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

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

Abstract 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 op...

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Bibliographic Details
Main Authors: Alexander W. Abboud, Donna P. Guillen, Bailey A. Christensen
Format: Article
Language:English
Published: Wiley 2022-07-01
Series:International Journal of Ceramic Engineering & Science
Subjects:
artificial neural network
computational fluid dynamics
convolutional neural network
glass waste vitrification
machine learning
random forest
Online Access:https://doi.org/10.1002/ces2.10134

Internet

https://doi.org/10.1002/ces2.10134

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