The 2024 AGC‐Michael Cable Memorial Lecture: Progress and challenges in decarbonization of industrial glass melting

For the automatic control of glass quality in glass production, the relation between process variable and product or glass quality and process conditions/process input parameters must be known in detail. So far, detailed 3-D glass melting simulation models were used to predict the effect of process input variables, such as fuel consumption and fuel distribution, load and load distribution, and electrical boosting, on the flow pattern (residence times, short cut flows), temperature distribution and redox state of the glass in the furnace. For feeder control, the main objectives are stable temperature and temperature uniformity in the spout section of the feeder just before the glass melt is delivered to the forming process. However, computations of detailed 3-D simulation models are very time-consuming: one steady state simulation of a complete furnace including refiner(s) typically takes about a day. This time demand indicates that the currently used detailed 3-D simulation models are not suitable for rigorous (CFD) model based Model Predictive Control (MPC). To make the 3-D simulation models suitable for control purposes, simulation tools that are much faster than real time with still a high level of reliability are now developed. These fast simulation tools (GPS: Glass Process Simulators) open up a wide variety of applications of glass furnace models: process monitoring, what-if scenarios and model based predictive control (MPC) of temperatures or glass melt quality or redox/color. Now we realized time-transient simulations with GPS for feeders, which are about 10000 times as fast as real time. This paper will show the capability of an MPC that is based on fast GPS to control temperature and temperature uniformity of one of the feeders connected to an emerald-green container glass furnace.

Modeling of evaporation processes in glass melting furnaces

Decomposition analysis of the change of energy intensity of manufacturing industries in Thailand

Melting and primary fining represent the most essential steps in the glass manufacturing process. Electric boosting and bubbling are common methods used to optimize these processes by improving the product quality and energy efficiency. However, a structured overview of their impacts on the operation of the total melting furnace has not previously been published. The present paper provides a thorough comparison of these technologies applied to an industrial melting furnace, including the effects on temperatures, melt flow patterns, glass quality, as well as the heat fluxes and process efficiency. In this work, extensive numerical simulations were performed. Unlike other studies described in the literature, a validated CFD model of exceptionally high accuracy was employed. Furthermore, the entire melting furnace was considered, such that the glass tank was coupled to detailed simulations of the turbulent gas-phase combustion. A novel method for combustion modeling in glass manufacturing was applied, and user-defined functions supported an analysis of glass quality. Substantial differences were observed between the furnaces with electric boosting and bubbling. For the first time, interrelated effects could be described in detail, providing a comprehensive overview of the entire operation. Based on the presented results, the targeted use of both electrodes and gas nozzles is suggested for future melting processes.

A three-dimensional numerical methodology to simulate the effect of electric boosting on glassmelt circulation and heat transfer in a glass melting furnace is presented. Due to a small, characteristic Hartmann number, the ponderomotive forces in the momentum equation were neglected. The voltage and electric current fields within the melt were determined by solving real and imaginary parts of the electric potential. The Joulean heat dissipation was determined and coupled to the energy equation of the melt. Other relevant processes, such as batch-melting and heat transfer from combustion space, were integrated into a system model. Merits of electric boosting were examined by obtaining some representative results and comparing model predictions with and without electric boosting.

Nowadays it is hard to re-valuate the importance of glass and glass products. Glass is used in construction, medicine, food packaging and chemical industry. As those domains continue to develop, they require even higher quality of glass products. Glass production plant is a complex facility that consists of multiple premises used at various stages of glassmaking: storage, batch preparation, glass melting (glass furnace) and product packaging. Glass furnace is a complex technological object. Chemical and physical transformations in the furnace occur simultaneously along with three types of heat exchange for both gas and liquid media. Glassmaking process is characterized by two interdependent parameters that affect the quality of glass products. An efficient process control system is needed to ensure the uninterrupted operation of a glass furnace at given process conditions in order to reach the desired quality of glass products. Development of the efficient control system is based on experimental data. Collecting of glass furnace data through experiment would certainly lead to unacceptable production losses: either due to production rejects or incidents. Usage of glass furnace model is the only alternative to avoid production losses during glassmaking process control system development. This article is dedicated to creation of glassmaking model by combining models of numerous physical and chemical processes that occur in glass furnace. Among the examined physicochemical phenomena are: fuel burning, glass melt and gas medium hydro- and gas dynamics, glass furnace heat exchange. Glassmaking physical reductions and assumptions, initial and boundary conditions are also described in the paper. Keywords: glass production, mathematical model, system of Navier-Stokes equations, batch melting, the equation of radiative transfer

Glass manufacturing is an energy-intensive process with high demands on product quality. The wide usage of glass products results in a high end-product diversity. In the past, many models have been developed to optimize specific process steps, such as glass melting or glass forming. This approach presents a tool for the modeling of the entire glass manufacturing process for container glass, flat glass, and glass fibers. The tool considers detailed bottom-up energy and material balance in each step of the processing route with the corresponding costs and CO2 emissions. Subsequently, it provides the possibility to quantify optimization scenarios in the entire glass manufacturing process in terms of energy, material and cost flow efficiency.

