Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/135586
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Type: Journal article
Title: In-situ imaging of particle size distribution in an industrial-scale calcination reactor using micro-focusing particle shadowgraphy
Author: Han, S.
Sun, Z.
de Jacobi du Vallon, C.
Collins, T.
Boot-Handford, M.
Sceats, M.G.
Tian, Z.F.
Nathan, G.J.
Citation: Powder Technology, 2022; 404:1-12
Publisher: Elsevier BV
Issue Date: 2022
ISSN: 0032-5910
1873-328X
Statement of
Responsibility: 
Shipu Han, Zhiwei Sun, Claire de Jacobi du Vallon, Tim Collins, Matthew Boot-Handford, Mark G. Sceats, Zhao Feng Tian, Graham J. Nathan
Abstract: We present a novel demonstration of in-situ particle size measurement in a high-temperature, industrial-scale reactor for lime-calcination using micro-focusing particle shadowgraphy in particle-laden flows with volume fraction up to 0.02 and an optical path length of 670 mm. This non-intrusive method was demonstrated to provide reliable in-situ measurement of both particle size distribution (PSD) and sphericity, which are relevant to the performance of a novel cement production technology under development to provide direct capture of process-derived CO2 emissions. The details of the optical diagnosing system and test rig are presented. A previously reported processing algorithm based on image gradient to accurately identify the edges of particles in the focal plane with negligible line-of-sight interference was employed to derive both particle diameter and sphericity in comparison with independent extractive measurements with a commercial Mastersizer. The in-situ measurement revealed the presence of large calcined particle agglomerates under some conditions that were not identified with the extractive measurements. Statistical correlations between particle diameter and sphericity are also reported.
Keywords: Particle shadowgraph imaging; In-situ; Particle size distribution; Sphericity; Industrial pilot reactor; Decarbonisation
Rights: © 2022 Elsevier B.V. All rights reserved
DOI: 10.1016/j.powtec.2022.117459
Grant ID: http://purl.org/au-research/grants/arc/DP180102045
http://purl.org/au-research/grants/arc/LE180100203
Published version: http://dx.doi.org/10.1016/j.powtec.2022.117459
Appears in Collections:Mechanical Engineering publications

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