Correlating the melting rates of feeds in electric melters with results of simple laboratory experiments can help evaluate melter feed additives and their effects on melting rate, and support the feed scheduling and plant operation. A recently proposed melting rate correlation (MRC) equation, relating the melting rate to melt viscosity, feed‐to‐glass conversion heat, and cold‐cap bottom temperature, was tested using data from experiments covering various feed compositions and melter operating parameters. The MRC equation is shown to reasonably represent the measured data and thus can be used to quantify how individual variables (melt viscosity, cold‐cap bottom temperature, conversion heat, melter operating temperature, and bubbling flux) affect the glass production rate.

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A recently proposed glass melting rate correlation (MRC) equation expresses an essential relationship between the melting rate and material and process variables (melt viscosity, cold‐cap bottom temperature, feed‐to‐glass conversion heat, melter operating temperature, and bubbling flux). It agreed well with data for high‐level waste (HLW) melter feeds processed in an electric melter. However, the nonlinear form and four coefficients made the original MRC somewhat cumbersome for representing existing data sets. Introducing new variables (glass melt density and depth of melt pool) makes the new MRC more broadly applicable. Also, reducing the number of coefficients to two simplifies it substantially. The simplified generalized MRC demonstrates good agreement with an extended data set encompassing additional melter feeds and melter sizes.

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Mathematical models of glass melting furnaces are incomplete in the sense that they do not estimate the rate of glass production (the rate of melting). Instead, they attempt to optimize melter efficiency and product quality for a specified production rate with other experimentally measured data. [1][2][3][4][5][6][7][8][9][10][11][12][13][14] The melting rate correlation (MRC) attempts to bypass this

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