Experimental investigation and modelling of continuous fluidized bed drying under steady-state and dynamic conditions

Burgschweiger, Jens; Tsotsas, Evangelos

doi:10.1016/s0009-2509(02)00424-4

Cited by 83 publications

(36 citation statements)

References 20 publications

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“…Due to availability at different sizes and previous experiences (Burgschweiger et al, 1999;Burgschweiger and Tsotsas, 2002), narrowly sieved fractions of -Al 2 O 3 particles have been used in the experimental investigations. Some properties (average particle diameter, dry particle density, packed bed porosity) are recapitulated in Table 7.…”

Section: Methodsmentioning

confidence: 99%

“…• The static and dynamic behaviour of continuously operated fluidized bed dryers (Burgschweiger and Tsotsas, 2002), again without indirect heating. This application required further expansion of the model, including population balances, which did not change any aspect of the model's fundamental structure and is not relevant for the present work.…”

Section: Drying Modulementioning

confidence: 99%

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Drying in fluidized beds with immersed heating elements

Groenewold

Tsotsas

2007

Chemical Engineering Science

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Section: Methodsmentioning

confidence: 99%

Section: Drying Modulementioning

confidence: 99%

Drying in fluidized beds with immersed heating elements

Groenewold

Tsotsas

2007

Chemical Engineering Science

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“…Despite the widespread application of fl uidized bed dryers, the development of effi cient and reliable modelling tools has been undermined by lack of systematic and well-documented data the literature [9].…”

Section: Nu-re Relationshipmentioning

confidence: 99%

Determination of entry length of a fluidized bed dryer using volumetric heat transfer coefficient

Poós

Szabó

2017

IRASE

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Fluidized bed dryers are widely used in several fi elds of industry. Suffi ciently accurate thermal models provide an opportunity to increase the effectiveness of dryers. The required size of a fl uidized bed dryer can be defi ned with the application of mathematical model. This work is aimed at developing mathematical model to investigate the infl uence of operating parameters in a fl uidized bed dryer using volumetric heat transfer coeffi cient. After the defi ning the input parameters of the differential equations, the required entry length of the dryer which effective heat and mass transfer between gas and particles takes place can be estimated. The correct estimation of the entry length is useful in optimal design of a fl uidized bed dryer. Using the model the impact of the drying parameters can be determined to the required length. Keywords: fl uidized bed dryer, heat and mass transfer, volumetric heat transfer coeffi cient, mathematical model

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“…A model extended in this way yields considerably better values for product moisture at the dryer outlet, as can be seen in Fig. 12 (Burgschweiger and Tsotsas 2002). Extensive experiments are currently being carried out, in which the distribution of outlet moisture is determined by gravimetric measurement of single particles.…”

Section: Population Balances: Distributed Product Quality In Fluidisementioning

confidence: 99%

Modern Modelling Methods in Drying

et al. 2006

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Several modern modelling techniques are presented as tools for drying science and technology, namely pore networks, discrete element method and population balances. After first presenting results from their own research, the authors indicate what future contributions to a better understanding of the drying process at different levels-single porous particles, agitated and fluidised beds-may be expected. NomenclatureA Pore throat cross section [m 2 ] c p Heat capacity [kJ kg −1 K −1 ] f Number density [m −3 kg −1 ] G Rate of drying/wetting [kg s −1 ] L Capillary or pore throat length [m] l Amount of liquid [kg] M Mass flow rate [kg s −1 ] M Molar mass [kg kmol −1 ] m l Liquid mass density [kg −3 ] N mix Mixing number [-] n Rotational frequency [s −1 ] n Number density [s −1 ] or [m −3 ] n Number flow rate [s −2 ] T. 104 Thomas Metzger et al. R Ideal gas constant [kJ kmol −1 K −1 ] p Pressure [Pa] r Radius [m] r 0 Mean radius [m] s Meniscus position [m] T Absolute temperature [K] t Time [s] t mix Revolution time [s] t R Mixing time [s] v Particle volume [m 3 ] z Space coordinate [m] Greek symbols α Heat transfer coefficient [W m −2 K −1 ] β Mass transfer coefficient [m s −1 ] β Agglomeration kernel [s −1 ] δ Binary diffusion coefficient [m 2 s −1 ] ζ Dimensionless position [-] η Dynamic viscosity [Pa s] λ Thermal conductivity [Wm −1 K −1 ] ν Dimensionless drying rate [-] ρ Density [kg m −3 ] σ Surface tension [N m −1 ] σ 0 Radius standard deviation [m] τ Age of particle [s] ψ Porosity [-]

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Experimental investigation and modelling of continuous fluidized bed drying under steady-state and dynamic conditions

Cited by 83 publications

References 20 publications

Drying in fluidized beds with immersed heating elements

Drying in fluidized beds with immersed heating elements

Determination of entry length of a fluidized bed dryer using volumetric heat transfer coefficient

Modern Modelling Methods in Drying

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