Resin Transfer Molding Process Research Articles

On the Fabrication Processes of Structural Supercapacitors by Resin Transfer Molding and Vacuum-Assisted Resin Transfer Molding

This study investigated the manufacturing processes for structural supercapacitors (SSCs) using smear molding (RS), resin transfer molding (RTM), and vacuum-assisted resin transfer molding (VARTM). Woven carbon fibers were used as the electrode, woven glass fibers as an insulating layer, and an alkaline/epoxy compound as the electrolyte. In the RTM process, due to the vacuum and the high-pressure injection of the electrolyte, the electrochemical and mechanical properties of the SSC can be greatly improved, and the void contents in the SSC can be reduced. The balanced electrochemical performance and mechanical properties of SSCs were observed in the range of epoxy content from 15 wt% to 30 wt%. This study contributes to the development of SSCs through the establishment of the fabrication process for improvements in part quality. The fabrication method demonstrated here can be directly applied by industries to produce even larger-scale SSCs, opening up new possibilities for practical implementation and scalability.

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.

Surface Treatments' Influence on the Interfacial Bonding between Glass Fibre Reinforced Elium® Composite and Polybutylene Terephthalate.

This study examines the process of using injection moulding to join two different materials to manufacture bi-component moulded products with improved performance characteristics. The two-component process, which combines the advantages of two different technologies-the high efficiency of the injection moulding process and the excellent mechanical properties of long glass fibre composites produced by resin transfer moulding (RTM) technology-offers a particular advantage and improved applicability of the prepared lightweight products in both the automotive and aerospace sectors. The composite studied here consists of Elium® thermoplastic resin (30%) reinforced with unwoven glass fibre fabric (70%) using the RTM process. The Elium® composite sample is consequently used as an insert overmoulded with polybutylene terephthalate (PBT) homopolymer reinforced with 20% w/w of short glass fibre through injection moulding. The influence of different mould temperatures and surface treatments on the adhesion between the materials used is investigated by evaluating the mechanical performance using tensile shear strength tests. It was found that while an increase in mould temperature from 40 °C to 120 °C resulted in a doubling of the initial average bond strength between untreated Elium® RTM inserts and overmoulded PBT parts (0.9 MPa), sandblasting the inserts ensured a further tripling of the bond strength of the composites to a value of 5.4 MPa.

Optimization of the VARTM Process for Prototyping a Bumper Using Hybrid Composite Materials

To provide an alternative for manufacturing auto parts using composite materials, the Vacuum Assisted Resin Transfer Molding (VARTM) process was utilized to prototype the bumper for the Chevrolet Aveo vehicle. This technique emerges as an alternative for composite material manufacturing, allowing for rapid and high-quality production of advanced composites. In this study, a hybrid composite material reinforced with fiberglass, cabuya fiber, IN2 epoxy resin, an infusion mesh, peel ply, and a vacuum bag was employed. To optimize the VARTM process in bumper prototyping, several simulations of resin flow were conducted with different locations of resin injection and vacuum entry points. Autodesk Moldflow Insight software facilitated the modification and addition of resin injection points to observe the flow evolution, thus determining the filling time for each proposed design. Six different designs were applied for the bumper mold filling. The proposed linear flow design reduced the total filling time of the bumper mold by 81.56% compared to the other five designs analyzed. The result of the numerical simulation was validated through the experimental process, where a high degree of concordance in the mold filling time was achieved between both methods.

Application of machine learning for composite moulding process modelling

Fibre-reinforced composites are commonly manufactured through moulding processes such as Resin Transfer Moulding (RTM) due to their great reliability and scalability. State-of-the-art RTM process modelling and simulation primarily rely on computationally expensive physics-based modelling methods. Given the great volume of possible input-output combinations, process optimisation via exhaustive physics-based simulations or experiments becomes unfeasible. Hence, this paper proposes the integration of machine learning to facilitate composite moulding process modelling. The well-established PixelRNN, an image-based machine learning model, is employed to model and simulate the complex composite mould filling phenomenon. Upon training and validation, the developed PixelRNN metamodels demonstrated impressive prediction accuracies of up to 97.35 % at 50 % training data proportions, at roughly half the cost of exhaustive simulations. The results of this early study convincingly underscore the promising potential of machine learning in composite moulding applications, particularly when utilising graphical input data rather than the traditional numeric data.

