Numerical and experimental study of the glass flow and heat transfer in the continuous glass fiber drawing process

Chouffart, Quentin; Simon, Philippe; Terrapon, Vincent

doi:10.1016/j.jmatprotec.2015.12.017

Cited by 7 publications

(8 citation statements)

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“…In such cases, the air flow can be chaotic, and an explicit modeling for the heat transfer coefficient can be challenging. Molten glass is here considered as an opaque medium, and internal radiation is neglected [2]. Therefore radiative heat transfer is modeled through a constant effective emissivity of glass fiber surface ε.…”

Section: Nonisothermal Modelmentioning

confidence: 99%

“…These estimations correspond to experimental or numerical measurements obtained in the region where each of the contributions is dominant. As radiative and convective exchanges are dominant close to the nozzle and along the fiber, respectively, we impose two different reference temperatures, as encountered in [2,31]. By adopting the same scaling as in [19], the free-fall velocity √ gL, with gravitational acceleration g, is used as reference velocity.…”

Section: Nonisothermal Modelmentioning

confidence: 99%

“…where t is the time variable, η 0 = η(θ 0 ), h 0 = 0.42π 1/3 k a (gL) 1/6 (νR 2 0 ) −1/3 is the convective heat transfer coefficient in x = 0, ε 0 is a typical average emissivity along the fiber near the nozzle [2,31], and θ = θ 0 − θ c . The resulting dimensionless parameters are defined by the following expressions:…”

Section: Nonisothermal Modelmentioning

confidence: 99%

“…In the case of St * → 0 and St * r → 0 we recover the isothermal problem in [19], but with additional flexibility of independently varying the dimensionless drawing length . The parameter values used in this study are displayed in Table I and have been chosen according to practical applications involving molten glass [2,31]. The parameters St * r , B * , and θ * c have small variations regarding the range of inlet temperature θ 0 considered in this study.…”

Section: Nonisothermal Modelmentioning

confidence: 99%

“…Thermal drawing processes are involved in a large range of applications as diverse as the manufacture of glass [1,2] and polymer fibers [3][4][5][6], optical fibers [7,8], or more recently multimaterial fibers with advanced functionalities [9][10][11][12]. We note that filamentary structures can also be produced naturally during volcanic eruptions.…”

Section: Introductionmentioning

confidence: 99%

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Linear stability analysis of nonisothermal glass fiber drawing

et al. 2022

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The draw resonance effect appears in fiber drawing processes when the draw ratio, defined as the ratio between the take-up and the inlet velocities, exceeds a critical value. In many cases, inertia, gravity, and surface tension cannot be neglected, and a model combining all these effects is necessary in order to correctly describe the physics of the phenomenon. Additionally, it is also known that cooling can have a highly stabilizing effect on the draw resonance instability. However, a detailed analysis encompassing the effect of inertia, gravity, surface tension, and temperature is still lacking. Due to a destabilizing effect induced by geometry in the heat equation, we first show that the maximum critical draw ratio for fiber drawing can be two orders of magnitude lower than the one for the film casting problem when the heat transfer coefficient is assumed constant. By introducing a scaling making the fiber aspect ratio an independent parameter, we next show that the high value of the critical draw ratio encountered in industrial applications could be rationalized only if we consider that the heat transfer coefficient is not constant but depends on both the velocity and the cross-section area of the fiber. Within this framework, we show how the practical stability window is affected by the five control parameters: the draw ratio, the fiber aspect ratio, the inlet temperature, the convective heat transfer coefficient, and the stiffness of the non-homogeneous ambient temperature. We finally discuss the influence of radiative heat transfer on the stability.

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Section: Nonisothermal Modelmentioning

confidence: 99%