Heat transfer efficiency in gas–solid fluidized beds with flat and corrugated walls
-
Alam Nawaz Khan Wardag
Abstract
Gas–solid fluidized bed reactors exhibit improved heat and mass transfer performance as compared to packed beds. Corrugated walls installed in narrow gas–solid bubbling fluidized bed (CWBFB) enclosures have been observed to decrease minimum bubbling velocity, reduce bubble size, improve gas distribution, provide stable operation, and minimize particle carryover or loss. Thorough analyses of the wall-to-bed heat transfer coefficient in flat- (FWBFB) and corrugated- (CWBFB) wall bubbling fluidized beds have been performed for a variety of operating conditions and geometric parameters. Fast-response self-adhesive heat flux probes and thermocouples were used to simultaneously measure the wall-to-bed heat flux, surface and bed temperatures, and were used to determine the heat transfer coefficient (HTC) at various axial and lateral locations. For a given set of parameters, a significant increase in HTC was observed at lower gas flow rates in CWBFB as compared to FWBFB. It was shown that CWBFB inventory required lower U mb (gas flow rate) as compared to FWBFB. Full 3-D transient Euler–Euler CFD simulations using the kinetic theory of granular flow were also performed, which confirmed the experimental results.
Funding source: Natural Sciences and Engineering Research Council of Canada
-
Research ethics: Not applicable.
-
Informed consent: Not applicable.
-
Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Use of Large Language Models, AI and Machine Learning Tools: Used to chase typos and for grammatical correctness.
-
Competing interests: The authors state no conflict of interest.
-
Research funding: The Natural Sciences and Engineering Research Council of Canada Strategic Grant Program and the Canada Research Chair “Green processes for cleaner and sustainable energy” are gratefully acknowledged for their financial support. One of the authors (ANKW) gratefully acknowledges the Pakistan Institute of Engineering and Applied Sciences for his PhD scholarship.
-
Data availability: Upon case by case request.
References
1. Iliuta, I, Leclerc, A, Larachi, F. Allothermal steam gasification of biomass in cyclic multi-compartment bubbling fluidized bed gasifier/combustor – new reactor concept. Bioresour Technol 2010;101:3194–208. https://doi.org/10.1016/j.biortech.2009.12.023.Suche in Google Scholar PubMed
2. Wei, B, Sun, L, Lv, G, Meng, X, Khalid, Z, Huang, Q, et al.. Effects of tube configurations on the heat transfer and hydrodynamic behavior in a gas-solid fluidized bed. Powder Technol 2024;436:119439. https://doi.org/10.1016/j.powtec.2024.119439.Suche in Google Scholar
3. Zheng, N, Chen, S, Liu, H, Fang, J, Wei, J. Novel segmental model for predicting bed-to-tube heat transfer coefficient in gas–solid fluidized beds. Ind Eng Chem Res 2024;63:4678–90. https://doi.org/10.1021/acs.iecr.3c04494.Suche in Google Scholar
4. Husin, H, Gani, A, Mamat, R, Nasaruddin, Mamat, R. Modification of perforated plate in fluidized-bed combustor chamber through computational fluid dynamics simulation. Results Eng 2023;19:101246. https://doi.org/10.1016/j.rineng.2023.101246.Suche in Google Scholar
5. Kunii, D, Levenspiel, O. Fluidization engineering, 2nd ed. Butterworth-Heinemann series in chemical engineering. MA, USA: Newton; 1991.Suche in Google Scholar
6. Khan Wardag, AN, Larachi, F. Bubble behavior in corrugated-wall bubbling fluidized beds – experiments and CFD simulations. AIChE J 2012;58:2045–57. https://doi.org/10.1002/aic.12725.Suche in Google Scholar
7. Khan Wardag, AN, Larachi, F. Stability analysis of flat- and corrugated-wall bubbling fluidized beds: differential pressure, heat transfer coefficient, digital image analysis and CFD simulations. Chem Eng J 2012;179:349–62. https://doi.org/10.1016/j.cej.2011.11.017.Suche in Google Scholar