An Enhanced Vacuum-Assisted Resin Transfer Molding Process and Its Pressure Effect on Resin Infusion Behavior and Composite Material Performance.

In this paper, an enhanced VARTM process is proposed and its pressure effect on resin infusion behavior and composite material performance is studied to reveal the control mechanism of the fiber volume fraction and void content. The molding is vacuumized during the resin injection stage while it is pressurized during the mold filling and curing stages via a VARTM pressure control system designed in this paper. Theoretical calculations and simulation methods are used to reveal the resin's in-plane, transverse, and three-dimensional flow patterns in multi-layer media. For typical thin-walled components, the infiltration behavior of resin in isotropic porous media is studied, elucidating the control mechanisms of fiber volume fraction and void content. The experiments demonstrate that the enhanced VARTM process significantly improves mold filling efficiency and composite's performance. Compared to the regular VARTM process, the panel thickness is reduced by 4% from 1.7 mm, the average tensile strength is increased by 7.3% to 760 MPa, the average flexural strength remains at approximately 720 MPa, porosity is decreased from 1.5% to below 1%, and the fiber volume fraction is increased from 55% to 62%.

Influence of MoS2 nano-filler additions on wear behavior of carbon fiber reinforced epoxy composites

In this research work, two body wear and three-body wear performance of carbon fabric reinforced HTR 212 epoxy resin(CF/Epoxy) composites are experimentally evaluated. Carbon fabric/epoxy resin composite panels with MoS2 nano-filler additions of 0.1, 0.2, 0.4 and 0.7 weight percentage are developed by Vacuum Assisted Resin Transfer Molding process. Two Body Wear test is conducted on the prepared specimen in accordance with ASTM G-99, whereas Three Body Abrasive wear test is conducted as per ASTM G-65. Experimental Tests are conducted for sliding and abrading distances in multiples of 250 m up to 1500 m. Results reveal that Carbon fabric/epoxy resin composites with 0.7 weight percent of MoS2 show 18% reduction in two body wear compared to a decrease of 35% in Three Body abrasive wear at 1500 m abrading distance. Scanning Electron Microscopy is used to study the surface morphology of the tested samples and to know the mode of damage at the surface.

Near-infrared spectroscopy in resin transfer molding—determination of the degree of cure

Near-infrared (NIR) spectroscopy is employed to directly monitor the degree of cure of composite material during the curing phase in the resin transfer molding (RTM) process. The composite material consists of natural fibers and an epoxy-amine resin system. The quantitative determination of the degree of cure, α, from the NIR spectra is realized by partial least square (PLS) regression in conjunction with various pre-treatments of the spectral data. As a reference, the degree of cure is determined by isothermal differential scanning calorimetry (DSC) experiments. The best PLS model that could be obtained for α is characterized by a determination coefficient of prediction (R²P) of 0.980 and root mean square error of prediction (RMSEP) of 4.4 %. While the spectra change during curing according to the literature for each RTM trial, significant differences can be observed between the spectra of different RTM trials. The reasons for this are discussed in detail. The findings show the potential of inline NIR spectroscopy for monitoring α in the RTM process.

