adaptive and generalizable temperature controller via Deep Reinforcement Learning in simulation. Using 5 1D heat diffusion models at different locations, this controller learns from experience to anticipate the thermochemical dynamics of composite curing, and makes use of both heating and cooling to reduce cycle time while adhering to soft constraints on the maximum temperature of the system and avoid thermal runaway. This adaptive controller is then used in a Bayesian Optimization loop to optimize tooling geometry, adding and removing thermal mass in different locations to ensure the resultant cure adheres to hard constraints and has minimal overall cycle time. On two realistic aerospace parts with complex geometry and varying thicknesses we are able to reduce ramp to cure time by 27 to 40%.

The Effect of Ensiling Sugar Beets on Preservation Characteristics, Nutrient Profile, and in Situ Disappearance

The objective of this project was to determine if sugar beets could be ensiled with hay or soybean meal with or without a liquid mold inhibitor and the impact on nutrient composition, pH, and aerobic stability. A 3 x 2 factorial experiment where hay (control; H) or sugar beets mixed with either hay (SBH) or soybean meal (SB) were ensiled at a rate of 50:50 (as fed) without the mold inhibitor. The mold inhibitor (T) was included to create three additional treatments: HT, SBT, and SBHT. All treatments decreased in pH over time (P < 0.01), with the lowest pH value being generated by the SB treatment. Concentrations of NDF increased between d 0 and d 90 for treatments SB and SBT (P ≤ 0.01) and increased between d 90 and d 180 for treatments H, HT, SBH, and SBHT (P ≤ 0.01). Concentrations of ADF also increased among all treatments (P ≤ 0.05). Concentrations of CP increased from d 0 to d 90 for HT and SB treatments (P ≤ 0.01), increased from d 90 to d 180 for the SBT treatment (P ≤ 0.02), increased from d 0 to d 180 for the SBH treatment (P ≤ 0.03), and decreased from d 90 to d 180 for the SB treatment (P ≤ 0.01). The data suggests that sugar beets may be ensiled with hay or soybean meal, with or without a liquid mold inhibitor, without negatively impacting nutrient quality or preservation characteristics of the ensiled mixture.