An advanced EMMS scheme for the prediction of drag coefficient under a 1.2 MWth CFBC isothermal flow-Part II: Numerical implementation

Nikolopoulos, A; Atsonios, K; Nikolopoulos, N; Grammelis, P; Kakaras, E

dc.contributor.author	Nikolopoulos, A	en
dc.contributor.author	Atsonios, K	en
dc.contributor.author	Nikolopoulos, N	en
dc.contributor.author	Grammelis, P	en
dc.contributor.author	Kakaras, E	en
dc.date.accessioned	2014-03-01T01:32:37Z
dc.date.available	2014-03-01T01:32:37Z
dc.date.issued	2010	en
dc.identifier.issn	00092509	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20200
dc.subject	CFBC	en
dc.subject	CFD	en
dc.subject	EMMS	en
dc.subject	Hydrodynamics	en
dc.subject	Multiphase flow	en
dc.subject	Numerical analysis	en
dc.subject.other	CFBC	en
dc.subject.other	CFD	en
dc.subject.other	CFD codes	en
dc.subject.other	Clustering mechanism	en
dc.subject.other	Co-existing	en
dc.subject.other	Coarse grid	en
dc.subject.other	Computational cell	en
dc.subject.other	Computational grids	en
dc.subject.other	Control volumes	en
dc.subject.other	Drag forces	en
dc.subject.other	Drag model	en
dc.subject.other	EMMS	en
dc.subject.other	Eulerian	en
dc.subject.other	Experimental data	en
dc.subject.other	Grid density	en
dc.subject.other	Homogeneous conditions	en
dc.subject.other	Induced drag	en
dc.subject.other	Inert materials	en
dc.subject.other	Isothermal flows	en
dc.subject.other	Multiscales	en
dc.subject.other	Numerical grids	en
dc.subject.other	Numerical implementation	en
dc.subject.other	Numerical results	en
dc.subject.other	Numerical tools	en
dc.subject.other	Particle structure	en
dc.subject.other	Three dimensional simulations	en
dc.subject.other	Time evolutions	en
dc.subject.other	Cluster analysis	en
dc.subject.other	Computational fluid dynamics	en
dc.subject.other	Drag coefficient	en
dc.subject.other	Fluid dynamics	en
dc.subject.other	Hydrodynamics	en
dc.subject.other	Inert gases	en
dc.subject.other	Multiphase flow	en
dc.subject.other	Numerical analysis	en
dc.subject.other	Pressure drop	en
dc.subject.other	Drag	en
dc.title	An advanced EMMS scheme for the prediction of drag coefficient under a 1.2 MWth CFBC isothermal flow-Part II: Numerical implementation	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ces.2010.03.053	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ces.2010.03.053	en
heal.publicationDate	2010	en
heal.abstract	The arithmetic results from the formulation of an EMMS analysis for the calculation of drag coefficient between the co-existing phases in a CFB riser were implemented in a CFD code and three dimensional simulations of the isothermal flow of a 1.2 MWth CFBC unit were performed. Gas and inert material were modeled in an Eulerian fashion. Except from EMMS scheme, Gidaspow's correlation was also tested for reasons of comparison. Gidaspow's drag model is based on the assumption of homogeneous conditions inside a control volume, whilst the EMMS analysis encounters the effect of spatiotemporal multi-scale gas-particle structures on the induced drag force. Moreover, regarding the grid density, smaller control volumes enhance the validity of the homogeneous assumption. Thus, the effect of the grid density on the numerical results was also examined, using two uniform computational grids, consisting of hexahedral computational cells. Numerical results were compared with available experimental data, as far as the pressure drop along the bed is concerned. A good agreement with the experimental data was achieved in the case of the dense grid (43 mm/cell) using both approaches. In the case of the coarse grid (86 mm/cell), Gidaspow's correlation clearly under-predicted the experimentally measured pressure drop along the bed. This under-prediction was more significant in the lower part of the bed. On the other hand, the implementation of the EMMS scheme increased the accuracy of the model, mainly in the bottom region, since particles clustering was taken into account, a phenomenon which is more evident in latter region. In this area the drag force calculated via EMMS method is considerably less than the drag force calculated by Gidaspow's correlation. Overall, it is proven that the EMMS model is a very promising numerical tool for the more accurate drag force calculation since it reproduces numerically the effect of clustering mechanism on the time evolution of this complicated phenomenon, increasing the accuracy of the predictions without the need of denser numerical grids. © 2010 Elsevier Ltd. All rights reserved.	en
heal.journalName	Chemical Engineering Science	en
dc.identifier.doi	10.1016/j.ces.2010.03.053	en
dc.identifier.volume	65	en
dc.identifier.issue	13	en
dc.identifier.spage	4089	en
dc.identifier.epage	4099	en