In the collaborative effort towards standardisation of out-of-plane permeability measurement, an international benchmarking exercise was carried out whereby 19 participants worldwide were instructed to measure the out-of-plane permeability following a number of strict guidelines, informed by the outcomes of the first international benchmarking exercise completed in 2021. This paper presents the results of the exercise and an assessment of the reproducibility of the data and the suitability of the proposed test method. The data returned were subjected to a number of statistical analysis methods, which showed that adherence to the test guidelines resulted in a high likelihood of a participant not being an outlier and therefore providing evidence that the test method proposed in this paper is a suitable way forward for a standardised test method.@en

This study presents the first steps of a benchmarking exercise on image processing of composite materials. Employing three distinct imaging protocols and five different image processing algorithms, the research explains the variability in capturing microstructural features of common micrograph dataset. Results highlight the sensitivity of different methods to factors like illumination inhomogeneities and pixel density, influencing the accuracy and consistency of obtained results. By comparing methodologies from different researchers in a blind format, the study identifies strengths and limitations, laying the groundwork for future benchmarking activities. Moving forward, this research sets the stage for standardized protocols and guidelines, aiming to enhance the reproducibility and reliability of microstructural analysis in composite materials. Such efforts are crucial for advancing material design and development, ultimately creating tailored composite materials with enhanced performance and functionality.@en

This paper presents an experimental investigation into the compaction behavior of roving-based unidirectional (UD) reinforcements. Understanding the complex dynamics of roving compaction is essential for ensuring the quality in composite manufacturing processes and in return to reach optimal performance. In continuous manufacturing processes like pultrusion or tape manufacturing, achieving proper compaction of rovings is crucial for reaching high fiber volume fractions and consequently, the desired mechanical properties in the final composite profile. However, high compaction in rovings poses challenges, particularly during the impregnation phase, where pressure buildup can occur, potentially leading to the formation of undesirable voids or to excessive forces on fiber, causing fuzz accumulation. Balancing the need for high compaction with the risk of defects is thus a delicate exercise, critical for ensuring the quality and integrity of the final product. Through experimental characterization and analysis, this work examines the influence of various factors to the compressibility of rovings, including the application of tension and different configurations in dry conditions. This study aims to provide valuable insights into characterizing the compaction behavior of roving-based reinforcements and the effect of applied tension, thereby advancing the state-of-the-art in continuous composite manufacturing processes.@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.

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Multiple phenomena occurring at the microscopic scale affect the final mechanical performance of composite parts manufactured through processes involving impregnation of dry fibers, such as resin transfer molding. Formation of fiber-poor areas in specific locations or air entrapment within the resin are issues that commonly arise during the impregnation. Such challenges have motivated the use of numerical simulations to understand the manufacturing processes better and to optimize the process design. However, the limitation imposed by their computational cost has encouraged the use of machine learning (ML) to replace them. Thus far, the state of the art has focused on predicting the permeability of fiber-reinforced microstructures. We expand the limits by proposing an ML-based surrogate for microscale steady-state velocity prediction of a fluid flowing through a fibrous microstructure. This model, inspired by the U-net architecture, takes as input the image representation of fiber-reinforced composite microstructures. It subsequently outputs the resin velocity field around the fibers based on prescribed boundary conditions. Those results are further used to estimate the permeability of the microstructures, thus encompassing previous works. We describe in this work the computational pipeline of our approach, starting from generation of the ground truth data to the optimization of the UNet hyperparameters.@en

Frontal polymerisation has the potential to bring unprecedented reductions in energy demand and process time to produce fibre reinforced polymer composites. Production of epoxy-based fibre reinforced polymer parts with high fibre volume content, commonly encountered in industry, is however hindered by the heat sink created by the fibres and the mould, overcoming the heat output of the chemical reaction, thus preventing front propagation. We propose a novel self-catalysed frontal polymerisation manufacturing method based on the integration of thin resin channels in thermal contact with the composite stack as a strategy for low-energy production of high fibre volume fraction polymer composites without the need for a continuous energy input. Frontal polymerisation inside the resin channel proceeds faster and preheats the fabric stack, thus catalysing the process. Parts with up to 60% fibre content are successfully produced independently of the sample thickness. Fillers added within the resin channels provide means to tailor the frontal polymerisation process kinetics. The parts have a significantly higher glass transition temperature than those produced in a conventional oven, and comparable mechanical properties while energy consumption is reduced by over 99.5%.

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Thin-ply carbon fiber reinforced polymers (CFRP) have claimed significant attention for their potential to surpass traditional composite materials in terms of performance metrics such as first-ply damage criteria, fatigue life, and ultimate strength. This study focuses on investigating the friction behavior of dry carbon fiber tow during mechanical bar spreading, a crucial process in the manufacturing of thinply CFRP. By systematically examining the interplay of wrap angle, tow pre-tension, and final tension, insights are provided into the frictional forces exerted on the carbon fibers. The study utilizes an experimental framework to analyze single-bar and multi-bar setups, considering both symmetric and asymmetric configurations. Results reveal non-linear friction behavior, with increasing wrap angles leading to decreased dynamic friction coefficients. Additionally, results seem to suggest that higher pretension reduces internal tow movement, thereby decreasing friction losses. Multi-bar setups exhibit distinct friction profiles compared to single-bar setups, especially for larger wrap angles and asymmetric cases, indicating the influence of superimposed wrap angles on friction. Recommendations for future research include further exploration of factors such as non-uniform normal loads and relaxation distances between spreader bars to enhance modeling accuracy and optimize friction performance.@en

