Dynamic control method of particle distribution uniformity in the rolling circulating fluidized bed (RCFB)

References

• Almuttahar, A., & Taghipour, F. (2008). Computational fluid dynamics of high density circulating fluidized bed riser: Study of modeling parameters. Powder Technology, 185(1), 11–23. https://doi.org/https://doi.org/10.1016/j.powtec.2007.09.010.
   Web of Science ®Google Scholar
• Anantharaman, A., Issangya, A., Karri, S. B. R., Findlay, J., Hrenya, C. M., Cocco, R. A., & Chew, J. W. (2017). Annulus flow behavior of Geldart Group B particles in a pilot-scale CFB riser. Powder Technology, 305, 816–828. https://doi.org/https://doi.org/10.1016/j.powtec.2016.11.007
   Web of Science ®Google Scholar
• Cai, R., Ke, X., Huang, Y., Zhu, S., Li, Y., Cai, J., Yang, H., Lyu, J., & Zhang, M. (2019). Applications of Ultrafine Limestone Sorbents for the Desulfurization Process in CFB Boilers. Environmental Science & Technology, 53(22), 13514–13523. https://doi.org/https://doi.org/10.1021/acs.est.9b04747
   PubMed Web of Science ®Google Scholar
• Ghalandari, M., Bornassi, S., Shamshirband, S., Mosavi, A., & Chau, K. W. (2019). Investigation of submerged structures’ flexibility on sloshing frequency using a boundary element method and finite element analysis. Engineering Applications of Computational Fluid Mechanics, 13(1), 519–528. https://doi.org/https://doi.org/10.1080/19942060.2019.1619197
   Web of Science ®Google Scholar
• He, Y., Bayly, A. E., & Hassanpour, A. (2018). Coupling CFD-DEM with dynamic meshing: A new approach for fluid-structure interaction in particle-fluid flows. Powder Technology, 325, 620–631. https://doi.org/https://doi.org/10.1016/j.powtec.2017.11.045
   Web of Science ®Google Scholar
• He, Y., Bayly, A. E., Hassanpour, A., Fairweather, M., & Muller, F. (2020). Flow behaviour of an agitated tubular reactor using a novel dynamic mesh based CFD model. Chemical Engineering Science, 212, 115333. https://doi.org/https://doi.org/10.1016/j.ces.2019.115333.
   Web of Science ®Google Scholar
• Hou, B., Wang, X., Zhang, T., & Li, H. (2017). A model for improving the Euler–Euler two-phase flow theory to predict chemical reactions in circulating fluidized beds. Powder Technology, 321, 13–30. https://doi.org/https://doi.org/10.1016/j.powtec.2017.07.081
   Web of Science ®Google Scholar
• Huai, W.-x., Xue, W.-y., & Qian, Z.-d. (2012). Numerical Simulation of Sediment-Laden Jets in Static Uniform Environment using Eulerian Model. Engineering Applications of Computational Fluid Mechanics, 6(4), 504–513. https://doi.org/https://doi.org/10.1080/19942060.2012.11015438
   Web of Science ®Google Scholar
• Jenaru, A., & Acomi, N. (2016). Numerical methods for assessment of the ship's pollutant emissions. In V. Cohal, L. Lobont, P. Topala, E. Oanta, M. Placzek, I. Carcea, C. Carausu, & D. Nedelcu (Eds.), Modtech International Conference – Modern Technologies in Industrial Engineering Iv, Pts 1-7 (Vol. 145). Iop Publishing Ltd. https://doi.org/https://doi.org/10.1088/1757-899x/145/8/082015.
   Google Scholar
• Ma, X. (2017). Analysis of the evolution mechanism about safety vulnerability of China's marine transport lanes. World Economics and Politics, 11, 108–129+159.
