Simulation and Optimization of Flow Patterns in an Oscillatory Central Baffled Reactor: Enhancing Mixing and Energy
Received: 19 July 2024 | Revised: 6 August 2024 | Accepted: 11 August 2024 | Online: 24 September 2024
Corresponding author: Saba A. Gheni
Abstract
This research analyses the flow patterns in an Oscillatory Central Baffled Reactor (OCBR) using Computational Fluid Dynamics (CFD) simulations under various oscillation conditions. Frequency (f) and amplitude (x0) are examined as critical parameters for enhancing fluid mixing and energy efficiency in high viscosity fluids, such as biofuels. The findings highlight the significant impact of the Strouhal number (St) on the flow behavior, showing improved fluid mixing with an increase in the oscillatory Reynolds number (Re0) from 125.6 (f = 2 Hz, x0 = 2 mm) to 392.7 (f = 2.5 Hz, x0 = 5 mm), corresponding to a decrease in the St from 0.2 to 0.08. The simulations indicated the appearance of stable vortices and a better distribution of the Weibel dead zones at an oscillation cycle (t/T) of 0.5. During the course of the study, the pressure distribution within the OCBR and its dependence on oscillation amplitude were shown, which significantly impacted the pressure drop from 8.8 to 123 Pa as Re0 was raised. In order to alleviate the endpoints for high resistance of sharp edged baffles, two modified baffle designs (semi-central and smooth-edge central baffles) were used. The findings showed that the performance of the semi-central baffle design in terms of dead zone reduction and shear stress was superior to those of the other designs for both upward and downward flows, indicating its suitability for enhancing the performance of the OCBR. This research offers important developments in the efficient mixing processes needed in industrial applications and indicates some areas for effective testing and validation of the models developed.
Keywords:
Oscillatory Central Baffled Reactor (OCBR), Computational Fluid Dynamics (CFD), Strouhal number, Reynolds number, central baffle, flow pattern, simulation, pressure distributionDownloads
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Copyright (c) 2024 Safaa M. R. Ahmed, Mudheher M. Ali, Saba A. Gheni
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