|Title||Impact of High-Emissivity Coatings on Process Furnace Heat Transfer|
|Contributor||Denison, M.; Oliver, J.|
|Spatial Coverage||Houston, Texas|
|Subject||2014 AFRC Industrial Combustion Symposium|
|Description||Paper from the AFRC 2014 conference titled Impact of High-Emissivity Coatings on Process Furnace Heat Transfer by B. Adams.|
|Abstract||This paper examines the theory behind the enhanced heat transfer, applications where such heat transfer is desirable, approaches for simulating the effects of high emissivity coatings, and field results from furnaces which have installed one such coating. For gas-fired furnaces, normal furnace refractories tend to reflect a majority of arriving energy back into the furnace flue gas at the same spectral wavelength at which it is emitted from the flue gas. This energy is then again absorbed by the flue gas, limiting the amount of energy transferred to the process (tubes or materials). High emissivity coatings on furnace walls absorb more of the incident radiant energy and re-emit this energy across the wavelength spectrum, including emission through transparent windows in the spectrum. This spectral redistribution of emitted energy allows more radiant energy to pass through the flue gas and be transferred to the process surface. Simulation of this process requires spectral based heat transfer models which can represent the spectral absorption bands and transparent windows in the flue gas. This is accomplished using a Spectral-Line-Weighted (SLW) model with multiple grey gases. CFD simulations of a millisecond furnace process furnace shows that changing the refractory emissivity from 0.4 to 0.9 resulted in negligible differences when using only a grey gas model. When the same change was made using a spectral gas property model, the radiant furnace efficiency increased by two percent and the arch temperature decreased by 30 °C. Simulating this behavior is helpful when evaluating adjustments to furnace operation, for example when changing from a liquid to gas process feedstock. Data from successful applications of the Emisshield high emissivity coating technology in a glass furnace and petrochemical furnace will be presented showing enhanced heat absorption, increased production and lower fuel usage.|
|Rights||No copyright issues exist.|
AFRC 2014 Industrial Combustion Symposium Impact of High-Emissivity Coatings on Process Furnace Heat Transfer Bradley Adams, Martin Denison Reaction Engineering International email@example.com 801-364-6925 x18 John Olver Emisshield firstname.lastname@example.org Abstract High emissivity coatings have been shown to enhance heat transfer in high temperature process furnaces. This paper examines the theory behind the enhanced heat transfer, approaches for simulating the effects of high emissivity coatings, simulation results evaluating the impact of high emissivity coating in a pyrolysis furnace, and field results from an industrial furnace where one such coating from Emisshield, Inc. was installed. High emissivity coatings on furnace walls absorb incident radiant energy and re-emit this energy across the wavelength spectrum, including emission through transparent windows in the spectrum. This spectral redistribution of emitted energy allows more radiant energy to pass through the flue gas and be transferred to the process surface. Simulation of this process requires spectral based radiation models which can represent the spectral absorption bands and transparent windows in the flue gas. This is accomplished using a Spectral-Line-Weighted (SLW) model. CFD simulation of a pyrolysis furnace showed that changing the refractory emissivity from 0.4 to 0.9 resulted in negligible differences when using only a grey gas model. When the same change was simulated using a spectral gas property model, the radiant furnace efficiency increased by 1.5% and the arch temperature decreased by 29 °C. Simulating this behavior is helpful when evaluating adjustments to furnace operation, for example when changing from a liquid to gas process feedstock. Data from successful applications of a high emissivity coating technology in a glass melting furnace showed improved fuel savings of 7-8% due to more efficient heat transfer. Introduction High temperature process furnaces are used in a variety of industrial processes. A key to process efficiency and throughput is efficient heat transfer from flames to the process material or process tubes. One technology that has been shown to enhance