A Probabilistic Statistical Method for the Determination of Void Morphology with CFD-DEM Approach

Yuanxiang Lu, Sihan Liu, Xinru Zhang, Zeyi Jiang and Dianyu E
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Yuanxiang Lu: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Sihan Liu: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Xinru Zhang: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Zeyi Jiang: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
Dianyu E: International Research Institute for Minerals, Metallurgy and Materials, Jiangxi University of Science and Technology, Nanchang 330013, China

Energies, 2020, vol. 13, issue 16, 1-14

Abstract: 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: packed bed; void morphology; CFD-DEM; dynamic stability; probability method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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