Knowledge Management System Of Institute of process engineering,CAS
| Coupling Artificial Neural Network with EMMS drag for simulation of dense fluidized beds | |
Yang, Zhuo1,2; Lu, Bona1,2; Wang, Wei1,2
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| 2021-12-31 | |
| Source Publication | CHEMICAL ENGINEERING SCIENCE
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| ISSN | 0009-2509 |
| Volume | 246Pages:12 |
| Abstract | The previous sub-grid, energy-minimization multi-scale (EMMS) drag models were all established at cer-tain fixed operating conditions and material properties. In this study, we developed a generic EMMS drag for simulating dense fluidized beds by using the Artificial Neural Network (ANN) to cover a wide range of operating conditions and material properties. To this end, the algorithm of the EMMS model was opti-mized to provide a huge dataset efficiently and the performance of ANN was tested by training with dif-ferent numbers of data and hidden layer structures. The EMMS-ANN model was determined by balancing the training precision and computational time and then applied to the simulation of five fluidized beds under different operating conditions and material properties. It was found that the simulation with the EMMS-ANN drag enables reasonable prediction and shows good applicability to a wide range of dense fluidization. (C) 2021 Elsevier Ltd. All rights reserved. |
| Keyword | EMMS Drag coefficient Artificial neural network Fluidized bed CFD simulation |
| DOI | 10.1016/j.ces.2021.117003 |
| Language | 英语 |
| WOS Keyword | GAS-SOLID FLOWS ; NUMERICAL-SIMULATION ; CONSTITUTIVE MODELS ; EULERIAN SIMULATION ; CFD SIMULATION ; 2-FLUID MODEL ; PARTICLES ; GELDART |
| Funding Project | National Natural Science Foundation of China[22078331] ; National Natural Science Foundation of China[91834302] ; National Natural Science Foundation of China[21625605] ; National Natural Science Foundation of China[21821005] ; State Key Laboratory of Multiphase Complex Systems of China[MPCS-2021-D05] ; Chinese Academy of Sciences[XDA21030700] |
| WOS Research Area | Engineering |
| WOS Subject | Engineering, Chemical |
| Funding Organization | National Natural Science Foundation of China ; State Key Laboratory of Multiphase Complex Systems of China ; Chinese Academy of Sciences |
| WOS ID | WOS:000704401400010 |
| Publisher | PERGAMON-ELSEVIER SCIENCE LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ipe.ac.cn/handle/122111/50538 |
| Collection | 中国科学院过程工程研究所 |
| Corresponding Author | Lu, Bona; Wang, Wei |
| Affiliation | 1.Chinese Acad Sci, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| Recommended Citation GB/T 7714 | Yang, Zhuo,Lu, Bona,Wang, Wei. Coupling Artificial Neural Network with EMMS drag for simulation of dense fluidized beds[J]. CHEMICAL ENGINEERING SCIENCE,2021,246:12. |
| APA | Yang, Zhuo,Lu, Bona,&Wang, Wei.(2021).Coupling Artificial Neural Network with EMMS drag for simulation of dense fluidized beds.CHEMICAL ENGINEERING SCIENCE,246,12. |
| MLA | Yang, Zhuo,et al."Coupling Artificial Neural Network with EMMS drag for simulation of dense fluidized beds".CHEMICAL ENGINEERING SCIENCE 246(2021):12. |
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