Optimization of mechanical mixing of anaerobic digesters using computational fluid dynamics (CFD)

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2018-09

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De Montfort University

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Thesis or dissertation

Peer reviewed

Abstract

To keep biogas production competitive against alternatives in the energy sector, reducing the operating costs is a major challenge for biogas applications. Up to 50 % of the energy consumption in biogas plants is contributed by the digester mixing. Therefore, the optimization of the digester mixing system is a promising approach to increase the overall efficiency of biogas plants. The main objective of the presented thesis is to optimize digester mixing to achieve the highest benefit at the lowest cost. Investigating the mixing process in digesters is a necessary precursor for successful design, operation, and increased efficiency in biogas plants. However, observation of mixing in digesters under real conditions is complex and cost intensive. With an adapted mixing system, a reduction of the operating costs of up to 30 % is possible. Process disturbance and maintenance costs can be minimized and the biogas production within a given digester volume can be maximized. The work shows the process and results of a simplified approach to simulate the mixing dynamic in a common cylindrical digester with computational fluid dynamics (CFD). The CFD simulation is verified by laboratory experiments. Based on the theory of similarity, at the Institute of new Energy Systems of the Technische Hochschule Ingolstadt, a 1:12 scale digester model was set up and an artificial chemical substrate was selected to mimic the rheology of real biomass. Different mixing regimes were configured using propellers and paddle stirrers located in varying positions. Optical and acoustic techniques were employed to observe the fluid dynamics in the laboratory experiment. In this thesis, the laboratory setup and the results on the flow velocity and torque on stirrer shaft developed during mixing are presented and discussed. The experimental are used to validate the similar numeric computational fluid dynamic study.

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