Abstract
Design and operation of mixing systems using agitated vessels is a difficult task due to the challenge of obtaining accurate information on impeller-induced turbulence. The use of Computational Fluid Dynamics (CFD) can provide detailed understanding of such systems. In this study, experimental tests and computational fluid dynamics simulations were performed to examine the flow characteristics of four impeller designs (anchor, saw-tooth, counter-flow and Rushton turbine), in achieving solution homogeneity. The impellers were used to mix potassium sulfate granules, from which values of electrical conductivity of the solution were measured and used to estimate the distribution pattern of dissolved solid concentrations within the vessel. CFD models were developed for similar mixing arrangement using commercial software, ANSYS Fluent 18.1 solver and the standard k-epsilon (ε) turbulence model. The Multiple Reference Frame (MRF) approach was used to simulate the impeller rotation. Velocity profiles generated from the simulations were in good agreement with the experimental predictions, as well as with results from previous studies. It was concluded that, through CFD analysis, detailed information can be obtained for optimal design of mixing apparatus. These findings are relevant in choosing the best mixing equipment and provides a basis for scaling up mixing operations in larger systems.
Highlights
Mixing is an essential operation in many engineering fields
The values of electrical conductivity obtained through experiments experiments were used to predict the mixing performance of the different impellers
Computational Fluid Dynamics (CFD) results were compared to the experimental data obtained on the distribution of the granules concentration concentration in in the the tank
Summary
Mixing is an essential operation in many engineering fields. It has central significance in food processing, pharmaceutical production, chemical engineering, biotechnology, agri-chemical preparations, paint manufacturing, water purification among countless other applications [1].Many mixing schemes using stirred tanks have been developed to meet various production and processing goals [2]. Mixing is an essential operation in many engineering fields. It has central significance in food processing, pharmaceutical production, chemical engineering, biotechnology, agri-chemical preparations, paint manufacturing, water purification among countless other applications [1]. Many mixing schemes using stirred tanks have been developed to meet various production and processing goals [2]. In agricultural systems, mixing set-ups have been used in a number of processes, such as preparing farm chemical concentrations, balancing nutrient amounts in fertilizer tanks, blending different substances and processing farm products. Flow streams in stirred vessels are known to be turbulent, chaotic and difficult to determine; attaining homogeneity in such mixing processes is a demanding task. A careful choice of equipment that generates sufficient turbulence and flow in the mixing vessel is necessary
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