heat transfer in high temperature process furnaces is high emissivity coatings. These coatings work as follows. For gas-fired furnaces, normal furnace refractories tend to reflect a majority of arriving energy back into the furnace flue gas at the same spectral wavelength at which it is emitted from the flue gas. This energy is then again absorbed by the flue gas, limiting the amount of energy transferred to the process (tubes or materials). High emissivity coatings on furnace walls absorb more of the incident radiant energy and re-emit this energy across the wavelength spectrum, including emission through transparent windows in the spectrum. This spectral redistribution of emitted energy allows more radiant energy to pass through the flue gas and be transferred to the process surface. AFRC 2014 Industrial Combustion Symposium Figure 1 illustrates the difference in radiant emissive power between the full blackbody spectrum and the absorption/emission bands in combustion gases. Radiation that is emitted in the combustion gases bands, and then reflected from a low emissivity surface back into the gases, will be reabsorbed by the gases. Radiation that can be absorbed by a high emissivity surface and re-emitted in a manner that more closely resembles the full blackbody spectrum will more efficiently transmit radiation between the gas absorption bands. Figure 1. Emissive power spectrum showing blackbody behavior compared to absorption/emission bands from combustion gases. Figure 2 illustrates the dependence of emissive power on different surface emissivities at a specified temperature. The blackbody surface is represented by an emissivity of 1.0. This is the most efficient emitter. A surface with an emissivity of 0.9 (say, a surface coated with a high emissivity coating) provides a relatively good approximation of the blackbody emission. A more typical surface emissivity of 0.4 from standard refractory or batting materials is a much less efficient emitter. Thus a typical surface not only reflects much of the arriving radiant energy back to the gases at wavelengths subject to absorption, but also emits what energy is absorbed on the surface less efficiently. High emissivity technology developed by NASA to protect the space shuttle during re-entry was licensed to Emisshield, Inc., which developed a family of high emissivity coatings having service temperatures of 1700°C and above. EMISSHIELD® is a registered trademark for coatings manufactured by Emisshield, Inc., and is covered by U.S. Patent 6,921,431. Figure 3 illustrates surface emissivity as a function of temperature with and without the Emisshield high emissivity surface coating. The coating emissivity remains nearly constant with changed wall temperature, whereas the emissivity of the uncoated refractory surface decreases with increasing temperature. 05000100001500020000250003000035000016wavelength μmEMISSIVE POWER W/(m2.μm) 2.7 4.3 6.3 Absorption wavelengths in combustion gases Full blackbody spectrum AFRC 2014 Industrial Combustion Symposium Figure 2. Emissive power spectrum comparing blackbody behavior to surfaces with lower emissivities. Figure 3. Refractory surface emissivity as a function of temperature with and without the Emisshield surface coating. Simulation Approach Assessment of the effectiveness of the high-emissivity coating requires a modeling approach capable of replicating the spectral radiation effects described above. REI's ADAPT CFD software was used in this study. The characteristics of this software have been previously described [Adams et al., 2007, Tang et al., 2009]. ADAPT capabilities include: • localized mesh refinement to capture burner geometry details and near-burner mixing; • discrete ordinates method with SLW gas property model for solving radiative transfer equation; • reduced chemical kinetic mechanisms with in-situ adaptive tabulation (ISAT) to compute finite rate chemistry; 0350000246810121416μmEMISSIVE POWER W/(m2.