Dynamic wetting performance and resin-flow behavior of two-level selective laser-etched metal surface in resin transfer moulding process of fiber-metal laminates

ABSTRACT In selective laser etching for the interfacial strengthening of Fiber Metal Laminates (FMLs), the wettability of customized structured features significantly affects their overall mechanical properties. For two-level features, their complicated geometry makes the evaluation of wettability difficult, which introduces challenges to feature design. In this study, a sandwich FMLs comprising an AA2024-O metal skin and a plain-woven carbon-fiber fabric core is investigated. Three types of two-level feature interfaces are designed and introduced into the FMLs structure. To understand the effect of two-level features on the resin flow and dynamic wetting progress in resin transfer molding, two-phase flow Computational Fluid Dynamics numerical models coupled with porous media and level-set numerical methods are built. The feasibility of the numerical simulation in the qualitative analysis was verified by comparing the results with those of the testing porosity values from X-ray scanning. In addition, the mechanisms of pore formation and transportation are revealed. These results indicate that the deeper groove structure in the etched features plays an important role in discharging residual air and determining the transformation of pores to reduce porosity. The permeability orientations of the porous media and surface structure both have significant impacts on the flow behavior and formation of pores.

A Novel Preparation Method of Composite Bolted T-Joint with High Bending Performance Based on the Prepreg-RTM Co-Curing Process.

A co-curing resin system consisting of 9368 epoxy resin for prepreg and 6808 epoxy resin for resin transfer molding (RTM) was developed. A corresponding preparation method for a novel polymer composite bolted T-joint with internal skeleton and external skin was proposed based on the prepreg-RTM co-curing process, and novel T-joints were fabricated. A series of conventional configuration T-joints based on the RTM process and T-joints made of 2A12 aluminum alloy were prepared simultaneously. Bending performances were studied on these T-joints experimentally. The results indicate that 9368 epoxy resin and 6808 epoxy resin exhibit good compatibility in rheological and thermophysical properties. The novel T-joints prepared with the prepreg-RTM co-curing process show no obvious fiber local winding or resin-rich regions inside, and the interface quality between the internal skeleton and the external skin is excellent. The main failure modes of the novel T-joint under bending load include the separation of the skin and skeleton and the fracture along the thickness on the base panel; the skeleton carries the main bending load, but there is still load transfer between external skin and internal skeleton through their interface. The internal damages of the novel T-joint are highly consistent with surface damages observed visually, facilitating the detection and timely discovery of damages. The initial stiffness, damage initiation load, and ultimate load of the novel T-joint are 1.65 times, 5.89 times, and 3.45 times that of the conventional T-joint, respectively. When considering the influence of the density, the relative initial stiffness and relative ultimate load of the novel T-joint are 1.44 times and 2.07 times that of the aluminum alloy T-joint, respectively.

Comprehensive Composite Mould Filling Pattern Dataset for Process Modelling and Prediction

The Resin Transfer Moulding process receives great attention from both academia and industry, owing to its superior manufacturing rate and product quality. Particularly, the progression of its mould filling stage is crucial to ensure a complete reinforcement saturation. Contemporary process simulation methods focus primarily on physics-based approaches to model the complex resin permeation phenomenon, which are computationally expensive to solve. Thus, the application of machine learning and data-driven modelling approaches is of great interest to minimise the cost of process simulation. In this study, a comprehensive dataset consisting of mould filling patterns of the Resin Transfer Moulding process at different injection locations for a composite dashboard panel case study is presented. The problem description and significance of the dataset are outlined. The distribution of this comprehensive dataset aims to lower the barriers to entry for researching machine learning approaches in composite moulding applications, while concurrently providing a standardised baseline for evaluating newly developed algorithms and models in future research works.

Environmental Impact of an Innovative Aeronautic Carbon Composite Manufactured via Heated Vacuum-Assisted Resin Transfer Molding

The Vacuum-Assisted Resin Transfer Molding (VARTM) process has gained popularity as a reliable and cost-effective alternative to autoclave molding for high-performance composite production, which is especially interesting for aeronautics, where weight reduction is crucial. However, to date, the environmental impact of components produced through VARTM remains relatively unknown. To address this gap, this study applied the Life Cycle Assessment (LCA) methodology to estimate the environmental impact of a thermoset composite laminate produced through heated VARTM. Aiming to support the decision, the VARTM composite part’s production was compared to conventional autoclave manufacturing, and the influence of alternative end-of-life (EoL) scenarios and energy mixes was considered, through LCA. The study found that energy consumption represented the majority of the environmental impacts of the heated VARTM component (33%), followed by carbon fibers, resins, consumables, and wastes. In terms of the comparative analysis, the autoclave manufacturing process showed better environmental results. Regarding EoL management, supercritical hydrolysis (with heat recovery) recycling emerges as the most beneficial method, reducing the impacts of the VARTM-manufactured component by 25%. This study emphasizes the importance of sustainable practices, such as reducing energy consumption, using low-carbon energy mixes, and adopting recycling methods to improve VARTM composite’s environmental performance.