The aim of this study was to characterise the microstructural organisation of staple carbon fibre-reinforced polymer composites and to investigate their mechanical properties. Conventionally, fibre-reinforced materials are manufactured using continuous fibres. However, discontinuous fibres are crucial for developing sustainable structural second-life applications. Specifically, aligning staple fibres into yarn or tape-like structures enables similar usage to continuous fibre-based products. Understanding the effects of fibre orientation, fibre length, and compaction on mechanical performance can facilitate the fibres’ use as standard engineering materials. This study employed methods ranging from microscale to macroscale, such as image analysis, X-ray computed tomography, and mechanical testing, to quantify the microstructural organisations resulting from different alignment processing methods. These results were compared with the results of mechanical tests to validate and comprehend the relationship between fibre alignment and strength. The results show a significant influence of alignment on fibre orientation distribution, fibre volume fraction, tortuosity, and mechanical properties. Furthermore, different characteristics of the staple fibre tapes were identified and attributed to kinematic effects during movement of the sliver alignment unit, resulting in varying tape thicknesses and fuzzy surfaces.

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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.

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We investigated the debonding on-demand (DoD) of adhesively bonded hybrid dissimilar joints by applying electromagnetic induction heating to the joint overlap section, wherein the epoxy resin is reinforced with iron oxide (Fe₃O₄) particles. Ti-6Al-4 V adherends were bonded with CFRP or GFRP adherends using neat/modified epoxy adhesive. DoD tests revealed that eddy current heating of Ti-6Al-4 V was a dominant heating mechanism of the joints while both eddy current and magnetic hysteresis of CFRP and Fe₃O₄ acted as a secondary heating factor. A low content Fe₃O₄ and thinner composite adherend reduced the time to failure of the joints. Likewise, CFRP required a shorter time for debonding compared to GFRP due to its electromagnetic properties. Modifications with 2 and 5 wt.% Fe3O4 for CFRP and GFRP joints led to 31% and 37% time reduction which will be crucial for energy-saving when debonding large structures. Remarkably, sandblasting improved the electromagnetic induction capabilities of Ti-6Al-4 V, leading to a notable increase in the heating rate, which jumped from around 20°C/s to 80°C/s. Sandblasting enhanced the surface roughness of the adherends but only the water contact angle of GFRP decreased considerably. Fe₃O₄ modifications increased the epoxy residue on the Ti-6Al-4 V surface from 26% to 99%. DIC revealed the strain distribution of bulk materials to understand the thermomechanical mismatches between the materials and the adhesive joints exhibited high peel stresses at the overlap ends. The low weight content (2 and 5 wt.%) of Fe₃O₄ exhibited beneficial effects on the mechanical, thermal, thermomechanical, wettability and lap shear strength.

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Transverse permeability is a key parameter to construct accurate process modelling frameworks for composite manufacturing processes whereby dry reinforcements are impregnated by a resin. The transverse permeability of fibrous structures is strongly correlated with the spatial fiber distribution which is inevitably irregular through the cross section. This irregularity and possible resin channel formation through the cross section cause complex permeability field. In this study, we analysed the correlation between the microstructural features and the apparent transverse permeability. Multiple regions of interest were collected from a pultruded part’s cross section that exhibited apparent resin rich layers. Apparent transverse permeability values of these Regions of Interest (ROIs) were calculated by using OpenFOAM. The principal components of the transverse were calculated, and the statistical descriptors were captured for the corresponding ROIs. The principal permeability component analysis showed that principal directions are in-line with the visual predictions. The correlation between the permeability components and the statistical descriptors shows some traces of the capability of predicting the transverse permeability and the principal components based on the microstructural features. A larger dataset and more elaborate statistical descriptors are needed for accurate prediction of the flow behaviour and the apparent permeability components.@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 (V_fs) up to 45.8%, exceeding previously reported maxima of similar systems. A process window was moreover established relating the V_f and required heat generation to the potential formation of a self-sustaining or supported front.

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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.

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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.

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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

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.

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After the spread of COVID-19, surgical masks became highly recommended to the public. They tend to be handled and used multiple times, which may impact their performance. To evaluate this risk, surgical masks of Type IIR were submitted to four simulated treatments: folding, ageing with artificial saliva or sweat and washing cycles. The air permeability, mechanical integrity, electrostatic potential, and filtration efficiency (FE) of the masks were measured to quantify possible degradation. Overall, air permeability and mechanical integrity were not affected, except after washing, which slightly degraded the filtering layers. Electrostatic potential and FE showed a strong correlation, highlighting the role of electrostatic charges on small particle filtration. A slight decrease in FE for 100 nm particles was found, from 74.4% for the reference masks to 70.6% for the mask treated in saliva for 8 h. A strong effect was observed for washed masks, resulting in FE of 46.9% (± 9.5%), comparable to that of a control group with no electrostatic charges. A dry store and reuse strategy could thus be envisaged for the public if safety in terms of viral and bacterial charge is ensured, whereas washing strongly impacts FE and is not recommended.

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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.

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