μm) Black Body ε =1 0 0.2 0.4 0.6 0.8 1 0 500 1000 1500 ε Temperature oC Refractory Wall with Emisshield® Coating Refractory Wall without Emisshield® CoatingAFRC 2014 Industrial Combustion Symposium • a combination of conventional Eulerian turbulence modeling with Monte-Carlo PDF methods to model turbulent reactions and mixing; and • a matrix-free Newton-Krylov method to reduce solver computational time and improve robustness. Radiation property models can and usually have a close relationship to the radiative transfer equation (RTE) solution method. For example, efficient but accurate predictions of gas radiative transfer can be a challenge due to the strong spectral variation of the gas radiative properties (absorption coefficient). The absorption spectra of gases consist of many thousands of spectral lines because gases emit and absorb electromagnetic radiation only at discrete frequencies where the corresponding photon energies match the quantum changes in energy of the gas molecules. Narrow- and wide-band models for gas radiation properties provide a representation of spectrally averaged quantities such as transmissivity or band absorptance that require specification of path-length. Therefore, these band models do not lend themselves to arbitrary solution methods of the RTE, which, in its most fundamental form, is written in terms of a monochromatic absorption coefficient at a specific wave number and not in terms of spectrally averaged properties. The discrete ordinates model [Jamaluddin and Smith, 1988] for solving the RTE was used in this study and also requires the gas radiative properties to be specified as an absorption coefficient. Gas radiation models have been developed over the past few decades, where the main idea of the models is replacement of integration over wave number with integration over absorption cross-section with the reordering of continuous gas absorption coefficient into a set of gray gases. The total gas emissivity is expressed in the weighted-sum-of-gray gases form as =1−− where are the black body weights and are the associated absorption coefficients. The RTE in expressed in the weighted-sum-of-gray gas form is given as =4− To obtain spectrally integrated quantities one simply sums over the index j. The total incident radiative heat flux, for example, is given as =, where the incident flux, ,, is obtained from the solution of the RTE for that index. The spectral line-based weighted-sum-of-gray-gases (SLW) model, first introduced by [Denison and Webb, 1993a], was developed based on detailed line-by-line spectral data of gases. The basis of this model is the use of the Absorption Line Blackbody Distribution Function (ALBDF) [Denison and Webb, 1993b]. Denison and Fiveland  later extended the spectral based weighted-sum-of-gray gases model to Edward's wide band model [Edwards, 1976] parameters via a wide-band black-body distribution function. In this study, the correlation of Denison and Fiveland  was used but with only one gray gas and one clear gas. The clear gas represents the spectral windows between the gas bands where the gas is not participating radiatively. Denison and Fiveland's correlation was used to calculate black body weights of the WSGG, while the corresponding gray gas absorption coefficients were determined to match the total emissivity based on a large number of gray gases.AFRC 2014 Industrial Combustion Symposium Sample Pyrolysis Furnace Case An idealized pyrolysis furnace was modeled with ADAPT to examine the impact of using a high-emissivity coating on the furnace walls. One-half of the symmetric furnace geometry was modeled as shown in Figure 4. The half-furnace was fired at 15.26 MW, with a fuel comprised of 50% methane, 50% hydrogen. The furnace was first simulated with the furnace walls at an emissivity of 0.4 (Case 1), then again with an emissivity of 0.9 (Case 2). Process coils were assigned an emissivity of 0.85 for both cases. All emissivities were assumed to be constant over the spectrum of wavelengths for these analyses. Spectral simulations (as described above) were used to calculate furnace properties for the two cases. Note that if spectral calculations were not used, the heat transfer and temperature results for the two cases would be identical. Table 1 summarizes the results for Case 1 and Case 2 scenarios. Only the wall emissivities were varied between the two cases. The higher wall emissivity for Case 2 resulted in more of the flame energy being transferred to the process tubes. As a result, the process fluid outlet temperature rose by 4 °C, the maximum tube surface temperature rose by 4 °C and the furnace thermal efficiency increased from 39.0% to 40.5%. Because the casing loss was similar for both cases, the higher energy transfer to the process tubes caused the energy remaining in the flue gas to decrease and the flue gas exit temperature dropped by 29 °C. These differences can be significant with respect to furnace process yield and/or required furnace firing rates. Table 1. Summary of Results