Prediction of solid circulation rate in an internal circulating fluidized bed: An empirical and ANN approach
Tài liệu tham khảo
Kunii, 1991, Chapter 2 - industrial applications of fluidized beds, 15
Feng, 2012, CFD modeling of gas–solid flow in an internally circulating fluidized bed, Powder Technol., 219, 78, 10.1016/j.powtec.2011.12.007
Kim, 2000, Modeling of coal gasification in an internally circulating fluidized bed reactor with draught tube, Fuel, 79, 69, 10.1016/S0016-2361(99)00128-3
Kim, 1997, Entrainment of solids in an internally circulating fluidized bed with draft tube, Chem. Eng. J., 66, 105, 10.1016/S1385-8947(96)03166-X
Song, 1997, Circulation of solids and gas bypassing in an internally circulating fluidized bed with a draft tube, Chem. Eng. J., 68, 115, 10.1016/S1385-8947(97)00061-2
Kim, 2002, Solid circulation characteristics in an internally circulating fluidized bed with orifice-type draft tube, Kor. J. Chem. Eng., 19, 911, 10.1007/BF02706989
Chu, 2005, Flue gas desulfurization in an internally circulating fluidized bed reactor, Powder Technol., 154, 14, 10.1016/j.powtec.2005.03.017
Miccio, 2012, Combined gasification of coal and biomass in internal circulating fluidized bed, Fuel Process. Technol., 95, 45, 10.1016/j.fuproc.2011.11.008
Tian, 2001, Internal circulating fluidized bed incineraton system and design algorithm, J. Environ. Sci., 13, 185
Reichhold, 1995, Internally circulating fluidized bed for continuous adsorption and desorption, Chem. Eng. Process, 34, 521, 10.1016/0255-2701(95)00623-0
Gujjula, 2015, Hydrodynamic study of gas–solid internally circulating fluidized bed using multiphase CFD model, Part. Sci. Technol., 33, 593, 10.1080/02726351.2015.1013590
Choi, 1991, Bubble characteristics in an internally circulating fluidized bed, J. Chem. Eng. Jpn., 24, 195, 10.1252/jcej.24.195
Song, 1997, Circulation of solids and gas bypassing in an internally circulating fluidized bed with a draft tube, Chem. Eng. J., 68, 115, 10.1016/S1385-8947(97)00061-2
Kim, 2002, Solid circulation characteristics in an internally circulating fluidized bed with orifice-type draft tube, Kor. J. Chem. Eng., 19, 911, 10.1007/BF02706989
Song, 2017, Experimental study on gas-solid flow characteristics in an internally circulating fluidized bed cold test apparatus, Adv. Powder Technol., 28, 10.1016/j.apt.2017.05.017
Jiang, 2020, Experimental investigation of particle circulation in an internally circulating clapboard-type fluidized bed, Chem. Eng. Technol., 43, 253, 10.1002/ceat.201800416
Li, 2022, Experimental and numerical study on thermal performance of an indirectly irradiated solar reactor with a clapboard-type internally circulating fluidized bed, Appl. Energy, 305, 10.1016/j.apenergy.2021.117976
Wei, 2020, Experimental investigation of pressure fluctuation propagation in two orthogonal directions using a clapboard-type internally circulating fluidized bed, Adv. Powder Technol., 31, 3395, 10.1016/j.apt.2020.06.026
Chen, 2020, Prediction of particle circulation rate in an internally circulating fluidized bed with a central draft tube, Powder Technol., 380
Chew, 2020, Application of machine learning methods to understand and predict circulating fluidized bed riser flow characteristics, Chem. Eng. Sci., 217, 10.1016/j.ces.2020.115503
Zhong, 2021, Prediction of solid holdup in a gas–solid circulating fluidized bed riser by artificial neural networks, Ind. Eng. Chem. Res., 60, 10.1021/acs.iecr.0c05474
Upadhyay, 2022, Hybrid CFD-neural networks technique to predict circulating fluidized bed reactor riser hydrodynamics, J. Clean. Prod., 337, 10.1016/j.jclepro.2022.130490
Gujjula, 2015, Experimental investigation of hydrodynamics of gas-solid flow in an internally circulating fluidized bed, Can. J. Chem. Eng., 93, 1380, 10.1002/cjce.22233
Kisi, 2016, Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution, J. Hydrol., 534, 104, 10.1016/j.jhydrol.2015.12.014
Abdolrasol, 2021, Artificial neural networks based optimization techniques, Review, 10, 2689
Upadhyay, 2022, Hybrid CFD-neural networks technique to predict circulating fluidized bed reactor riser hydrodynamics, J. Clean. Prod., 337, 10.1016/j.jclepro.2022.130490
Chandel, 2006, A model for the solid circulation rate in a recirculating fluidized bed, Chem. Eng. Commun., 193, 1514, 10.1080/00986440600584250
Ahn, 1999, Solid circulation and gas bypassing in an internally circulating fluidized bed with an orifice-type draft Tube, Kor. J. Chem. Eng., 16, 618, 10.1007/BF02708141
Mathew, 2014, Hydrodynamic studies on fluidized beds with internals: experimental and ANN approach, Powder Technol., 264, 423, 10.1016/j.powtec.2014.06.001
Korkerd, 2021, Artificial neural network model for predicting minimum fluidization velocity and maximum pressure drop of gas fluidized bed with different particle size distributions, S. Afr. J. Chem. Eng., 37, 61
Serrano, 2020, Predicting the effect of bed materials in bubbling fluidized bed gasification using artificial neural networks (ANNs) modeling approach, Fuel, 266, 10.1016/j.fuel.2020.117021
Asghar, 2022, Estimation of the solid circulation rate in circulating fluidized bed system using adaptive neuro-fuzzy algorithm, Energies, 15, 211, 10.3390/en15010211
Yang, 1978, 218
H. Liu, C. Chen, Y. Li, Z. Duan, Y. Li, Chapter 9 - characteristic and correlation analysis of metro loads, in: H. Liu, C. Chen, Y. Li, Z. Duan, Y. Li (Eds.), Smart Metro Station Systems, Elsevier2022, pp. 237-267.
Janitza, 2018, On the overestimation of random forest's out-of-bag error, PLoS One, 13, 10.1371/journal.pone.0201904
Silva, 2015, Drying of Brazilian pepper-tree fruits (schinus terebinthifolius raddi): development of classical models and artificial neural network approach, Chem. Eng. Commun., 202, 1089, 10.1080/00986445.2014.901220