Importance of mathematical modeling in innovation

  • 1 Mechanical Engineering, Akdeniz University, Antalya, Turkey; Bucak Technology Faculty, Burdur Mehmet Akif Ersoy University, Burdur, Turkey
  • 2 Bucak Emin Gülmez Vocational School of Technical Sciences, Burdur Mehmet Akif Ersoy University, Burdur, Turkey
  • 3 Department of Energy Systems Engineering, Burdur Mehmet Akif Ersoy University, Burdur, Turkey
  • 4 Department of Chemical Engineering, Pakistan Institute of Engineering and Applied Sciences, Pakistan
  • 5 School of Foreign Languages, Akdeniz University, Antalya, Turkey


Mathematical modeling is the key parameter in designing new devices. Renewable energy technologies are getting higher importance in the near future. Mathematical modeling of circulating fluidized bed (CFB) biomass combustion could improve both their design and operation, reduce any associated problems and facilitate the implantation of this technology. A good understanding of the combustion and pollutant generating processes in the gasifier can greatly avoid costly upsets. Presently, there is a focus on developing models of CFB for burning biomass and waste material. The objectives of these models are to be able to predict the behavior with respect to the combustion efficiency, fouling problems and pollutant emissions performance of different fuels or mixtures in commercial CFBs. In this study, importance of mathematical modeling in designing CFB biomass gasifiers is investigated in view of innovative solutions.



  1. Lee, R., Lee, J.H., Garrett, T.C., 2019. Synergy effects of innovation on firm performance. Journal of Business Research, 99, 507-515.
  2. Zeigler, B.P., Praehofer, H., Kim, T., 2000. Theory of Modeling and Simulation. 2nd Edition, Academic Press.
  3. Koçer, A., Yaka, I.F., Gungor, A., Evaluation of greenhouse residues gasification performance in hydrogen production. International Journal of Hydrogen Energy, 42, 23244-23249.
  4. Gungor, A., 2011. Modeling the effects of the operational parameters on H2 composition in a biomass fluidized bed gasifier. International Journal of Hydrogen Energy, 36, 6592-6600.
  5. Gungor, A., 2007. Two-dimensional biomass combustion modeling of CFB. Fuel, 87, 1453-1468.
  6. Li, F., Song, F., Benyahia, S., Wang, W., Li, J. 2012. MP-PIC simulation of CFB riser with EMMS-based drag model. Chemical Engineering Science, 82, 104-113.
  7. Zhang, H.L., Degreve, J., Dewil, R., Baeyens, J. 2015. Operation diagram of Circulating Fluidized Beds (CFBs). Procedia Engineering, 102, 1092-1103.
  8. Mirmoshtaghi, G., Skvaril, J., Campana, P.E., Li, H., Thorin, E., Dahlquist, E., 2016. The influence of different parameters on biomass gasification in circulating fluidized bed gasifiers. Energy Conversion and Management, 126, 110-123.
  9. Zhu, L.-T., Liu, Y.-X., Tang, J.-X., Luo, Z.-H. 2019. A MaterialProperty-Dependent Sub-Grid Drag Model for Coarse-Grained Simulation of 3D Large-Scale CFB Risers. Chemical Engineering Science, 204,228-245.
  10. Doherty, W., Reynolds, A., Kennedy, D., 2009. The effect of air preheating in a biomass CFB gasifier using ASPEN Plus simulation. Biomass and Bioenergy, 33, 1158-1167.
  11. Gungor, A., 2010. Simulation of emission performance and combustion efficiency in biomass fired circulating fluidized bed combustors. Biomass and Bioenergy, 34, 506-514.
  12. Ghadirian, E., Abbasian, J., & Arastoopour, H. 2019. CFD simulation of gas and particle flow and a carbon capture process using a circulating fluidized bed (CFB) reacting loop. Powder Technology, 344, 27-35.
  13. Niemi, T., Kallio, S., 2018. Modeling of conversion of a single fuel particle in a CFD model for CFB combustion. Fuel Processing Technology, 169, 236-243.
  14. Xu, L., Cheng, L., Ji, J., Wang, Q., Fang, M., 2019. A comprehensive CFD combustion model for supercritical CFB boilers, Particuology, 43, 29-37.
  15. Yaming, Z., Daoyin, L., Xiaoping, C., Jiliang, M., Jie, X., Cai, L., 2018. Statistic model for predicting cluster movement in circulating fluidized bed (CFB) riser, Journal of the Taiwan Institute of Chemical Engineers, 91, 200-212.
  16. Peng, L., Wu, Y., Wang, C., Gao, J., Lan, X., 2016. 2.5D CFD simulations of gas–solids flow in cylindrical CFB risers. Powder Technology, 291, 229-243.
  17. Yu, X., Blanco, P.H., Makkawi, Y., Bridgwater, A.V., 2018. CFD and experimental studies on a circulating fluidised bed reactor for biomass gasification. Chemical Engineering and Processing - Process Intensification, 130, 284-295.
  18. Rossbach, V., Utzig, J., Decker, R.K., Noriler, D., Soares, C., Martignoni, W.P., Meier, H.F., 2019. Gas-solid flow in a ring-baffled CFB riser: Numerical and experimental analysis. Powder Technology, 345, 521-531.
  19. Zhou, X., Gao, J., Xu, C., Lan, X., 2013. Effect of wall boundary condition on CFD simulation of CFB risers. Particuology, 11, 556-565.

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