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

Abboud, Alexander W.; Guillen, Donna Post; Pokorný, Richard

doi:10.1111/ijag.15031

Cited by 15 publications

(8 citation statements)

References 25 publications

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“…It required 30 000 iterations to reach steady state. Further details on model implementation can be found in Refs 30,33,34 . The local melting rate was estimated using Equation (), which, when averaged over cold cap surface, provides the glass production rate.…”

Section: Cold Cap Modelmentioning

confidence: 99%

Conversion degree and heat transfer in the cold cap and their effect on glass production rate in an electric melter

Ferkl

Hrma

Abboud

et al. 2022

Int J of Appl Glass Sci

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A predictive model of melt rate in waste glass vitrification operations is needed to inform melter operations during normal and off‐normal operations. This paper describes the development of a model of the cold cap (the reacting melter feed floating on molten glass in a glass melter) that couples heat transfer with the feed‐to‐glass conversion kinetics. The model was applied to four melter feeds designed for high‐level and low‐activity nuclear waste feeds using the material properties, either measured or estimated, to obtain temperature and conversion distribution within the cold cap. The cold cap model, when coupled with a computational fluid dynamics model of a Joule‐heated glass melter, allows the prediction of the glass production rate and power consumption. The results show reasonable agreement with the melting rates measured during pilot‐scale melter tests.

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Section: Cold Cap Modelmentioning

confidence: 99%

Conversion degree and heat transfer in the cold cap and their effect on glass production rate in an electric melter

Ferkl

Hrma

Abboud

et al. 2022

Int J of Appl Glass Sci

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“…High-fidelity, multiphase computational fluid dynamics (CFD) melter models have been developed and validated with experimental data. [2][3][4] Using numerical data from the CFD model, the cold-cap coverage in a continuous laboratory-scale melter was effectively predicted based on the computed plenum-temperature distribution. 5 This methodology will be valuable to the development of predictive control strategies for WTP melters by relating the cold-cap topology to measured temperatures provided by plenum thermocouples.…”

Section: Introductionmentioning

confidence: 99%

“…High‐fidelity, multiphase computational fluid dynamics (CFD) melter models have been developed and validated with experimental data 2–4 . Using numerical data from the CFD model, the cold‐cap coverage in a continuous laboratory‐scale melter was effectively predicted based on the computed plenum‐temperature distribution 5 .…”

Section: Introductionmentioning

confidence: 99%

Prediction of melter cold‐cap topology from plenum temperatures with computational fluid dynamics and machine learning

Abboud

Guillen

Christensen

2022

Int J Ceramic Engine & Sci

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A computational fluid dynamics (CFD) model of a pilot‐scale waste‐glass melter was used to generate input data for several different machine‐learning models to predict the cold‐cap coverage from plenum temperatures. This methodology could serve as useful to provide nonvisual feedback for operational control. The machine‐learning models tested include an artificial neural network (ANN), a convolutional neural network (CNN), a random forest (RF) algorithm, and a support vector machine (SVM) method. CFD simulations with randomized cold‐cap coverage were run to generate plenum‐temperature distributions. The topology of the cold cap was predicted with each method using an input layer of selected temperature locations. The ANN was used to predict the cold‐cap coverage percentage with an accuracy of 1.2%. The accuracy of the various machine‐learning algorithms was dependent on the filter resolution employed. When using a low resolution (16‐cm filter), the CNN and ANN methods produced the best accuracy, with errors of 6.98% and 6.58%, respectively. At finer levels of resolution (4‐cm filter), the RF method produced the best accuracy, with an error of 8.12%. The ANN and SVM methods required less computational time to train than either the CNN or RF methods.

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“…Modeling them mathematically also poses formidable obstacles. Models of nuclear waste glass melters and the cold cap have not yet successfully simulated the cold‐cap bottom region, mainly because of its intriguing complexity. A lack of relevant data and insufficient understanding preclude the development of plausible simplifications that would yield results correlated with technological experience.…”

Section: Introductionmentioning

confidence: 99%

“…As mathematical models of a nuclear waste glass melter demonstrated in Ref. [] the melt temperature in the melt pool under the TBL is virtually uniform and equal to T MO . This has been shown for a melter with natural convection and is a common feature of melters in which gas bubbles produce pneumatic stirring .…”

Section: Introductionmentioning

confidence: 99%

Viscosity of glass‐forming melt at the bottom of high‐level waste melter‐feed cold caps: Effects of temperature and incorporation of solid components

et al. 2019

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During the final stages of conversion of melter feed (glass batch) to molten glass, the glass‐forming melt becomes a continuous liquid phase that encapsulates dissolving solid particles and gas bubbles that produce primary foam at the bottom of the cold cap (the reacting melter feed in an electric glass‐melting furnace). The glass‐forming melt viscosity plays a dominant role in primary foam formation, stability, and eventual collapse, thus affecting the rate of melting (the glass production rate per cold‐cap area). We have traced the glass‐forming melt viscosity during the final stages of feed‐to‐glass conversion as it changes in response to changing temperature and composition (resulting from dissolving solid particles). For this study, we used high‐level waste melter feeds—taking advantage of the large amount of data available to us—and a variety of experimental techniques (feed expansion test, evolved gas analysis, thermogravimetric analyzer‐differential scanning calorimetry, X‐ray diffraction, and viscometer). Starting with a relatively low value at the moment when the melt connects, melt viscosity reached maximum within the primary foam layer and then decreased to its final melter operating temperature value. At the cold‐cap bottom—the boundary between the primary foam layer and the thermal boundary layer—where physicochemical reactions of a melter feed influence the driving force of the heat transfer from the melt to the cold cap, the melt viscosity affects the rate of melting predominantly through its effect on the temperature at which primary foam is collapsing.

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

Cited by 15 publications

References 25 publications

Conversion degree and heat transfer in the cold cap and their effect on glass production rate in an electric melter

Conversion degree and heat transfer in the cold cap and their effect on glass production rate in an electric melter

Prediction of melter cold‐cap topology from plenum temperatures with computational fluid dynamics and machine learning

Viscosity of glass‐forming melt at the bottom of high‐level waste melter‐feed cold caps: Effects of temperature and incorporation of solid components

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