A simple and coherent set of coefficients for modelling of heat and mass transport with and without chemical reaction in tubes filled with spheres

Winterberg, Markus; Tsotsas, Evangelos; Krischke, A.; Vortmeyer, D.

doi:10.1016/s0009-2509(99)00379-6

Cited by 153 publications

(93 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Liu et al [18], who observed pressure drop overshoots in a thin fluidized bed, interpreted the pressure changes by the classical Ergun model extended to an additional term which translated viscous effects of the wall. In fact, pressure drops were found to be mainly driven by porosity profiles, which in low aspect ratio packed beds are not constant but change along the radial coordinates [19]. In this work, a fluidized bed with an aspect ratio of 16.7 is operated at static and minimum bubbling conditions in order to ensure two types of radial porosity profiles.…”

Section: Introductionmentioning

confidence: 99%

Screening wall effects of a thin fluidized bed by near-infrared imaging

Aiouache

tSaoir

Kitagawa

2011

Chemical Engineering Journal

View full text Add to dashboard Cite

a b s t r a c tNear-infrared (NIR) imaging was used to observe water vapour flow in a gas-solid fluidized bed reactor. The technique consisted of a broadband light, an optical filter with a bandwidth centred on strong water vapour absorptions, a Vidicon NIR camera, a nozzle from which an optically active mixture of gas and water vapour was trans-illuminated by an NIR beam and collected data of transmittance were normalized to actual optical path. The procedure was applied to a thin fluidized bed reactor with a low aspect ratio of tube to particle diameters (D t /d p ) in order to validate the wall effect on flow dynamics and mass transfer during the reduction of ceria-silica by hydrogen. High concentrations of water vapour emerged in the vicinity of the wall when the bed was operated at pseudo-static conditions but disappeared when the bed was run at minimum bubbling conditions. This result shows the capability of optical methods with affordable costs to 2D imaging opaque packed bed by using a spatially resolved probe located at the exit, which is of great benefit for in situ visualization of anisotropic concentrations in packed beds under industrially relevant conditions and thus for elucidation of the underlying reaction mechanism and diffusion interactions.Crown

show abstract

Section: Introductionmentioning

confidence: 99%

Screening wall effects of a thin fluidized bed by near-infrared imaging

Aiouache

tSaoir

Kitagawa

2011

Chemical Engineering Journal

View full text Add to dashboard Cite

show abstract

“…Thus the model cannot predict the velocity maximum in the vicinity of the wall observed experimentally for those reactors [56]. An averaged velocity with a radially varying axial component can be provided by a further modification of the momentum balance [56][57][58] as an improvement of the classical model. The reader is referred to the textbook by Keil [54] and references therein.…”

Section: Modeling Gaseous Transport In Porous Catalystsmentioning

confidence: 97%

Modeling of the Interactions Between Catalytic Surfaces and Gas-Phase

Deutschmann

2014

Catal Lett

View full text Add to dashboard Cite

The catalytic surface interacts with the gasphase by a variety of chemical and physical processes. Hence, optimization of design and operation conditions of catalytic reactors do not only require the understanding of the catalytic reaction sequence but also its coupling with mass and heat transport and potential homogeneous reactions. The chemical, thermal, and mass-transport interactions between the catalytic surface and the gas-phase are discussed in terms of the individual and combined interactions. The state-of-the-art modelling of reactive flows and its coupling with the catalytic surface is summarized. The interactions are illustrated by a number of examples such as reforming of hydrocarbons, catalytic combustion, exhaust-gas after-treatment, each focusing on a special aspect of catalyst-gas interactions. The potentials and limitations of the numerical simulations will be discussed including experimental techniques for model validation.

show abstract

“…Winterberg et al [46] reviewed experiments with spherical particles and derived a simple and consistent set of coefficients based on uneven flow distributions and wall heat conduction model. Distribution of both flow and porosity has been approximated by the extended Brinkmann equation and an exponential expression according to Giese et al [47,48].…”

Section: One-phase (Homogeneous) Modelsmentioning

confidence: 99%

Simulation of thermal conversion of solid fuel by the discrete particle method

Peters¹,

Džiugys²,

Navakas³

2011

Lith. J. Phys.

View full text Add to dashboard Cite

We introduce the discrete particle method (DPM) that derives from the discrete element method (DEM). This is an advanced numerical simulation tool that takes into account both motion and chemical conversion of granular material, such as coal or biomass, in furnaces in conjunction with computational fluid dynamics (CFD). However, predictions of solely motion or conversion in a decoupled mode are also applicable. The DPM uses object oriented computational techniques that support objects representing three-dimensional particles of various shapes, size, and physical properties of particle material. This makes DPM a highly versatile tool in dealing with a variety of problems related to different industrial applications of granular matter. A review of literature concerning different approaches to mass and heat transfer in packed beds is presented.

show abstract

A simple and coherent set of coefficients for modelling of heat and mass transport with and without chemical reaction in tubes filled with spheres

Cited by 153 publications

References 39 publications

Screening wall effects of a thin fluidized bed by near-infrared imaging

Screening wall effects of a thin fluidized bed by near-infrared imaging

Modeling of the Interactions Between Catalytic Surfaces and Gas-Phase

Simulation of thermal conversion of solid fuel by the discrete particle method

Contact Info

Product

Resources

About