8. Khan Wardag, AN, Larachi, F. Bed expansion and disengagement in corrugated wall bubbling fluidized beds. Chem Eng Sci 2012;81:273–84. https://doi.org/10.1016/j.ces.2012.07.016.Suche in Google Scholar
9. Khan Wardag, AN, Larachi, F, Grandjean, BPA. Bubble size and frequency in corrugated-wall bubbling fluidized beds-image analysis and neural network correlations. Ind Eng Chem Res 2012;51:12107–16. https://doi.org/10.1021/ie3007775.Suche in Google Scholar
10. Kunii, D, Levenspiel, O. Fluidization engineering, 1st ed. New York, USA: John Wiley; 1969.Suche in Google Scholar
11. Chen, JC. Heat transfer. In: Yang, WC, editor. Handbook of fluidization and fluid-particle systems, Chapter 10. New York, USA: Marcel Dekker; 2003.10.1201/9780203912744.ch10Suche in Google Scholar
12. Ranz, WE. Friction and transfer coefficients for single particle and packed beds. Chem Eng Prog 1952;48:247–53.Suche in Google Scholar
13. Hrdlička, J, Opatřil, J, Vodička, M. Bed-to-surface heat transfer in a BFB oxy-fuel combustor. Fuel 2023;364:131093. https://doi.org/10.1016/j.fuel.2024.131093.Suche in Google Scholar
14. Lee, MJ, Kim, S, Kim, SW. Experimental investigation of wall-to-bed heat transfer of carbon nanotubes in a fluidized bed. Int J Heat Mass Tran 2023;204:123858. https://doi.org/10.1016/j.ijheatmasstransfer.2023.123858.Suche in Google Scholar
15. Brewster, KJ, Fosheim, JR, Arthur-Arhin, WJ, Schubert, KE, Chen-Glasser, M, Billman, JE, et al.. Particle-wall heat transfer in narrow-channel bubbling fluidized beds for thermal energy storage. Int J Heat Mass Tran 2024;224:125276. https://doi.org/10.1016/j.ijheatmasstransfer.2024.125276.Suche in Google Scholar
16. Yu, Y, Lu, F, Bai, H, Wei, F, Zhang, C. Effect of fines addition on heat transfer performance in gas-solid fluidized bed: an integrated experimental, simulation, and theoretical study. Chem Eng J 2023;476:146806. https://doi.org/10.1016/j.cej.2023.146806.Suche in Google Scholar
17. Decker, N, Glicksman, LR. Heat transfer in large particle fluidized beds. Int J Heat Mass Tran 1983;26:1307–20. https://doi.org/10.1016/s0017-9310(83)80062-3.Suche in Google Scholar
18. Horio, M, Kobylecki, RP, Tsukada, M. Instrumentation and measurements. In: Yang, WC, editor. Handbook of fluidization and fluid-particle systems, Chapter 25. New York: Marcel Dekker; 2003.Suche in Google Scholar
19. Wu, C, Al-Dahhan, MH, Prakash, A. Heat transfer coefficients in a high-pressure bubble column. Chem Eng Sci 2007;62:140–7. https://doi.org/10.1016/j.ces.2006.08.016.Suche in Google Scholar
20. Luo, X, Jiang, P, Fan, LS. High-pressure three-phase fluidization: hydrodynamics and heat transfer. AIChE J 1997;43:2432–45. https://doi.org/10.1002/aic.690431007.Suche in Google Scholar
21. Patil, DJ, Smit, J, van Sint Annaland, M, Kuipers, JAM. Wall-to-bed heat transfer in gas-solid bubbling fluidized beds. AIChE J 2006;52:58–74. https://doi.org/10.1002/aic.10590.Suche in Google Scholar
22. Taghipour, F, Ellis, N, Wong, C. Experimental and computational study of gas-solid fluidized bed hydrodynamics. Chem Eng Sci 2005;60:6857–67. https://doi.org/10.1016/j.ces.2005.05.044.Suche in Google Scholar
23. Fluent user’s guide. Lebannon, USA: Fluent Inc.; 2006.Suche in Google Scholar
24. van Wachem, BGM, Schouten, JC, Krishna, R, van den Bleek, CM. Validation of the Eulerian simulated dynamic behavior of gas-solid fluidized beds. Chem Eng Sci 1999;54:2141–9. https://doi.org/10.1016/s0009-2509(98)00303-0.Suche in Google Scholar
25. Sommerfeld, M, van Wachem, B, Oliemans, R. Best practice guidelines for computational fluid dynamics of dispersed multiphase flows. ver. 1. European Research Community on Flow, Turbulence and Combustion. SIAMUF; 2008. https://www.ercoftac.org/publications/ercoftac_best_practice_guidelines/dispersed_multi-phase_flows_dmpf/.Suche in Google Scholar