for the Pyrolysis Furnace Spectral Analyses. Case1 Case2 Wall Emissivity 0.4 0.9 Firing Rate (MW) 15.26 15.26 Flue Gas Exit Temperature (°C) 1,223 1,194 Tube Heat Absorption (MW) 5.95 6.18 Max Tube Temperature (°C) 1,352 1,356 Process Outlet Temperature (°C) 855 859 Casing Loss (% of firing rate) 1.6 1.6 Furnace Efficiency (%) 39.0 40.5 Symmetry Plane 12.8 m Burners Process Coils Figure 4. Pyrolysis furnace geometry.AFRC 2014 Industrial Combustion Symposium Figure 5 shows the flame shapes in the furnace as defined by a 5000 ppmv CO iso-surface. The iso-surfaces are colored by flame temperature. The flames were longer than typical flames due to the idealized nature of the burners. Flame temperatures peaked approximately half-way up the furnace. Flame shapes for Case 1 and Case 2 were indistinguishable. Figure 6 shows the gas temperature profiles inside the furnace for Case 1 and Case 2. Consistent with the 29 °C drop in flue gas exit temperature for Case 2, the gas temperature profile is slightly lower for Case 2. Figure 7 plots the wall surface temperature for Case 1 and Case 2. The profiles and magnitudes are very similar, but Case 2 has slightly higher wall temperatures, consistent with the higher energy absorption and re-emission at the higher emissivity. Similarly, the net heat flux profiles shown in Figure 8 are slightly higher for Case 2. Figure 6. Gas temperature profiles for Case 1 and Case 2. Figure 5. Flame shapes as defined by 5000 ppm CO iso-surface.AFRC 2014 Industrial Combustion Symposium Figure 7. Furnace wall and process tube surface temperatures for Case 1 and Case 2. Figure 8. Process tube net heat flux profiles for Case 1 and Case 2.AFRC 2014 Industrial Combustion Symposium To more clearly illustrate the differences in radiative heat flux between the cases, the incident heat flux at the process tubes (averaged over all tubes) is plotted as a function of furnace height in Figure 9. The higher emissivity case clearly has a higher incident flux over the entire furnace height. Figure 9. Average incident heat flux at the process tubes for Case 1 (ε=0.4) and Case 2 (ε=0.9). These CFD results illustrate that the higher emissivity coating does improve the transfer of heat from the flame to process tubes, by making the radiative heat transfer between the furnace walls (as heated by the flame) and the process tubes more efficient. The overall effect is higher furnace efficiency. Simulating this behavior is helpful when evaluating adjustments to furnace operation, for example when changing from a liquid to gas process feedstock. This analysis did not include temperature or wavelength-dependent spectral characteristics of the furnace wall and tube emissivities, but accounting for these properties are not expected to change the conclusions that high emissivity surfaces produce enhanced heat transfer. The analysis also did not account for any changed surface conductivity associated with application of a coating that could more evenly distribute the absorbed heat before re-emission. Field Test in Glass Furnace A glass melting furnace is used to melt a batch of recycled glass (cullet) by heat transfer from gas burners and hot refractory walls to the cullet and melt. The use of high emissivity coatings on the furnace walls can potentially increase the efficiency of heat transfer to the cullet and melt, resulting in reduced firing rates to achieve a molten state for the glass. The concept for this application is shown in Figure 10. When high emissivity coatings are applied to the hot face of the refractories in the furnace superstructure and crown, radiant and convective energy from the burners and hot furnace gases are absorbed at the surface of the coating and re-radiated to the cooler glass batch. The use of the coating increases the heat transfer from the flame and furnace walls to the melt. This results in lower wall temperatures, lower gas temperatures (including less energy loss via flue gas), and higher melt temperatures. Alternately, the same melt temperature is achievable with lower firing rates (i.e., lower wall and gas temperatures).AFRC 2014 Industrial Combustion Symposium An Emisshield high-emissivity coating was applied to the crown and superstructure in an Owens Corning glass furnace as shown in Figure 11. This application has been previously documented (Kleeb and Fausey, 2010) and is only summarized here to illustrate the impact of the coating on furnace heat transfer. Figure 10. Glass furnace schematic and temperature