Pultrusion vs RTM

Pultrusion and resin transfer molding (RTM) are two widely used manufacturing processes for producing composite materials. Kim Sjödahl, VP of technology and R&D at Exel Composites, considers the benefits of pultrusion and compares them to the RTM process.

Evaluation of resin impregnation using self-sensing of carbon fibers

The wettability of fiber-reinforced composites plays a crucial role in both mechanical properties and the efficiency of the manufacturing process. This is particularly significant in large and intricate composite structures where any flaws can have more severe consequences. In this study, the impregnation of epoxy resin into carbon fiber (CF) mats in-situ was monitored by observing the electrical resistance (ER) behaviors of CFs without any other additional sensors. The ERs of CF and CF tows at various points were measured, while epoxy resin was applied to establish fundamental data on ER behavior during the Vacuum Assisted Resin Transfer Molding (VARTM) process. During the VARTM process, the ERs of CF mats in-situ were compared with the behaviors of micro and sub-micro CFs, along with capturing images of the front flow of epoxy resin. The ER data obtained during the VARTM process was visualized through 3D ER mapping, which allowing for real-time monitoring of the flow front. Ultimately, the resin flow front of epoxy resin into CF mats was successfully monitored using the ER behaviors of CFs themselves.

Static and dynamic study of fiber-reinforced hemispherical stacked sandwich structure

Sandwich structures have garnered considerable attention due to their ability to meet the requirements of the aerospace and defense industry for impact resistance and lightweight performance. Unlike the plate or block construction investigated in previous studies, this present study proposes a new type of configuration known as the fiber-reinforced hemispherical stacked sandwich (FRHSS) structure. The fabrication of this FRHSS is achieved through the utilization of the Vacuum Assisted Resin Transfer Molding (VARTM) process and its response under quasi-static compression load is analyzed through both simulation and experiment. It is found that the internal configuration design effectively determines the direction of contraction in the hemispherical construction when it is subjected to quasi-static compression load. Furthermore, the impact resistance of the FRHSS against projectile penetration is also assessed. Through a comparison of simulation and experimental results, it becomes evident that the Chang-Chang failure criterion can successfully model the penetration process. Finally, the influence of internal configuration on the penetration resistance of the structure is studied by finite element method. The results show that the internal configuration plays an important role in the ballistic limiting velocity and ballistic performance of the construction. This study provides a valuable reference for the design of hemispherical sandwich structures.

Void formation and suppression in CFRP laminate using newly designed ultrasonic vibration assisted RTM technique

This study introduces an ultrasonic vibration assisted resin transfer molding (RTM) technique as an innovative approach to address the inherent challenges associated with traditional methods for producing CFRP laminates. It investigates the mechanism of void formation in CFRP composites under ultrasonic vibration using 3D X-ray microscopy. Numerical calculations and simulation analyses are also employed to validate the impact of ultrasonic vibration on mechanical properties of CFRP. The findings indicate that ultrasonic vibration results in CFRP laminates with more uniform thickness, leading to a substantial increase in fiber volume fraction up to ∼16 %. Concurrently, there are significant improvements in flexural strength (∼20 %) and fracture energy (∼90 %). Ultrasonic vibration also effectively reduces CFRP porosity by at least 25 %, resulting in a more consistent distribution of voids, primarily consisting of small circular voids. This porosity reduction is attributed to the cavitation effect and enhancing wettability, consequently improving the mechanical properties of CFRP. Moreover, simulations and numerical calculations demonstrate the significant occurrence of cavitation effect within the resin under specific process conditions. The intensity of cavitation is influenced by factors such as the initial bubble radius, acoustic pressure amplitude, and static pressure of the resin. The ultrasonic-assisted RTM process is proved as a promising method for producing CFRP laminates with superior properties.

