Dynamic saturation curve measurement in liquid composite molding by heat transfer analysis

Villière, Maxime; Guéroult, Sébastien; Sobotka, Vincent; Boyard, Nicolas; Bréard, Joël; Delaunay, Didier

doi:10.1016/j.compositesa.2014.11.024

Cited by 17 publications

(10 citation statements)

References 15 publications

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“…However, there are still many difficulties in the VARI process, such as the control of the resin flow, the prevention of dry spots and the delamination and residual stress that closely related to the control parameter of the process [4,5]. These flaws seriously jeopardizing the structural health cannot be easily corrected, because the trial-and-error approaches are inefficient and costly to determine suitable process parameters [6][7][8]. Therefore, it is necessary to carry out in-suit monitoring in the manufacturing process to adjust the process parameters in time to avoid the occurrence of defects.…”

Section: Introductionmentioning

confidence: 99%

Life-Cycle Monitoring of CFRP using Piezoelectric Sensors Network

Qing

Liu

Wamg

2021

Materials Research Proceedings

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Abstract. Vacuum Assisted Resin Infusion (VARI) process is suitable for manufacturing complex large-scale composite structures and has the potential for low cost and mass production. However, the inappropriate process parameters such as incomplete resin flow and the uneven cure occurred will lead to some defects such as dry spots and delamination. In the present work, the concept of Networked Elements for Resin Visualization and Evaluation (NERVE) with the piezoelectric lead-zirconate-titanate (PZT) sensors as the base unit was used to monitor the internal state of composite struture during its life-time. The capability of PZT sensors in the NERVE to monitor two important parameters during the manufacturing process including the flow front of resin and progress of reaction (POR), was investigated. The Lamb waves generated by PZT, propagating in the mold/composite, was used to measure the parameters. The resin flow front was analyzed using optical detection at the same time. The flow front position over time and the influence of the length of sensing path covered by resin were delivered. The effects of different resin cure state on Lamb signal attenuation and energy leakage were also obtained. The change of amplitude was integrated to get the POR curves, so the resin cure state could be also monitored. After the composite was demoulded, the network was used contiously to identify the artifical damages with the fused probability-based diagnostic imaging (PDI). Experimental results indicate that the NERVE has the ability to realize the full life-cycle health monitoring of composite structures.

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Section: Introductionmentioning

confidence: 99%

Life-Cycle Monitoring of CFRP using Piezoelectric Sensors Network

Qing

Liu

Wamg

2021

Materials Research Proceedings

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“…If their values or combinations are not reasonable, such as varying cooling rate and the lack of the reinforcement by the resin, this may induce the creation of porosity in the preform and affect the final properties of the composite. [ 6–8 ] These problems cannot be easily corrected because trial‐and‐error approaches to determine a suitable cure cycle are inefficient and costly. [ 9 ] Therefore, it is necessary to use real‐time monitoring technology to monitor the resin flow and cure state, so these process parameters can be accordingly adjusted to reduce defects in time.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of resin flow front and degree of cure in vacuum‐assisted resin infusion process using multifunctional piezoelectric sensor network

Xiao

Zhu

et al. 2020

Polymer Composites

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Vacuum assisted resin infusion (VARI) has attracted more and more attentions in the aerospace field and the monitoring of the process variables has been one of the milestones for most aerospace companies. This study focuses on monitoring the flow front and curing degree of the resin in‐suit using a piezoelectric (PZT) sensor network. In the resin transfer stage, the propagation characteristics of Lamb waves were extracted from different paths to characterize the resin flow front, and the quadratic regression models of three variables were established. In the resin cure stage, the leaky Lamb waves and electromechanical impedance based on PZT sensors were simultaneously adopted to monitor the degree of cure of the resin globally and locally, respectively. The differential scanning calorimeter analysis was carried to see the compatibility among different methods for the curing degree. Experimental results demonstrated that it was feasible to monitor the flow front and curing degree of resin in VARI process using Lamb waves and electromechanical impedance based on a multifunctional piezoelectric sensor network.

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“…the amount of air in the preform. These methods involve electrical conductivity, 22,31 thermal conductivity, 32,33 ultrasound, 34–36 magnetic resonance imaging, 37 flow-rate comparison, 38,39 and overall light transmission. 40,41 All but the latter could be theoretically performed on carbon reinforcements, although only one of the above studies presented quantitative measurements for carbon.…”

Section: Introductionmentioning

confidence: 99%

Optical measurement of voids in situ during infusion of carbon reinforcements

Lystrup

George

Zobell

et al. 2020

Journal of Composite Materials

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Liquid composite molding (LCM) is growing in importance as an alternative to traditional prepreg-autoclave methods for manufacture high-performance composites. The most significant roadblock to industry’s implementation of LCM is the usually higher void content compared with prepreg processing. One tool for reducing void levels in LCM involves optimization of flow velocity, which requires models to be developed to describe void formation at a given velocity. To help solve this problem, the following research illustrates the first known method for optical void measurement in situ during infusion in a carbon fiber reinforcement. Similar to previous studies on glass fiber, this work utilizes fluorescent dye and a digital camera to produce sufficient contrast and resolution for image analysis. Visible bubbles are photographed against the opaque carbon fiber background. An automated method of image analysis is outlined, which was used to analyze 230 images for three different flow orientations of a single fabric, producing the highest amount of experimental data seen so far on in situ void measurement. The resulting data identifies a minimum velocity threshold for minimal macro-void formation. The resultant void characterization framework will better enable optimization of LCM processing for high-performance composites based on carbon reinforcements.

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Dynamic saturation curve measurement in liquid composite molding by heat transfer analysis

Cited by 17 publications

References 15 publications

Life-Cycle Monitoring of CFRP using Piezoelectric Sensors Network

Life-Cycle Monitoring of CFRP using Piezoelectric Sensors Network

Monitoring of resin flow front and degree of cure in vacuum‐assisted resin infusion process using multifunctional piezoelectric sensor network

Optical measurement of voids in situ during infusion of carbon reinforcements

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