The earliest refractories for containing melts were quarried from natural deposits of limestone and dolomite. Today these two carbonate rocks serve important roles in the production of metal contact refractories. Early refractories for glass melting on the other hand were manufactured from clays and claystones. These materials are also still used extensively for the batch melting of glasses that are hand formed or blown into art and tableware. Glass contact refractories for the continuous (tank) melting of glass are often fired, cast into large shapes, and arranged in a soldier course which constitutes the sidewalls of the glass tank.In this brief exposition of refractories technology and allied research, the articles by B. Brezny, T.F. Vazza and T.A. Leitzel, and by T.S. Busby cover materials development, selection, and properties of the systems which have evolved for the efficient melting of steels and glasses. As such they relate to extremes of technological flux in the processes for the manufacture of steel and glass, respectively.The continuous melting of large volumes of commercial glasses has been carried out in tanks equipped with reverberators for at least 70 years. The basic design of the overall system and of many of the glass fabrication machines for pressing, rolling, and blowing the glass has been constant since World War I. Only the introduction of the float glass method, the famous Pilkington process, for the production of flat glass, has interrupted the slow quiet progress in the technology of continuous glass making.

Glass manufacturing is an energy-intensive process in which oxy-fuel combustion can offer advantages over the traditional air-blown approach. Examples include the reduction of NOx and particulate emissions, improved furnace operations and enhanced heat transfer. This paper presents a one-dimensional mathematical model solving mass, momentum and energy balances for a planar oxygen transport membrane module. The main modelling parameters describing the surface oxygen kinetics and the microstructure morphology of the support are calibrated on experimental data obtained for a 30 μm thick dense La0.6Sr0.4Co0.2Fe0.8O3-δ (LSCF) membrane layer, supported on a 0.7 mm porous LSCF structure. The model is then used to design and evaluate the performance of an oxygen transport membrane module integrated in a glass melting furnace. Three different oxy-fuel glass furnaces based on oxygen transport membrane and vacuum swing adsorption systems are compared to a reference air-blown unit. The analysis shows that the most efficient membrane-based oxyfuel furnace cuts the energy demand by ~22% as compared to the benchmark air-blown case. A preliminary economic assessment shows that membranes can reduce the overall glass production costs compared to oxyfuel plants based on vacuum swing adsorption technology.

Integration of oxygen transport membranes in glass melting furnaces

In the glass manufacturing industry, electric melting would greatly improve the energy efficiency and reduce the pollution emission, which agrees with the target of peak carbon and carbon neutrality. In this work, electric boosting system is introduced into float glass furnace, and the influence of varied electrodes positions on glass melting process is investigated. The glass temperature and velocity fields of glass melting tank are obtained using numerical modeling. According to the temperature and velocity fields, the glass trajectories at glass melting tank are tracked, and the residence time distribution and quality indexes of glass melt are statistic as well. Ultimately, the evaluation method is proposed to predict the glass quality and melting efficiency of glass furnace, which is based on the quality indexes of critical particles and longest residence time of glass melt. The accelerated batch melting process and stable convection flow are obtained as the electrodes are installed under batch blanket. Furthermore, the improved glass quality and melting efficiency of glass furnace is obtained. The study is expected to promote the application and optimization of electric boosting system in large‐scale float furnace, which would accelerate the use of clean energy in glass manufacturing industry.

