Positron emission particle tracking (PEPT): A novel approach to flow visualisation in lab-scale anaerobic digesters



Sindall, Rebecca C, Dapelo, Davide ORCID: 0000-0002-3442-6857, Leadbeater, Tom and Bridgeman, John ORCID: 0000-0001-8348-5004
(2017) Positron emission particle tracking (PEPT): A novel approach to flow visualisation in lab-scale anaerobic digesters. FLOW MEASUREMENT AND INSTRUMENTATION, 54. pp. 250-264.

[img] PDF
Positron_emission_particle_tracking_PEPT_A_novel_a.pdf - Author Accepted Manuscript

Download (9MB) | Preview

Abstract

Positron emission particle tracking (PEPT) was used to visualise the flow patterns established by mixing in two laboratory-scale anaerobic digesters fitted with mechanical mixing or gas mixing apparatus. PEPT allows the visualisation of flow patterns within a digester without necessitating the use of a transparent synthetic sludge. In the case of the mechanically-mixed digester, the mixing characteristics of opaque sewage sludge was compared to a transparent synthetic sludge at different mixing speeds. In the gas-mixed apparatus, two synthetic sludges were compared. In all scenarios, quasi-toroidal flow paths were established. However, mixing was less successful in more viscous liquids unless mixing power was increased to compensate for the increase in viscosity. The robustness of the PEPT derived velocities was found to be significantly affected by the frequency with which the particle enters a given volume of the vessel, with the accuracy of the calculated velocity decreasing in regions with low data capture. Nevertheless, PEPT was found to offer a means of accurate validation of computational fluid dynamics models which in turn can help to optimise flow patterns for biogas production.

Item Type: Article
Uncontrolled Keywords: Anaerobic digestion, Mechanical mixing, Gas mixing, Flow patterns, Particle tracking
Divisions: Faculty of Science and Engineering > School of Engineering
Depositing User: Symplectic Admin
Date Deposited: 17 May 2023 10:07
Last Modified: 17 May 2023 10:07
DOI: 10.1016/j.flowmeasinst.2017.02.009
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3170416