The through-thickness compressive behavior of fabric reinforcements is crucial in liquid composite molding manufacturing processes. Predictive simulations of the compressive response are thus necessary to enable a virtual processing workflow. These are complex however, as the compressive behavior of the reinforcement fabrics is non-linear. Altough virtual fiber modeling has proven to be a strong kinematical tool, it cannot predict the compressive response due to the lack of bending stiffness in the virtual fibers. Here, we describe a solution that enables predictive compressive simulations through hybrid virtual fibers. It is based on an overlay mesh-element technique, combining both (i) finite elements that determine the in-plane fiber properties as well as (ii) finite elements that determine out-of-plane fiber bending. Using these hybrid virtual fibers, the through-thickness compression of a twill woven fabric ply is simulated and experimentally validated using both μCT-based as compliance-based measurements. Excellent agreement between simulation and experiment is obtained for the right set of input parameters.@en

In this study, three novel thermoplastic impregnation processes were analyzed towards automotive applications. The first process is thermoplastic compression resin transfer molding in which a glass fiber mat is impregnated in through thickness by a thermoplastic polymer. The second process is a melt-thermoplastic Resin Transfer Molding (RTM) process in which the glass fibers are impregnated in plane with the help of a spacer. The third process, stamp forming of hybrid bicomponent fibers, coats the fibers individually during the glass fiber production. The coated fibers are used to produce a fabric, which is then further processed by stamp forming. These three processes were compared in a life cycle analysis (LCA) against conventional resin compression resin transfer molding with either glass or carbon fibers and metal processes with either steel or aluminum that can be new, partly or fully recycled using the case study of the production, life and disposal of a car bonnet. The presented LCA includes the main phases of the process: extraction and preparation of the raw materials, production and preparation of the mold, process, and energy losses. To include the life of the analyzed bonnet, the amount of diesel that is used to drive the weight of the bonnet for 300′000 km is calculated. In this LCA, the disposal of the bonnet is integrated by analyzing the used energy for the recycling and the incineration. The results show the potential of the developed thermoplastic impregnation processes producing automobile parts, as the used energy producing a thermoplastic bonnet is in the same range as the steel production.@en

Capillarity plays a crucial role in many natural and engineered systems, ranging from nutrient delivery in plants to functional textiles for wear comfort or thermal heat pipes for heat dissipation. Unlike nano- or microfluidic systems with well-defined pore network geometries and well-understood capillary flow, fiber textiles or preforms used in composite structures exhibit highly anisotropic pore networks that span from micron scale pores between fibers to millimeter scale pores between fiber yarns that are woven or stitched into a textile preform. Owing to the nature of the composite manufacturing processes, capillary action taking place in the complex network is usually coupled with hydrodynamics as well as the (chemo) rheology of the polymer matrices; these phenomena are known to play a crucial role in producing high quality composites. Despite its importance, the role of capillary effects in composite processing largely remained overlooked. Their magnitude is indeed rather low as compared to hydrodynamic effects, and it is difficult to characterize them due to a lack of adequate monitoring techniques to capture the time and spatial scale on which the capillary effects take place. There is a renewed interest in this topic, due to a combination of increasing demand for high performance composites and recent advances in experimental techniques as well as numerical modeling methods. The present review covers the developments in the identification, measurement and exploitation of capillary effects in composite manufacturing. A special focus is placed on Liquid Composite Molding processes, where a dry stack is impregnated with a low viscosity thermoset resin mainly via in-plane flow, thus exacerbating the capillary effects within the anisotropic pore network of the reinforcements. Experimental techniques to investigate the capillary effects and their evolution from post-mortem analyses to in-situ/rapid techniques compatible with both translucent and non-translucent reinforcements are reviewed. Approaches to control and enhance the capillary effects for improving composite quality are then introduced. This is complemented by a survey of numerical techniques to incorporate capillary effects in process simulation, material characterization and by the remaining challenges in the study of capillary effects in composite manufacturing.@en

