Comments on ‘‘A New Method to Optimize Furnace Designs UsingDaily Flow Rates to Maximize Energy Savings in the Steady Production’’

Manoj K. Choudharyw

Owens Corning Science & Technology, Granville, Ohio 43023

The paper, ‘‘A New Method to Optimize Furnace Designs Us-ing Daily Flow Rates to Maximize Energy Savings in the SteadyProduction’’ by Feng et al.1 presents an illustration of the use ofcomputational fluid dynamics (CFD)-based modeling to changesome aspects of furnace design to improve the energy efficiencyof a glass furnace. Specifically, the paper examines the effect ofthe siege height on the return flow of glass melt from the work-ing end to the melting end. The glass coming from the workingend is cooler than the glass in the melting end and requiresheating, resulting in an increased overall energy consumption inthe furnace. The study by Feng and colleagues shows that theeffect of increasing the siege height is to reduce the amount ofreturn flow from the working to the melting end. This effect canbe understood in terms of the impact of the siege height on therelative importance of the two driving forces for glass flow,namely the ‘‘pull’’ associated with the furnace throughput andthe thermally driven buoyancy force.

Mathematical modeling-based studies are very useful inquantifying the effects of design and operational changes onthe furnace performance (e.g., energy efficiency). Some aspectsof the modeling approach used by Feng and colleagues, how-ever, need clarification in order to quantitatively assess theirfindings. The authors state that ‘‘For the furnace simulation, aNewton incompressible turbulent heat analysis was used.’’ Theyfurther state that ‘‘the turbulent nature of the glass fluids wassimulated by applying the realizable k–e model.’’ Apparently,the authors assumed the glass melt to be Newtonian and in-compressible. That is indeed the usual approach in modeling ofglass flow in furnaces. It is unusual, however, for the flow ofglass melt in a furnace to be considered turbulent. As is wellknown, turbulent flow is characterized by a high Reynolds num-ber—i.e. in turbulent flow, the inertial force acting on a fluidvolume is much larger than the viscous force. This is not likely tobe the case in a glass furnace. The authors have not providedany results on the turbulence parameters (k the turbulencekinetic energy, e the rate of dissipation of turbulence energy,or the turbulence viscosity) for one to be able to ascertain thelevel of turbulence in the furnace they have modeled. The pres-ent author also reviewed an earlier paper by Feng et al.2 to seewhether relevant information could be found there toestimate the Reynolds number and/or the level of turbulence(characterized by the ratio of turbulent viscosity and glassviscosity) in these studies. Although the earlier paper hadsome values of k, it did not have other information (e.g.,e, temperature of the glass melt) required to perform the re-quired calculations. Based on generally available knowledgeabout conditions in glass furnaces, one would expect the Rey-

nolds number to be o1—a condition not conducive to gener-ating turbulent flow.

It is not the purpose of this brief note to review the funda-mentals of turbulent flow and its modeling or to present a de-tailed review of the papers by Feng and colleagues. It appearsthough that Feng and colleagues are using the term turbulencedifferently than is commonly understood. In their 2008 paper,for example, they have provided calculated values on forwardand backward components (both in the X—or the longitudinaldirection) of turbulent velocities and they have signs attached tothese values. The k–e model that they have used in these paperscalculates the specific turbulence kinetic energy, k, which is onehalf of the sum of the time-averaged squares of the three com-ponents of the fluctuating (i.e. turbulent) velocity. It is not clear,from a fundamental perspective, as to how one would resolvethe calculated ‘‘k’’ value to the forward and backward turbulentvelocity components as Feng and colleagues have done.

It would be very helpful to the readers of Feng andcolleagues’ papers to understand their modeling approachand appraise their results if the authors could address some ofthe comments made above and provide the following details.

(1) The Reynolds number for both the melting and theworking ends. The authors may calculate these values using hy-draulic diameters of the respective sections for the characteristiclength scales. Further, they may use average temperatures in thetwo sections to calculate the characteristic viscosities and densi-ties and the average ‘‘horizontal’’ velocities for the velocity scale.

(2) The inlet conditions for k and e (i.e., the values associ-ated with the inlet velocities in the 2008 paper).

(3) The ratio of the turbulent viscosity to the glass viscosity.

The general purpose CFD software used by them and manyothers (including this author) are designed to solve a wide va-riety of CFD problems. They have provisions for modeling tur-bulence. The turbulence model equations are intended for fullyturbulent flows, with provisions to handle the viscous nature offlow in the vicinity of solid boundaries. It is always beneficial tocheck if a particular module of general purpose CFD software isrelevant for solving a specific problem.

References

1Z. Feng, D. Li, G. Qin, and S. Liu, ‘‘A New Method to Optimize FurnaceDesigns Using Daily Flow Rates to Maximize Energy Savings in the Steady Pro-duction,’’ J. Am. Ceram. Soc., 92 [10] 2459–62 (2009).

2Z. Feng, D. Li, G. Qin, and S. Liu, ‘‘Study of the Float Glass Melting Process:Combining Fluid Dynamics Simulation and Glass Homogeneity Inspection,’’J. Am. Ceram. Soc., 91 [10] 3229–34 (2008). &

D. J. Green—contributing editor

wAuthor to whom correspondence should be addressed. e-mail: manoj.choudhary@owenscorning.com

Manuscript No. 27259. Received December 16, 2009; approved February 28, 2010.

Journal

J. Am. Ceram. Soc., 93 [6] 1803 (2010)

DOI: 10.1111/j.1551-2916.2010.03757.x

r 2010 The American Ceramic Society

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