26. Gao, J, Chang, J, Xu, C, Lan, X, Yang, Y. CFD simulation of gas solid flow in FCC strippers. Chem Eng Sci 2008;63:1827–41. https://doi.org/10.1016/j.ces.2007.12.009.Suche in Google Scholar
27. Li, T, Zhang, Y, Grace, JR, Bi, X. Numerical investigation of gas mixing in gas-solid fluidized beds. AIChE J 2010;56:2280–96. https://doi.org/10.1002/aic.12144.Suche in Google Scholar
28. Schmidt, A, Renz, U. Numerical prediction of heat transfer between a bubbling fluidized bed and an immersed tube bundle. Heat Mass Tran 2005;41:257–70.10.1007/s00231-004-0510-zSuche in Google Scholar
29. Hamzehei, M, Rahimzadeh, H. Experimental and numerical study of hydrodynamics with heat transfer in a gas−solid fluidized-bed reactor at different particle sizes. Ind Eng Chem Res 2009;48:3177–86. https://doi.org/10.1021/ie801413q.Suche in Google Scholar
30. Zhao, Y, Jiang, M, Liu, Y, Zheng, J. Particle-scale simulation of the flow and heat transfer behaviors in fluidized bed with immersed tube. AIChE J 2009;55:3109–24. https://doi.org/10.1002/aic.11956.Suche in Google Scholar
31. Armstrong, LM, Gu, S, Luo, KH. Study of wall-to-bed heat transfer in a bubbling fluidised bed using the kinetic theory of granular flow. Int J Heat Mass Tran 2010;53:4949–59. https://doi.org/10.1016/j.ijheatmasstransfer.2010.05.047.Suche in Google Scholar
© 2024 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Energy cost prediction for chromium removal by nanofiltration membrane
- Forecasting gasification sustainability through enhanced K-nearest neighbour models for hydrogen and nitrogen amount
- Applying machine learning for biomass gasification prediction: enhancing efficiency and sustainability
- Enhancing prediction of elemental composition through machine learning decision tree models for biomass gasification optimization
- Nonlinear model predictive controller of hydrogenation of dimethyl oxalate for ethylene glycol production
- Dynamic optimization of boiler for minimizing energy consumption in the intentionally transient process operation: effect of different interval number
- Heat transfer efficiency in gas–solid fluidized beds with flat and corrugated walls
- Ant lion based optimization for performance improvement of methanol production
- Boundary Element Method for Viscous Flow through Out-phase Slip-patterned Microchannel under the Influence of Inclined Magnetic Field
- Artificial neural network models for forecasting the extracted yield of essential oils from Curcuma longa L. by hydro-distillation
Artikel in diesem Heft
- Frontmatter
- Research Articles
- Energy cost prediction for chromium removal by nanofiltration membrane
- Forecasting gasification sustainability through enhanced K-nearest neighbour models for hydrogen and nitrogen amount
- Applying machine learning for biomass gasification prediction: enhancing efficiency and sustainability
- Enhancing prediction of elemental composition through machine learning decision tree models for biomass gasification optimization
- Nonlinear model predictive controller of hydrogenation of dimethyl oxalate for ethylene glycol production
- Dynamic optimization of boiler for minimizing energy consumption in the intentionally transient process operation: effect of different interval number
- Heat transfer efficiency in gas–solid fluidized beds with flat and corrugated walls
- Ant lion based optimization for performance improvement of methanol production
- Boundary Element Method for Viscous Flow through Out-phase Slip-patterned Microchannel under the Influence of Inclined Magnetic Field
- Artificial neural network models for forecasting the extracted yield of essential oils from Curcuma longa L. by hydro-distillation