The transverse permeability of roving/tow-based fiber reinforcement is of great importance for accurate flow modeling in the pultrusion process. This study proposes an experimental approach to characterize the roving-based fiber beds' permeability under different compaction conditions. The experimental permeability results of thick roving-based preforms were reported and compared with the permeability values of roving-based preforms in the literature. A representative preform was infused under vacuum conditions. Its thickness was varied to replicate the different compaction values observed in permeability tests. Micrographs were then collected from it and analyzed to highlight the microscale transformations caused by processing/compaction on the fiber arrangement. The analysis revealed that compaction resulted in the reorganization of filaments along the direction of the applied compaction. Overall, the uniformity of the spatial filament distribution, i.e., the homogeneity within the fibrous domain, increased with increasing compaction. Furthermore, the microstructural analysis demonstrated transverse anisotropy within the tested domains, indicating that the obtained permeability results represented an upper boundary. In addition to the experimental analyses, various transverse permeability models, which were developed based on recently introduced statistical descriptors of fiber distribution, were evaluated by using the statistical descriptors extracted from the analyzed cross-sections. Among these models, the one correlating the second neighbor fiber distance with apparent permeability exhibited good agreement with the experimental results. Highlights: Transverse permeability measurement of a roving-based reinforcement was presented. The influence of compaction on the microstructure was investigated at the filament level. Filament distribution in a pultruded profile was analyzed by using statistical descriptors. The results of the experiments and the models in the literature were compared. The correlation between microstructural features and apparent permeability was discussed.@en

Thermoplastic compression resin transfer moulding coupled with injection moulding is an appealing process for the production of thermoplastic composites. However, its implementation at an industrial scale remains challenging as variotherm injection moulding could prevent solid skin formation in the parting line, making cavity sealing difficult. In this study, a tool for thermoplastic compression resin transfer moulding and the related methods and process parameters for an implementation at an industrial scale are presented. The validity of the concept is proved by producing and characterizing composite plates with elevated fibre volume fractions and advantageous mechanical properties at a range of production temperatures within a cycle time not exceeding 20 min. The best mechanical properties were obtained at a production temperature of 270°C with a bending strength of 477 MPa, a flexural modulus measured at 25.7 GPa and a fibre volume content of 67%.@en

Permeability of fibrous microstructures is a key material property for predicting the mold fill times and resin flow path during composite manufacturing. In this work, we report an efficient approach to predict the permeability of 3D microstructures from deep learning based permeability predictions of 2D cross-sections combined via a circuit analogy. After validating the network's predictions in 2D and extending it to 3D, we investigate its capabilities for handling images of various sizes obtained from virtual and real microstructures. More than 90% of 2D predictions is within ± 30% of their counterparts obtained via flow simulations, similarly for 3D transverse permeability predictions, while in 3D case computational time is reduced from several thousands of seconds to less than 10 s. This work provides a robust and efficient framework for characterizing the permeability of fibrous microstructures and paves the way for extending this capability to estimate the permeability of fabric mesostructures.@en

We propose a methodology to monitor the progressive saturation of a non-translucent unidirectional carbon fabric stack through its thickness by means of X-ray radiography and extract the dynamic saturation curves using image analysis. Four constant flow rate injections with increasing flow speed were carried out. These were simulated by a numerical two-phase flow model for both capillary and viscous leading flow conditions. The hydraulic functions describing pressure and relative permeability versus saturation were determined by fitting the saturation curves using a heuristic optimization routine. As the fluid velocity increases and the flow regime at the flow front shifts from capillary to hydrodynamically driven, the resulting capillary pressure curves for a given saturation level are shifted to higher values, from negative to positive. These as well as the capillary pressure calculated from the pressure drop within the unsaturated region of the fabric correlate well with a corresponding change in the averaged dynamic contact angle.@en

Direct visualization is often sought to elucidate flow patterns and validate models to predict the filling kinetics during processes whereby a liquid resin infiltrates a textile porous preform. Here, X-ray phase contrast interferometry is evaluated to image in-operando constant flow rate impregnation experiments of a model fluid into glass, carbon and flax fabrics and a 3D printed structure. A methodology is presented to build the dynamic saturation curve based on image analysis of the dark field images, in which the pixel intensity values are transformed into saturation level versus position and time. The results prove the suitability of this technique to observe the progressive saturation averaged through the thickness of translucent and non-translucent preforms. The porosity network formed by the layers of fabric, the refractive properties of the material, the fabric geometry and its position relative to the X-ray setup are reported to be the main parameters affecting image contrast.@en