This presentation shows the advantages of re-melting post-consumer glass, but also the potential risks of using contaminated cullet in the raw material batch of glass furnaces (e.g. container glass furnaces). As an example of potential advantages: increasing the cullet % in the batch of an efficient end-port fired regenerative container glass furnace from 65 up to 75% decreased the specific energy consumption from 3.95 MJ/kg molten glass to 3.8 MJ/kg and reduced the direct CO2 emissions with 31 grams per kg glass. Additional, lower indirect CO2 emissions can be taken into account, since less primary raw materials have to be applied, saving fossil energy in raw material synthesis (e.g. synthetic soda production). Waste glass has to be sorted and prepared in dedicated cullet recycling (treatment) plants (CTP) to meet the strict quality standards often expressed in maximum mass fraction of ceramics, stones, china, metal (ferro & non-ferro) and color mismatches that can still be accepted. But, also the presence of organic components (fats, oils, sugar, food residues,..) has to be controlled to avoid production or glass color problems. Contamination of cullet may lead to: 1. Glass quality problems: inclusions or color changes; 2. Glass melting disturbances by foaming or limited heat transfer into melt; 3. Glass furnace lifetime, by drilling of melts of metals, present in the cullet. The most important problems today are related to the presence of glass ceramics in the post-consumer waste glass and the variable amount of different colors in the glass cullet or fluctuating contamination by organics. Even small pieces of china or glass ceramics in the cullet, with sizes less than 5 mm, may end as glass defects in glass products. Larger pieces of glass ceramics may even lead to severe interruptions in the gob formation process, due to problems with cutting of the gobs with high viscous inclusions. In modern cullet treatment plants most ferro- and non-ferro metals are rather effectively removed. Glass-ceramics are very difficult to distinguish from normal soda-lime-silica glass, because color and transparency can be almost the same. Specific techniques have to be applied to detect glass-ceramic pieces in the cullet based on X-Ray absorption, X-Ray fluorescence, Hyper-spectral Imaging or UV techniques. Such systems are recently applied in modern waste glass treatment plants in Europe, delivering recycling cullet to the glass industry. This paper will show the glass defects related to the presence of glass-ceramics and the typical compositions of these inclusions (often present as cord or big knots). Organic materials can pyrolize within the batch blanket to form carbon rich residues. Carbon or cokes can react with sulfates in the batch and will cause formation of sulfides. A high level of sulfides in the batch (instead of sulfate) will jeopardize the fining process, may cause changes in fining onset temperature, may cause foaming around the batch blanket, or may lead to chemically reduced glass or even amber cords. The process of radiant heat transmission in the melt will change with a variation of the oxidation state of the melt (redox state of batch & cullet). Examples of glass defects caused by metal contamination in the batch will be shown. The composition of the metal inclusions (glass defects) in the glass product may be very different from the composition of the original contamination, causing the defect. An example is metallic aluminum that leads to silicon inclusions in the glass. Nickel sulfide can be formed by pollution of the glass melt by stainless steel flakes. Liquid metals are very aggressive towards the refractory bottom materials of the tank. A droplet of molten lead for instance will drill a hole in the refractory layers: downward drilling. The presentation will show the relation between glass defects and their origin in contaminated cullet and the mechanism of defect formation or defect conversion.

Scientific and technological challenges of industrial glass melting

Glass furnaces represent a continuous challenge for CFD simulations, which is attributed to the complex description of multiple phases: the turbulent gas phase, raw materials from a solid glass batch and the laminar liquid phase of the glass melt. Prevalence of unsuitable oxy-fuel combustion models, like the eddy-dissipation model, and the lack of advanced coupling methods for the coupling of combustion chamber and glass tank domains have been identified as research gaps in glass furnace simulations. These are tackled in a 3D CFD simulation model for an oxy-fuel glass furnace with electric boosting by introducing two significant improvements compared to previous approaches: (1) The partially-premixed steady diffusion flamelet model in combination with a skeletal25 reaction mechanism was used for combustion modelling. (2) An advanced iterative coupled simulation method is presented, which introduces damping of the solution and a rigorous termination condition. By employing the presented models, the respective temperatures in the combustion chamber and the glass tank were predicted within less than 1.93% and 3.81% of the experimental data.

Redox state is one of the most important factors that affect color of glasses. Recently, optical properties and redox state of the glass melts have been studied at TNO by A.J. Faber [1]. Spectral measurements up to 4 {micro}m into the infrared region were taken. The focus of similar studies [2] was on the redox state of iron. In glassware production, the control of color is mainly dependent upon the experience of the operators. When the color varies due to changes in processing conditions, batching or furnace contamination, usually little can be done but to scrap the entire batch. This can result in significant down time and waste of energy to melt and refine the glass. For small glass companies, detecting out-of-specification color variation early in the melting process means savings on labor and energy costs. In larger color glass operations, early detection may provide means to correct or save the batch. Monitoring the redox state of the glass melt can be used to effectively control the quality of glass products. An in-line redox sensor has been tested in industrial environment [3]. Thermal emission spectroscopy is a non-contact, real-time sensing technique. The collection of a spectrum takes only a few seconds or less. This may allow on-line analysis of the glass melt or hot glass products. For a specific glass product, a series of spectra with different processing parameters could be collected and analyzed. The sensing system would be able to detect a deviation from the normal conditions and signal the operator a change has occurred. The primary goal of this GPLUS effort is to find a practical solution for color monitoring. In this project, we proposed to conduct initial experiments of spectral characterization of colored glasses from the designated glass industry members of the Society for Glass Science and Practices. The work plan contained three stages: (1) Obtain glass samples and use spectroscopy analysis at ORNL to measure basic spectral characteristics of various glass products; (2) collect emission spectra of the glasses using single-point spectrometers (UV to 2.5 microns) from glass melts; (3) Using a spectral imaging device (3-5 microns) at ORNL to obtain 2D hyper-spectra images to evaluate the emission of glass melts.