impacts of coating. Figure 11. Installation of Emisshield coating in Owens Corning glass furnace. The impact of the coating is shown in Figure 12. The top curve of Figure 12 shows the energy consumption in the furnace at various cullet levels over the previous campaign. This plot confirms the well-established relationship that as cullet level in the batch is increased the energy consumption will decrease. These data points represent many months of operation at each level and thus are considered reliable for comparison to the energy consumption after installation of the high emissivity coating. The bottom curve is the energy consumption after the coating was applied to the furnace. Cullet levels in the AFRC 2014 Industrial Combustion Symposium batch were changed to be able to compare directly to the pre-coating energy consumption. Care was taken to spend enough time at each cullet level to be sure any change in energy consumption was real. Clearly the energy consumption is less after application of the coating. Although the axes are not labeled for proprietary reasons, the energy saving was in the range of 7-8%. Figure 12. Glass furnace energy requirements with and without coating. According to the glass furnace owner, the coating was still providing energy savings after two and one-half years of operation. Since the application and data collection on this furnace, the owner has applied a high emissivity coating to other oxy-fuel furnaces and to one gas-fired furnace. Furnaces identical to the one discussed here have shown a similar 7-8% energy savings while other oxy-fuel furnaces have shown savings as high as 10%. Conclusions The concept of how high emissivity coatings can enhance heat transfer efficiency in process furnaces has been reviewed. The enhanced efficiency can lead to increased process production and/or reduced firing rate (fuel) requirements. Modeling the behavior of high emissivity coatings can help furnace owners evaluate performance and operational impacts before application. Accurate simulation of the enhanced heat transfer from a coating requires spectral radiation calculations which can account for both the absorbing/emitting bands and the transparent windows in the combustion gases. REI's ADAPT CFD code was run with spectral calculations to simulate a pyrolysis furnace with and without an enhanced emissivity coating. Changing the wall refractory emissivity from 0.4 to 0.9 resulted in a 1.5% increase in furnace efficiency, a 4 °C increase in process fluid exit temperature, and a 29 °C drop in gas temperature at the furnace arch. Field application of the Emisshield high emissivity coating in a glass melting furnace showed energy savings of 7-8%. The durability and additional heat conduction behavior of coatings were not addressed in this work.AFRC 2014 Industrial Combustion Symposium Acknowledgments CFD graphics were created with Fieldview software by Intelligent Light (http://www.ilight.com). Coating emissivity information and glass furnace data were provided by Emisshield, Inc. References Adams, B., Tang, Q., Ma, J., Brown, D., 2007, "Modeling Combustion in Pyrolysis Furnaces with Next Generation Low NOx Burners," AFRC-JFRC International Symposium Denison, M.K., Webb, B.W., 1993a, "A spectral line based weighted-sum-of-gray-gases model for arbitrary RTE solvers," ASME J. Heat Transfer, vol. 115, pp. 1004-1012. Denison, M.K., Webb, B.W., 1993b, "An absorption-line blackbody distribution function for efficient calculation of total gas radiative transfer". J. Quant. Spectral Rad. Transfer, vol.50, pp.499-510. Denison, M.K. and Fiveland, W.A., 1997, "A Correlation for the Reordered Wavenumber of the Wide Band Absorptance of Radiating Gases," ASME J. Heat Transfer, Vol. 119, pp. 853-856. Edwards, D. K., 1976, "Molecular Gas Band Radiation," Advances in Heat Transfer, Vol. 12, pp. 115-193, Academic Press, New York. Jamaluddin, A. S. and Smith, P. J., 1988, "Predicting Radiative Transfer in Rectangular Enclosures Using the Discrete Ordinates Method," Combustion Science and Technology, Vol. 59, pp. 321-340. Kleeb, T., Fausey, B., 2010, "Fuel Savings with High Emissivity Coatings," 71st Conference on Glass Problems, Oct. 19-20, Columbus, Ohio. Tang, Q., Denison, M., Adams, B., and Brown, D., 2009, "Towards Comprehensive Computational Fluid Dynamics Modeling of Pyrolysis Furnaces With Next Generation Low NOx Burners Using Finite-rate Chemistry," Proceedings of Combustion Institute, Volume 32, Issue 2, Pages 2649-2657.