A new model is proposed for the consolidation of hybrid textiles, in which air entrapment and dissolution are considered. One of the key parameters is tow permeability, which is described by the analytical model of Gebart and validated at very high fibre volume fractions by direct tow permeability measurement. The model also takes into account the presence of fibres limiting gas diffusion in the molten polymer. Experimental validation of the proposed model is then conducted with quasi-unidirectional glass textile and either polypropylene or polyethylene by measuring the impregnation degree as a function of the consolidation time. Good agreement is found between predictions and measurements for the two matrix systems at different pressures. It is shown that entrapped air significantly influences impregnation. The model offers new and comprehensive insights about the phenomena taking place during consolidation and enables future process optimization.@en

In Resin Transfer Molding (RTM), resin precursors of thermoset or, more recently, thermoplastic polymers are generally employed, raising issues related to the chemical reaction taking place during and after part processing. In this study, already polymerized polyamide-6 with low melt-viscosity (~30 Pa·s at 280 °C), is injected at low pressure (<30 bar) in a custom-made mold, so as to impregnate glass fabric preforms via in-plane impregnation. Composite plates were produced using interply spacers acting as flow-enhancers. A three-step impregnation strategy, involving fast in-plane resin injection, a successive saturation step through transverse flow, followed by further micro-saturation caused by the collapse of the spacers, ensured industrially relevant impregnation kinetics. The influence of the spacer, the saturation time, pressure and temperature on the process kinetics and part quality were evaluated with three-point bending tests as well as microstructural analyses. Optimum processing parameters were identified and scaled up for a given part geometry.@en

In-plane permeability of small area (100 × 50 mm) alumina fiber woven fabrics grafted with aligned carbon nanotubes (CNT) was quantified by placing them in series with a glass mat of known permeability during a flow experiment. The methodology was first validated on a reference woven textile. Permeability values matched those obtained by a direct method within a margin of ±15%. Permeabilities of radial-aligned (short CNT, SCNT) and so-called ‘Mohawk’ (long CNT, LCNT) morphologies of the CNT-grafted samples were then measured and compared to the non-grafted alumina, showing a decrease attributed to a change in local textile structure as assessed in previous studies. Unsaturated permeability decreased by 77% after SCNT- and 88% after LCNT-grafting, while saturated permeability further decreased by 90% and 93%, respectively. The high ratio of unsaturated to saturated permeability (in the range of 1.14 – 2.89) implies that capillary wicking contributes largely to the impregnation of CNT-grafted fabrics.@en

Radical induced cationic frontal polymerisation (RICFP) is considered a promising low energy method for processing of fibre reinforced polymers (FRPs). Optimisation of the local heat balance between reinforcement, epoxy resin and the surrounding mould is required to pave the way for its adaptation to an industrial processing method for high volume fraction structural fibre reinforced composites. In this work, we investigate several methods to control the governing heat balance in RICFP-processing of FRPs. Heat generation was controlled by tuning the initiator concentration while limitation of heat losses using highly insulating moulds was found beneficial to the front characteristics and resulting curing degrees. An optimised mould configuration allowed for self-sustaining RICFP in FRPs with fibre volume fractions (Vfs) up to 45.8%, exceeding previously reported maxima of similar systems. A process window was moreover established relating the Vf and required heat generation to the potential formation of a self-sustaining or supported front.@en

We seek to address how air entrapment mechanisms during infiltration are influenced by the wetting characteristics of the fluid and the pore network formed by the reinforcement. To this end, we evaluated the behavior of two model fluids with different surface tensions, infiltrating three carbon fiber reinforcements, by means of X-ray radiography. We also assessed initial (dry) and final (wetted) states for each experiment by performing X-ray CT scans. We found that the fluid characteristics strongly affect the flow front patterns and pore filling events for a given fabric architecture. Two main promoters of snap-off events are involved in capillary dominated flows: a very wetting system leading to corner flows and the fabric bundles oriented perpendicular to the flow acting as obstacles, specifically in fabric architectures prone to variations in nesting. Finally, we evaluated the applicability of a pore network model to further link preform architecture and void formation.@en

