Mathematical modelling of time-dependent densified thickeners

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Zhang, Yi and Martin, Alastair and Grassia, Paul (2013) Mathematical modelling of time-dependent densified thickeners. Chemical Engineering Science, 99. pp. 103-112. ISSN 0009-2509 (https://doi.org/10.1016/j.ces.2013.05.046)

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Abstract

A one dimensional dewatering model for a thickener consistent with time-dependent densification of aggregates within a sludge suspension has been developed in this paper. The effects of different densification rate parameters and different underflow solids fluxes on the predictions of the sludge rheological properties and thickener performance have been explored. Pre-shearing of aggregates (which leads to the aggregates densifying to some extent before entering the thickener consolidating bed) must occur if a large underflow solids flux is required in a densified thickener. This increases the suspension gel point, and hence the solids volume fraction at the top of the bed. The solids volume fraction at the top of the bed will however be the initial undensified gel point in the case of a small underflow solids flux, where no pre-shearing of aggregates needs to occur. The effects of densification and/or pre-shearing on the sludge rheological properties and thickener performance have been predicted. For a densified thickener, an algorithm has been developed to determine the maximum permitted underflow solids flux, qmax, assuming any possible solids volume fraction at the top of the bed and the maximum underflow solids flux, qmu, constraining to the initial undensified gel point at the top of the bed. Regarding the aggregate densification rate parameter, as this parameter was increased, the sludge rheological properties evolved significantly during thickening and thickener performance was substantially enhanced. Moreover, the total solids residence time required to achieve the desired underflow solids volume fraction was significantly reduced both for a higher densification rate parameter and in the presence of pre-shearing in a densified thickener.

ORCID iDs

Zhang, Yi, Martin, Alastair and Grassia, Paul ORCID logoORCID: https://orcid.org/0000-0001-5236-1850;
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