Exploring equivalence of information from dielectric and calorimetric measurements of thermoset cure—a model for the relationship between curing temperature, degree of cure and electrical impedance

Kazilas, Mihalis; Partridge, Ivana K.

doi:10.1016/j.polymer.2005.05.005

Cited by 34 publications

(16 citation statements)

References 20 publications

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“…However, the tunneling processes inside the aliphatic polymer composites seem to be dominated by another mechanism which lowers the sample's conductivity to a constant value. The decreasing mobility of the suspended ions with increasing crosslinking density would explain this behaviour [30,31], but more experiments are necessary in order to validate this assumption.…”

Section: In Situ Raman and Conductivity Measurements During The Curinmentioning

confidence: 99%

Combined Raman and dielectric spectroscopy on the curing behaviour and stress build up of carbon nanotube–epoxy composites

Vega

Kovacs

Bauhofer

et al. 2009

Composites Science and Technology

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Section: In Situ Raman and Conductivity Measurements During The Curinmentioning

confidence: 99%

Combined Raman and dielectric spectroscopy on the curing behaviour and stress build up of carbon nanotube–epoxy composites

Vega

Kovacs

Bauhofer

et al. 2009

Composites Science and Technology

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“…2). The purpose of dielectric sensing was to measure the change in the imaginary impedance maximum, which can be correlated to the chemical conversion state of the material [29][30][31]. The data obtained were used for a correlation with chemical conversion using the cure kinetics model presented in [27].…”

Section: Dielectric Sensingmentioning

confidence: 99%

“…The progression in chemical conversion appears in the kinetics part of the IIM response. This contribution can be de-convoluted using the methods proposed in [30,31]. Both methods utilise the time derivative of the IIM signal and are performed in analogy to the integration of the DSC reaction peak area; in [31], the d(IIM)/dt is integrated using an appropriate baseline [33].…”

Section: Residual Stress Determinationmentioning

confidence: 99%

“…Both methods utilise the time derivative of the IIM signal and are performed in analogy to the integration of the DSC reaction peak area; in [31], the d(IIM)/dt is integrated using an appropriate baseline [33]. Kazilas and co-authors used regression analysis to estimate parameters in a model function of that includes the conversion rate as follows [30]:…”

Section: Residual Stress Determinationmentioning

confidence: 99%

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In-situ Curing Strain Monitoring of a Flat Plate Residual Stress Specimen Using a Chopped Stand Mat Glass/Epoxy Composite as Test Material

et al. 2015

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The curing stresses in a newly proposed bi-axial residual stress testing configuration are studied using a chopped strand mat glass/epoxy specimen. In-situ monitoring of the curing is conducted using dielectric and fibre Bragg grating sensors. It is confirmed that a bi-axial residual stress state can be introduced in the specimens during curing and a quantification of its magnitude is presented. An alternative decomposition method used for converting the dielectric signal into a material state variable is proposed and good agreement with models found in the literature is obtained. From the cure cycles chosen it is suggested that any stress build up in the un-vitrified state is relaxed immediately and only stress build up in the vitrified state contributes to the residual stress state in the specimen.

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“…The sensors of this type are denoted as Long Period Grating Fiber Sensor (LPGFS). This paper presents results obtained in simulation of an unperturbed LPG transmission spectrum attenuation bands and shifting induced by a composite material internal mechanical and thermal stress, the optic fiber being embedded in the matrix of the investigated composite 1,[11][12][13] . The composite internal mechanical and thermal stresses are the result of environment mechanical and thermal loads upon the composite material.…”

Section: Introductionmentioning

confidence: 99%

Numerical analysis of a smart composite material mechanical component using an embedded long period grating fiber sensor

et al. 2015

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Results obtained by FEM analysis of a smart mechanical part manufactured of reinforced composite materials with embedded long period grating fiber sensors (LPGFS) used for operation monitoring are presented. Fiber smart reinforced composite materials because of their fundamental importance across a broad range of industrial applications, as aerospace industry. The main purpose of the performed numerical analysis consists in final improved design of composite mechanical components providing a feedback useful for further automation of the whole system. The performed numerical analysis is pointing to a correlation of composite material internal mechanical loads applied to LPGFS with the NIR absorption bands peak wavelength shifts. One main idea of the performed numerical analysis relies on the observed fact that a LPGFS embedded inside a composite material undergoes mechanical loads created by the micro scale roughness of the composite fiber network. The effect of this mechanical load consists in bending of the LPGFS. The shifting towards IR and broadening of absorption bands appeared in the LPGFS transmission spectra is modeled according to this observation using the coupled mode approach.

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Exploring equivalence of information from dielectric and calorimetric measurements of thermoset cure—a model for the relationship between curing temperature, degree of cure and electrical impedance

Cited by 34 publications

References 20 publications

Combined Raman and dielectric spectroscopy on the curing behaviour and stress build up of carbon nanotube–epoxy composites

Combined Raman and dielectric spectroscopy on the curing behaviour and stress build up of carbon nanotube–epoxy composites

In-situ Curing Strain Monitoring of a Flat Plate Residual Stress Specimen Using a Chopped Stand Mat Glass/Epoxy Composite as Test Material

Numerical analysis of a smart composite material mechanical component using an embedded long period grating fiber sensor

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