Thin-ply composites are recognized as a key solution for the manufacturing of high-performance composite structures due to the unique mechanical properties and the increased design versatility that they offer. They are obtained with state-of-the-art fiber spreading methods where high-count (6-24K filaments) tows of technical fibers (carbon, glass) are thinned by spreading into flat unidirectional tapes which are then combined with a polymer matrix to create pre-impregnated (prepregs) tapes of reduced thickness. In recent years, the industrialization of fiber spreading and impregnation processes enabled the large-scale production of homogenous thin-ply prepregs with thicknesses down to about 15μm per ply, which attracted the interest of the research community. However, the high production cost due to the complexity of the manufacturing methods and the inherent brittleness of thin-ply composites limit their wider adoption by the composites industry[1]. Fiber hybridization (i.e combining at least two types of fibers in a common matrix) is emerging as a promising approach for alleviating these drawbacks towards laminates with balanced characteristics in terms of mechanical properties and cost-efficiency. Currently, most studies on thin-ply hybrids employ simple interlayer (ply-by-ply) configurations mainly due to difficulties in manufacturing of more complex hybrid architectures[2]. However, simulation tools predict that notable improvements can be obtained from more complex intralayer (tow-by-tow) and intrayarn (fiber-by-fiber) hybrid architectures[3]. This work focuses on the study of existing fiber spreading methodologies, the development of equipment, and the optimization of composite processing at North Thin Ply Technology (NTPT) Renens, Switzerland, that allowed the manufacturing of hybrid composites with a high degree of fiber dispersion and controlled microstructure. Hybrid prepregs were produced by combining various ratios of dissimilar fibers following different processing routes. Composite laminates were manufactured and a versatile microstructural analysis tool was developed that enabled correlations between the manufacturing route, the resulting microstructural features describing the degree of co-dispersion, and the mechanical performance of the final part. Acknowledgments The research leading to these results has been performed within the framework of the HyFiSyn project and has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 765881. Delamination growth in fibre reinforced polymer composites is generally evaluated with experiments that have been standardized for quasi-static load conditions. These tests characterize unidirectional delamination growth in mode I (DCB), mode II (ELS or ENF) of mixed mode conditions (MMB). However, little attention is paid in literature to the applicability of these tests to in-service delamination problems that are generally characterized by planar delamination growth. In this study, the relation between planar delamination growth, induced by transverse quasi-static indentation loading, and these unidirectional delamination tests was investigated. To that aim, prior planar delamination growth tests reported in literature, performed at EPFL, were analysed to identify up to what extent this planar growth could be correlated to the concepts of strain energy release and strain energy density. Once this appeared to successful, an experimental setup was designed to measure the delamination boundary during the transverse indentation loading of planar delamination specimens made of nontransparent carbon fibre reinforced polymer composites. With that set-up, quasi-static and fatigue planar delamination growth experiments were performed, and delamination contours could be successfully captured. While the quasi-static tests revealed limited growth, evaluation with numerical simulations revealed that the indentation force required to extend the delamination quasi-statically would cause damage to the specimen. This is attributed to the increasing length of the delamination contour when delaminations expand, which is not the case with standard unidirectional specimen. With the fatigue tests, however, delamination growth was achieved, but interestingly enough two phases were observed; first the delamination propagated in a planar fashion, while at some point in time work did not exceed an apparent threshold. Instead of no growth, however, the delamination still increased but then in a transverse manner. What makes this study of particular interest, is that the strain energy density as criterion could capture the strain energy offered (work) along the entire delamination contour, while the strain energy release rate described the resistance to delamination growth. This latter observation is in agreement with the original concept employed by Griffith when he formulated the basis of linear elastic fracture mechanics. This presentation present the experiments performed, the analysis of results, and will conclude with a proposal how to relate standard unidirectional tests to planar growth, considering that these standard tests contain little to no information on transverse phenomena with respect to strain energy density (work) and strain energy release (dissipation). @en