Physical and mechanical characterization of glass fiber‐grewia optiva fiber reinforced hybrid polymer composite fabricated by vacuum assisted resin transfer moulding

AbstractThe natural and synthetic fibers are combined in a single composite to achieve a balance between the desired strength and cost considerations. In this study, the vacuum resin transfer moulding process was used to prepare an epoxy‐based composite. The composite consisted of grewia optiva as the natural fiber and glass fiber as the synthetic fiber, both with a fixed weightage of 10 %. Dolomite was used as a filler with varying content (0 %, 5 %, 10 %, and 15 weight %). The physical, mechanical, erosion wear and morphological behavior of the epoxy‐based composite were investigated. The inclusion of dolomite filler significantly increased the composite hardness and impact strength but reduced its tensile and flexural strength. At a dolomite filler content of 10 weight %, the erosive wear was reduced, while it increased at higher dolomite filler contents. The composite was examined using the L16 array, and the minimum wear rate was observed at an impingement angle of 30°, a velocity of 10 m/s, and an erodent size of 150 μm. Morphological studies were conducted to explore the possible mechanism for the variation in erosive wear at different dolomite contents in the hybrid composites.

Bayesian Optimal Experimental Design for Race Tracking in Resin Transfer Moulding

A Bayesian inference formulation is applied to the Resin Transfer Moulding process to estimate bulk permeability and race-tracking effects using measured values of pressure at discrete sensor locations throughout a preform. The algorithm quantifies uncertainty in both the permeability and race-tracking effects, which decreases when more sensors are used or the preform geometry is less complex. We show that this approach becomes less reliable with a smaller resin exit vent. Numerical experiments show that the formulation can accurately predict race-tracking effects with few measurements. A Bayesian A-optimality formulation is used to develop a method for producing optimal sensor locations that reduce the uncertainty in the permeability and race-tracking estimates the most. This method is applied to two numerical examples which show that optimal designs reduce uncertainty by up to an order of magnitude compared to a random design.

Modeling formation and evolution of voids in unsaturated dual scale preforms in Resin Transfer Molding processes

Modeling formation and evolution of voids in unsaturated dual scale preforms in Resin Transfer Molding processes

Effect of mold on curing deformation of resin transfer molding‐made textile composites

AbstractIn the process of preparing textile composites by resin transfer molding (RTM) method, both the upper and lower surface of the mold will interact with the composite parts due to the mismatch of thermal expansion coefficient between the mold and the part, resulting in warpage deformation. To address this key technical problem, this article first studied the effect of mold on the warpage deformation of composite material under different fiber volume fractions. Then a mold–part interaction modeling method for RTM process with nonthermoelastic deformation is proposed. By introducing shear layers between the upper and lower surfaces of the mold and the composite part, a finite element simulation model for predicting the curing deformation of the component is established and experimentally verified. The results show that the effect of mold–part interaction on the warpage deformation of the composite decreases with increasing fiber volume fraction. Meanwhile, the proposed modeling method can avoid complete material characterization, and the comparison between experimental and simulation results proves that the model can accurately simulate the curing deformation of composite components under the same process conditions. Finally, the analysis reveals that the interaction caused by thermal mismatch between the composites and the mold is less related to the intermediate layup, but mainly related to the fiber orientation of the layup layer in contact with the mold.Highlights The warpage deformation law of the mold on the composites with different fiber volume fractions is investigated. A mold–part interaction modeling method for a resin transfer molding process with nonthermoelastic deformation is proposed, where the mold stretching effect is represented by the cumulative effect of the interaction between the two layers on the upper and lower surfaces of the part.