LAPSE:2023.25679
Published Article
LAPSE:2023.25679
A Probabilistic Statistical Method for the Determination of Void Morphology with CFD-DEM Approach
Yuanxiang Lu, Sihan Liu, Xinru Zhang, Zeyi Jiang, Dianyu E
March 29, 2023
Voids that are formed by gas injection in a packed bed play an important role in metallurgical and chemical furnaces. Herein, two-phase gas−solid flow in a two-dimensional packed bed during blast injection was simulated numerically. The results indicate that the void stability was dynamic, and the void shape and size fluctuated within a certain range. To determine the void morphology quantitatively, a probabilistic method was proposed. By statistically analyzing the white probability of each pixel in binary images at multiple times, the void boundaries that correspond to different probability ranges were obtained. The boundary that was most appropriate with the simulation result was selected and defined as the well-matched void boundary. Based on this method, the morphologies of voids that formed at different gas velocities were simulated and compared. The method can help us to express the morphological characteristics of the dynamically stable voids in a numerical simulation.
Keywords
CFD-DEM, dynamic stability, packed bed, probability method, void morphology
Suggested Citation
Lu Y, Liu S, Zhang X, Jiang Z, E D. A Probabilistic Statistical Method for the Determination of Void Morphology with CFD-DEM Approach. (2023). LAPSE:2023.25679
Author Affiliations
Lu Y: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Liu S: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Zhang X: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China; Beijing Engineering Research Center of Energy Saving and Environmental Protection, University of Science and Technology Beijing, Beijing 1 [ORCID]
Jiang Z: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China; Beijing Key Laboratory for Energy Saving and Emission Reduction of Metallurgical Industry, University of Science and Technology Beijing, B
E D: International Research Institute for Minerals, Metallurgy and Materials, Jiangxi University of Science and Technology, Nanchang 330013, China
Journal Name
Energies
Volume
13
Issue
16
Article Number
E4041
Year
2020
Publication Date
2020-08-05
Published Version
ISSN
1996-1073
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PII: en13164041, Publication Type: Journal Article
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doi:10.3390/en13164041
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