Comparison of three different CFD methods for dense fluidized beds and validation by a cold flow experiment--颗粒学报PARTICUOLOGY

Stroh, A., Alobaid, F., Hasenzahl, M. T., Hilz, J., Ströhle, J., & Epple, B. (2016). Comparison of three different CFD methods for dense fluidized beds and validation by a cold flow experiment. Particuology, 29, 34-47. https://doi.org/10.1016/j.partic.2015.09.010

Comparison of three different CFD methods for dense fluidized beds and validation by a cold flow experiment

Alexander Stroh ^*, Falah Alobaid, Max Thomas Hasenzahl, Jochen Hilz, Jochen Ströhle, Bernd Epple

Technische Universität Darmstadt, Institute for Energy Systems and Technology, Otto-Berndt-Straße 2, 64287 Darmstadt, Germany

10.1016/j.partic.2015.09.010

Volume 29, December 2016, Pages 34-47

Received 14 July 2015, Revised 25 August 2015, Accepted 11 September 2015, Available online 12 January 2016, Version of Record 18 November 2016.

E-mail: alexander.stroh@est.tu-darmstadt.de

Highlights

• Three numerical methods were compared to experimental data of a cold flow spouted fluidized bed.

• Two-fluid model was able to predict the flow pattern for the small mass flow rate.

• Euler–Lagrange MP-PIC and two-fluid methods were more appropriate for macroscale applications.

• Euler–Lagrange DEM was more appropriate to catch flow pattern details at different mass flow rates.

Abstract

This work focuses on a comparison between three different numerical CFD methods, namely Euler–Euler, Euler–Lagrange-stochastic, and Euler–Lagrange-deterministic, to treat a dense spouted bed. A simple cold flow experiment was used to investigate the hydrodynamics of a gas–solid flow in a three dimensional lab-scale spouted bed. In this context, two different air mass flow rates, 0.005 and 0.006 kg/s, were applied during fluidization. The experimental bed behaviour was recorded with a high-speed camera to validate the numerical predictions in terms of bubble size, bed expansion rate, and particle velocities at different reactor heights. The numerical setup was kept similar between all three modelling approaches. At both gas mass flow rates all three approaches are able to capture the overall bed expansion. However, at higher gas mass flow rates, discrepancies between experiment and simulation increase for the Euler–Euler and Euler–Lagrange-stochastic models. The Euler–Lagrange deterministic model most accurately predicts the flow pattern at both mass flow rates. The main reasons for discrepancies between simulation and experiment result from modelling of the collision and friction forces.

Graphical abstract

Keywords

Computational fluid dynamics; Euler–Lagrange-deterministic collision model; Euler–Euler; MP-PIC approach; Experimental validation

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