Monitoring of three-dimensional resin flow front using hybrid piezoelectric-fiber sensor network in a liquid composite molding process

Yu, Yinghong; Cui, Xiyue; Liang, Zhihong; Qing, Xinlin; Yan, Wentao

doi:10.1016/j.compscitech.2022.109712

Cited by 14 publications

(8 citation statements)

References 27 publications

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“…Lamb waves can leak into the liquid through the solid-liquid interface with a consequent energy and amplitude reduction. This property can be used to detect fiber impregnation [ 77 ]. This method, compared to the longitudinal waves method, is suitable for thick preforms thanks to the capability of guided waves to propagate over long distances.…”

Section: Measurement Methodsmentioning

confidence: 99%

“…Yu et al [ 77 ] realized a hybrid piezoelectric-fiber sensor network embedded inside a carbon fiber preform to monitor the three-dimensional resin flow front. They used PZTs for flow front monitoring in the thickness direction and Fiber Bragg Grating (FBG) sensors to monitor the flow front inside the sample.…”

Section: Measurement Methodsmentioning

confidence: 99%

“…While fiber optics with cut ends were used for flow front monitoring, FBG sensors with a Bragg grating length of 10 mm were used for temperature monitoring [ 57 ]. Yu et al [ 77 ], instead, used FBG sensors in their hybrid piezoelectric-fiber sensor network described in Section 3.3.2 to monitor resin flow front in the thickness direction through the shift of Bragg wavelength caused by contact between resin and sensors. Chehura et al [ 96 ] applied embedded fiber optics to monitor the filling stage and the cure cycle of a carbon fiber-reinforced tail cone, as the refractive index of resin is also sensitive to density variation [ 98 ].…”

Section: Measurement Methodsmentioning

confidence: 99%

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An Overview of the Measurement of Permeability of Composite Reinforcements

2023

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Liquid composite molding (LCM) is a class of fast and cheap processes suitable for the fabrication of large parts with good geometrical and mechanical properties. One of the main steps in an LCM process is represented by the filling stage, during which a reinforcing fiber preform is impregnated with a low-viscosity resin. Darcy’s permeability is the key property for the filling stage, not usually available and depending on several factors. Permeability is also essential in computational modeling to reduce costly trial-and-error procedures during composite manufacturing. This review aims to present the most used and recent methods for permeability measurement. Several solutions, introduced to monitor resin flow within the preform and to calculate the in-plane and out-of-plane permeability, will be presented. Finally, the new trends toward reliable methods based mainly on non-invasive and possibly integrated sensors will be described.

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Section: Measurement Methodsmentioning

confidence: 99%

Section: Measurement Methodsmentioning

confidence: 99%

Section: Measurement Methodsmentioning

confidence: 99%

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An Overview of the Measurement of Permeability of Composite Reinforcements

2023

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“…During resin injection, the pressure distribution within the mold changes rapidly. This phenomenon is generally monitored using point sensors drilled within the mold [51][52][53][54][55] . rGO coated fabrics can act as an attractive alternative to these sensor arrays 44 .…”

Section: Data Generated By Reduced Graphene Oxide Strain Sensorsmentioning

confidence: 99%

Graphene nanoparticles as data generating digital materials in industry 4.0

Ali

Irfan

Khan

et al. 2023

Sci Rep

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One of the potential applications of 2D materials is to enhance multi-functionality of structures and components used in aerospace, automotive, civil and defense industries. These multi-functional attributes include sensing, energy storage, EMI shielding and property enhancement. In this article, we have explored the potential of using graphene and its variants as data generating sensory elements in Industry 4.0. We have presented a complete roadmap to cover three emerging technologies i.e. advance materials, artificial intelligence and block-chain technology. The utility of 2D materials such as graphene nanoparticles is yet to be explored as an interface for digitalization of a modern smart factory i.e. “factory-of-the-future”. In this article, we have explored how 2D material enhanced composites can act as an interface between physical and cyber spaces. An overview of employing graphene-based smart embedded sensors at various stages of composites manufacturing processes and their application in real-time structural health monitoring is presented. The technical challenges associated with interfacing graphene-based sensing networks with digital space are discussed. Additionally, an overview of the integration of associated tools such as artificial intelligence, machine learning and block-chain technology with graphene-based devices and structures is also presented.

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“…Based on the Fresnel reflection, Antonucci et al 19 laid optical fibers among the stack layers to obtain the three-dimensional resin flow front location by detecting the reflected optical signal at the end of the fiber. Yu et al 20 realized a hybrid piezoelectric-fiber sensor network including piezoelectric (PZT) sensors for through-the-thickness direction monitoring and embedded Fiber Bragg Grating (FBG) sensors as local flow sensors. The results were combined as a complement of each other to estimate the three-dimensional resin flow front.…”

Section: Introductionmentioning

confidence: 99%

Unsaturated out-of-plane permeability measured with three-dimensional flow monitoring by etched optical fiber sensors

Liu,

Sousa,

Pfeiffer

et al. 2024

Journal of Composite Materials

Self Cite

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In our work, the three-dimensional flow in stacks of biaxial E-glass fiber non-crimp fabrics (NCF) and unidirectional carbon fiber layers was monitored by the etched optical fiber sensors embedded inside the fabric stack. The influence of embedding sensors with a diameter of 200 µm on the flow was experimentally illustrated and discussed. The out-of-plane permeability of the two fabric materials was estimated with a radial infusion model using the in-plane permeability values as the prior knowledge. The assumed radius of the semi-ellipsoidal flow was derived and showed a good agreement with the results obtained by the best fit of the exact solution, which provides an approximate solution that simplifies the calculation process. The asymptotic form and the modified semi-ellipsoidal inlet radius method for the case of a non-negligible radius of injection tube compared to the fabric sample thickness were verified. The uncertainties related to the unknown flow pattern near the inlet were also demonstrated. The presented results facilitate the further development and standardization of out-of-plane permeability measurement methods with embedded sensors.

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Monitoring of three-dimensional resin flow front using hybrid piezoelectric-fiber sensor network in a liquid composite molding process

Cited by 14 publications

References 27 publications

An Overview of the Measurement of Permeability of Composite Reinforcements

An Overview of the Measurement of Permeability of Composite Reinforcements

Graphene nanoparticles as data generating digital materials in industry 4.0

Unsaturated out-of-plane permeability measured with three-dimensional flow monitoring by etched optical fiber sensors

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