   Google Scholar
• Mnasri, C., Hafsia, Z., Omri, M., & Maalel, K. (2010). A Moving Grid Model for Simulation of Free Surface Behavior Induced by Horizontal Cylinders Exit and Entry. Engineering Applications of Computational Fluid Mechanics, 4(2), 260–275. https://doi.org/https://doi.org/10.1080/19942060.2010.11015315
   Web of Science ®Google Scholar
• Mosavi, A., Shamshirband, S., Salwana, E., Chau, K.-w., & Tah, J. H. M. (2019). Prediction of multi-inputs bubble column reactor using a novel hybrid model of computational fluid dynamics and machine learning. Engineering Applications of Computational Fluid Mechanics, 13(1), 482–492. https://doi.org/https://doi.org/10.1080/19942060.2019.1613448
   Web of Science ®Google Scholar
• Murata, H., Oka, H., Adachi, M., & Harumi, K. (2012). Effects of the ship motion on gas–solid flow and heat transfer in a circulating fluidized bed. Powder Technology, 231, 7–17. https://doi.org/https://doi.org/10.1016/j.powtec.2012.06.060
   Web of Science ®Google Scholar
• Park, S., Yang, J., & Rhee, S. H. (2017). Parametric study on ship’s exhaust-gas behavior using computational fluid dynamics. Engineering Applications of Computational Fluid Mechanics, 11(1), 159–171. https://doi.org/https://doi.org/10.1080/19942060.2016.1260057
   Web of Science ®Google Scholar
• Razvan, C., Lucian, G., & Ioan, M. (2015a). An OOP MATLAB Extensible Framework for the Implementation of Genetic Algorithms. Part I: The Framework. Procedia Technology, 19, 193–200. https://doi.org/https://doi.org/10.1016/j.protcy.2015.02.028
   Google Scholar
• Razvan, C., Lucian, G., & Ioan, M. (2015b). An OOP MATLAB Extensible Framework for the Implementation of Genetic Algorithms. Part II: Case Study. Procedia Technology, 19, 201–206. https://doi.org/https://doi.org/10.1016/j.protcy.2015.02.029
   Google Scholar
• Song, G., Li, Y., Wang, W., & Shi, Z. (2020). Numerical simulation of hydrate particle size distribution and hydrate particle bedding in pipeline flowing systems. Journal of Dispersion Science and Technology, 41(7), 1051–1064. https://doi.org/https://doi.org/10.1080/01932691.2019.1614043
   Web of Science ®Google Scholar
• Tian, Y., & Peng, X. F. (2004). Analysis of particle motion and heat transfer in circulating fluidized beds. International journal of energy research, 28(4), 287–297. doi:https://doi.org/10.1002/er.965
   Google Scholar
• Wahyudi, H., Chu, K. W., & Yu, A. B. (2016). 3D particle-scale modeling of gas–solids flow and heat transfer in fluidized beds with an immersed tube. International Journal of Heat and Mass Transfer, 97, 521–537. https://doi.org/https://doi.org/10.1016/j.ijheatmasstransfer.2016.02.038
   Web of Science ®Google Scholar
• Wang, Z., Zhao, T., Liu, K., & Takei, M. (2020). Clarification of an improved cluster renewal model (ICRM) for heat transfer characteristics in a rolling circulating fluidized bed (RCFB). Advanced Powder Technology, 31(7), 2866–2879. https://doi.org/https://doi.org/10.1016/j.apt.2020.05.015
   Web of Science ®Google Scholar
• Wu, Y., Liu, D. Y., Ma, J. L., & Chen, X. P. (2017). Three-Dimensional Eulerian–Eulerian Simulation of Coal Combustion under Air Atmosphere in a Circulating Fluidized Bed Combustor. Energy & Fuels, 31(8), 7952–7966. https://doi.org/https://doi.org/10.1021/acs.energyfuels.7b01084
   Web of Science ®Google Scholar
• Xia, Y., & Peng, F. F. (2007). Effect of Structured Plates on Fine Coal Gravity Separation in a Liquid Fluidized Bed System. Engineering Applications of Computational Fluid Mechanics, 1(3), 164–180. https://doi.org/https://doi.org/10.1080/19942060.2007.11015190
   Web of Science ®Google Scholar
• Yan, L., Liu, H., Li, F., & Liu, J. (2020). Dynamic characteristics of the large particles inside the fluidized bed with an inclined air distribution plate. Powder Technology, 367, 632–642. https://doi.org/https://doi.org/10.1016/j.powtec.2020.03.069
   Web of Science ®Google Scholar
• Zhang, M.-C. (2020). Characteristic-particle-tracked modeling for CFB boiler: Coal combustion and ultra-low NO emission. Powder Technology, 374, 632–647. https://doi.org/https://doi.org/10.1016/j.powtec.2020.07.079
   Web of Science ®Google Scholar
• Zhang, H., Zhong, L., Chen, J., & Zhang, Y. (2016). Review on desulfurization and denitration technologies for ship exhaust gas treatment. Chemical Industry and Engineering Progress, 35(11), 3650–3657. https://doi.org/https://doi.org/10.16085/j.issn.1000-6613.2016.11.040
   Google Scholar
• Zhao, T., Liu, K., Murata, H., Harumi, K., & Takei, M. (2014). Experimental and numerical investigation of particle distribution behaviors in a rolling circulating fluidized bed. Powder Technology, 258, 38–48. https://doi.org/https://doi.org/10.1016/j.powtec.2014.03.023
   Web of Science ®Google Scholar
• Zhao, T., Nakamura, Y., Liu, K., Murata, H., & Takei, M. (2016). The effect of rolling amplitude and period on particle distribution behavior in a rolling circulating fluidized bed. Powder Technology, 294, 484–492. https://doi.org/https://doi.org/10.1016/j.powtec.2016.03.018
   Web of Science ®Google Scholar