We propose a new modeling strategy based on hybrid elements for virtual fiber modeling (also known as the digital element method) to predict both kinematics as well as mechanics of woven fabrics. In virtual fiber modeling, yarns are modeled consisting of a number of discrete fibers. We show that through the development of a modeling strategy based on hybrid elements, we are able to impose correct properties in the fiber direction, as well as out-of-plane properties thanks to the inclusion of fiber bending stiffness. This approach accurately predicts the through thickness compression of a 2x2 twill glass fiber woven fabric. Both kinematically, as well as mechanically, good agreement between experiment and simulation is obtained. Ultimately, these kinds of models could allow faster virtual prototyping as the amount of experimental input is very low and can usually be found in the datasheet. @en

The COVID-19 pandemic resulted in shortages of personal protective equipment and medical devices in the initial phase. Agile small and medium-sized enterprises from regional textile industries reacted quickly. They delivered alternative products such as textile-based community masks in collaboration with industrial partners and research institutes from various sectors. The current mask materials and designs were further improved by integrating textiles with antiviral and antimicrobial properties and enhanced protection and comfort by novel textile/membrane combinations, key factors to increase the acceptance and compliance of mask wearing. The safety and sustainability of masks, as well as taking into account particular needs of vulnerable persons in our society, are new fields for textile-based innovations. These innovations developed for the next generation of facemasks have a high adaptability to other product segments, which make textiles an attractive material for hygienic applications and beyond.@en

Modeling the consolidation of fiber-reinforced thermoplastic composites at the part level presents a formidable computational challenge due to the multi-scale nature of the process. In this article, a method to bypass the multi-scale problem by homogenizing the micro scale and describing the medium with characteristic parameters is described. The model is intended for press molding of hybrid textiles and considers a free-form plate with non-uniform thickness and can describe consolidation in three dimensions with some restrictions. 2D implementation in FEM shows how in-plane matrix pressure gradients can arise in parts and cause fiber disorientation. Experimental verification demonstrates that fiber disorientation arises at the predicted location, and that defect size is proportional to matrix pressure gradient. This novel consolidation model provides new insights, enables part and process optimization, and paves the way for high-quality composite part production. Highlights: A consolidation model for press molding of hybrid textiles is presented. A method to extend consolidation models for complex geometry is presented. The origin of defect formation in complex geometries is explained.@en

Radical Induced Cationic Frontal Polymerisation (RICFP) has recently been proposed as a promising strategy for processing of epoxide carbon fibre reinforced polymers. Control of the local heat balance is crucial towards the production of industrial-quality composites, which is typically achieved via controlling the heat generation. In this work we present a comprehensive overview of RICFP processing of cycloaliphatic epoxide composites with enhance heat insulation. The thermal initiating compound was identified as the main component to control heat generation, which correlated well with the front velocity. A processing window was defined as function of the fibre and initiator contents and composites with to 45.8% Vf were successfully produced. Optimisation of resulting mechanical properties was made possible by optimisation of the heat balance, with matrix glass transition temperatures of up to 187°C achieved for the used cycloaliphatic system. Post-curing was found beneficial to overcome suggested inhomogeneous curing due to the dual-scale nature of fabrics. @en

Knowledge of permeability of fibrous microstructures is crucial for predicting the mold fill times and resin flow path in composite manufacturing. Herein we report a method to rapidly predict the permeability of 3D fibrous microstructures. Our method relies on predicting the permeability of 2D cross-sections via deep neural networks and extending this capability to 3D microstructures via circuit analogy as a means of reduced order modeling. Approximately 50% of the permeability predictions of 2D cross-sections have 10% or less deviation from the permeability results obtained via flow simulations in Geodict. Computational time required for predicting the permeability of 3D microstructures is reduced from hours to less than 10 seconds. This framework enables fast and accurate prediction of micro-permeability and serves as the first building block towards prediction of fabric mesostructures’ permeability via deep learning based methods. @en