Characterization of textile permeability as a function of fiber volume content with a single unidirectional injection experiment

Fratta, Claudio Di; Klunker, Florian; Trochu, F.; Ermanni, Paolo

doi:10.1016/j.compositesa.2015.05.021

Cited by 36 publications

(21 citation statements)

References 24 publications

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“…The “normalized K ” correctly relates the dependence of the flow characteristics on the fiber volume V f . Dimensionless permeability has a direct relates to the fabric volume fraction variance showing the dependence on the normalized permeability with fiber reinforcement, which is in a good agreement with the literature .…”

Section: Resultssupporting

confidence: 88%

Hybrid‐permeability model evaluation through concepts of tortuosity and resistance rate: Properties of manufactured hybrid laminate

Monticeli¹,

Vidal²,

Shiino

et al. 2019

Polymer Engineering & Sci

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The mechanical properties of composite structures depend on the preform impregnation and a successful impregnation can be achieved using the permeability relation in the case of an infusion process. The objective of this study is to develop an analytical model to predict the permeability K of carbon and glass fabrics through hybrid laminate using different stacking sequence, applying an average-permeability model. Preforms permeabilities were evaluated through tortuosity and void-volume fraction. The model allows the analysis of different stacking sequence combinations (interleaved and in block), measuring the contribution of each material type. As a result, hybrid average-permeability model was validated through experimental permeability tests, dimensionless permeability, and tortuosity results, besides enabling predictions of the flow front behavior with <10% of deviation. Carbon fiber preforms exhibited higher flow resistance, which is explained via tortuosity concept. A combination of carbon/glass preforms presented an increased permeability, which means a synergy that provides higher value of K. In addition, the use of hybrid preforms, especially Hybrid 2 stacking sequence, reduce the injection time and void formation, ensuring composite impregnation quality. POLYM. ENG. SCI., 59:1215-1222, 2019

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Section: Resultssupporting

confidence: 88%

Hybrid‐permeability model evaluation through concepts of tortuosity and resistance rate: Properties of manufactured hybrid laminate

Monticeli¹,

Vidal²,

Shiino

et al. 2019

Polymer Engineering & Sci

View full text Add to dashboard Cite

show abstract

“…To avoid such an undesired time shift, a practical solution could be filling the sensor cavities prior to the experiments as detailed in Di Fratta et al. 68 The slight difference between the experimental and simulated pressures in the post-filling stage is suspected to be due to the characterization approach of the compaction behavior. Wet compaction behavior is characterized in unloading by decreasing Pc during the measurements as detailed in the Compaction Characterization section whereas Pc increases with time during the post-filling stage and this difference is likely to contribute significantly to the deviation between experimental and simulated pressure curves in the post-filling stage.…”

Section: Resultsmentioning

confidence: 99%

Monitoring and modeling of part thickness evolution in vacuum infusion process

Caglar

Hancioglu

Sozer

2020

Journal of Composite Materials

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The main hurdles in Vacuum Infusion (VI) are the difficulty in achieving complete mold filling and uniform part thickness. This study integrates process monitoring by full field thickness measurements and resin flow modeling that accounts for compaction and permeability characterizations of fabric reinforcements to assess the evolution of part thickness during filling and post-filling stages of VI process. A Structured Light Scanning system is used for full field thickness monitoring in experiments and a Control Volume Finite Element Method solver is implemented to couple resin flow with fabric’s compaction and permeability. Two cases are studied both experimentally and numerically. Evolutions of thickness and pressure validate the developed flow solver, its accuracy in terms of predicting fill times and fill patterns, suitability and limitations of the elastic compaction models for thickness modeling.

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“…The injectability number, which is again equal to 10 9 for the considered reference parameters, depends also here only on the mold geometry (via the characteristic length L) and on the properties of the textile preform (permeability K and porosity ϕ). Note that the preform permeability is generally an exponential function of fiber volume content [30]; thus, it dominates porosity in the ratio K/ϕ. Therefore, the injectability number given by Equations (3) and (6) for a unidirectional flow is mainly determined by the permeability and the characteristic length L of the cavity.…”

Section: Analytical Solution At Constant Injection Flow Ratementioning

confidence: 99%

A Dimensionless Characteristic Number for Process Selection and Mold Design in Composites Manufacturing: Part I—Theory

et al. 2020

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The present article introduces a dimensionless number devised to assist composite engineers in the fabrication of continuous fiber composites by Liquid Composite Molding (LCM), i.e., by injecting a liquid polymer resin through a fibrous reinforcement contained in a closed mold. This dimensionless number is calculated by integrating the ratio of the injection pressure to the liquid viscosity over the cavity filling time. It is hereby called the “injectability number” and provides an evaluation of the difficulty to inject a liquid into a porous material for a given part geometry, permeability distribution, and position of the inlet gate. The theoretical aspects behind this new concept are analyzed in Part I of the article, which demonstrates the invariance of the injectability number with respect to process parameters like constant and varying injection pressure or flow rate. Part I also details how process engineers can use the injectability number to address challenges in composite fabrication, such as process selection, mold design, and parameter optimization. Thanks to the injectability number, the optimal position of the inlet gate can be assessed and injection parameters scaled to speed up mold design. Part II of the article completes the demonstration of the novel concept by applying it to a series of LCM process examples of increasing complexity.

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Characterization of textile permeability as a function of fiber volume content with a single unidirectional injection experiment

Cited by 36 publications

References 24 publications

Hybrid‐permeability model evaluation through concepts of tortuosity and resistance rate: Properties of manufactured hybrid laminate

Hybrid‐permeability model evaluation through concepts of tortuosity and resistance rate: Properties of manufactured hybrid laminate

Monitoring and modeling of part thickness evolution in vacuum infusion process

A Dimensionless Characteristic Number for Process Selection and Mold Design in Composites Manufacturing: Part I—Theory

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