A methodology to reduce the computational cost of transient multiphysics simulations for waste vitrification

Abboud, Alexander W.; Guillen, Donna Post

doi:10.1016/j.compchemeng.2018.03.027

Cited by 11 publications

(17 citation statements)

References 32 publications

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“…The melt pool surface area is approximately 1.2 m 2 (1.372 m × 0.864 m). The main difference between this and previous models, which were developed to characterize the bubbling flow in the melt pool, is that the outer regions of the melter consisting of refractory, insulation, and cooling layers are included in this model. Figure A shows the melter layout with labeled regions, including vertical bubbler and thermocouple locations.…”

Section: Methodsmentioning

confidence: 99%

“…The plenum is assumed to be well mixed so that the variation of gas species concentrations in the plenum is minor; no trace particulate matter is considered, so the scattering coefficient is set to zero. Further details and governing equations can be found in a previous paper authored by Abboud and Guillen . The cold cap here is modeled as a rigid, solid slab of constant thickness floating on the glass pool, with four vent holes of equal diameter directly above each bubbler.…”

Section: Methodsmentioning

confidence: 99%

“…The insulation of the upper portion of the melter is open to the environment, and a heat‐loss coefficient for the buoyancy‐driven heat transfer from a heated vertical plate was applied to the sidewalls, and a coefficient for a horizontal heated plate applied to the lid. This is an improvement from the prior treatment, in which the refractory was not modeled, and a simpler heat‐loss expression was used . Heat‐transfer coefficients for the natural‐convection heat loss from vertical and horizontal external surfaces are calculated from the following expressions as functions of the Rayleigh number, Ra, and Prandtl number, Pr

h_{vert} = \frac{k}{L} N u_{L} = \frac{k}{L} {(}{, 0.825 + \frac{0.387 R a_{L}^{1 false/ 6}}{{(][, 1 = {false(0.492 false/ P r false)}^{9 false/ 16})}^{8 / 27}})}^{2}

h_{horz} = \frac{k}{L} N u_{L} = \frac{k}{L} R a_{L}^{1 / 4} .

…”

Section: Methodsmentioning

confidence: 99%

“…Due to the high viscosity of the glass, the number of bubbles did not change significantly between cases as the bubbling rate changed. The y ‐coordinate value is capped slightly below the top of the liquid surface to eliminate numerical issues of the momentum source extending too far into the plenum . In addition, a sine wave is applied to the curve, rather than a constant value to mimic localized bubbles rising as

S_{mod} = 0.5 \sin false(32 y + 16 t false) + 0.5

…”

Section: Methodsmentioning

confidence: 99%

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Effect of cold cap coverage and emissivity on the plenum temperature in a pilot‐scale waste vitrification melter

Abboud

Guillen

Pokorný

2020

Int J of Appl Glass Sci

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Integrated computational fluid dynamics (CFD) models are being developed to model the complex physics occurring within the high‐level waste melter for vitrification of legacy tank waste at the Hanford site. This study presents a validation of the integrated CFD model by using data from two experimental runs in a pilot‐scale melter. While the model uses several simplifying assumptions (such as constant heat sinks from a cooling jacket and inleakage of ambient air, steady state feed‐to‐batch conversion heat, and a cold cap model with a simplified shape), it closely predicts the molten glass (1150°C and 1175°C) and plenum temperatures (550°C) obtained from thermocouples during two pilot‐scale tests, with an average cold cap coverage of 80%. Additional simulations were performed to explore the sensitivity of the predicted plenum temperatures to variations in cold cap coverage (fraction of melt surface covered by the glass batch) and batch emissivity. The plenum temperature was found to be in the range of 606°C when cold cap coverage decreased from 95% to 70%. Cold cap emissivity had a smaller effect, increasing the plenum temperature by as much as 179°C when cold cap emissivity increased from 0.2 to 0.8. Maintaining a high cold cap coverage without overfeeding is important for a sustained melter operation with high glass throughput. This work provides a tool for achieving that goal in terms of correlating the plenum temperature with the cold cap coverage.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

h_{vert} = \frac{k}{L} N u_{L} = \frac{k}{L} {(}{, 0.825 + \frac{0.387 R a_{L}^{1 false/ 6}}{{(][, 1 = {false(0.492 false/ P r false)}^{9 false/ 16})}^{8 / 27}})}^{2}

h_{horz} = \frac{k}{L} N u_{L} = \frac{k}{L} R a_{L}^{1 / 4} .

…”

Section: Methodsmentioning

confidence: 99%

S_{mod} = 0.5 \sin false(32 y + 16 t false) + 0.5

…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Effect of cold cap coverage and emissivity on the plenum temperature in a pilot‐scale waste vitrification melter

Abboud

Guillen

Pokorný

2020

Int J of Appl Glass Sci

Self Cite

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show abstract

“…Because of the differences in governing equations in gas space and in molten glass, these subdomains are usually solved independently and then iteratively coupled using boundary conditions such as Equations () and (). To avoid the computational cost of iteration, attempts have also been made to develop fully coupled models that simulate all regions in a single domain, or at least reduce the number of iterations by providing improved estimates on the boundary heat fluxes . Both of these methods add other complexities, and do not significantly improve the computational speed.…”

Section: Heat Transfer Modelingmentioning

confidence: 99%

Modeling batch melting: Roles of heat transfer and reaction kinetics

et al. 2019

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Development of mathematical models of heat and mass transfer in glass‐melting furnaces began in the 1970s and progressed rapidly with advances in sophisticated experimental/numerical techniques and increasing computational power. Today, practically all newly built or rebuilt furnaces are optimized with these models to meet stringent quality requirements, reduce the unit costs of manufacturing, or control emissions. One remaining hurdle is to model the batch‐to‐glass conversion accurately enough to reliably assess the glass production rate. This article summarizes two key aspects of the batch‐conversion modeling—the heat transfer and the kinetics of conversion—and reviews the current state‐of‐the‐art approaches to simulating them. We critically examine the advantages of the commonly used heat transfer approach, but also explain that its predictive capabilities are significantly restricted by the dependence of batch thermal properties on the time‐temperature history. We argue that kinetic approaches to the batch‐conversion modeling would offer a significant improvement when coupled with the heat transfer approach. Finally, we summarize key areas requiring further research on the way toward a realistic model of the batch blanket.

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Sensitivity study of forced convection bubbling in a transparent viscous fluid as a proxy for molten borosilicate glass

Guillen

Abboud

2019

Annals of Nuclear Energy

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A methodology to reduce the computational cost of transient multiphysics simulations for waste vitrification

Cited by 11 publications

References 32 publications

Effect of cold cap coverage and emissivity on the plenum temperature in a pilot‐scale waste vitrification melter

Effect of cold cap coverage and emissivity on the plenum temperature in a pilot‐scale waste vitrification melter

Modeling batch melting: Roles of heat transfer and reaction kinetics

Sensitivity study of forced convection bubbling in a transparent viscous fluid as a proxy for molten borosilicate glass

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