Simulating Industrial Spray-Drying Operations Using a Reaction Engineering Approach and a Modified Desorption Method

Zhu, Peng; Patel, Kamleshkumar Chhanabhai; Lin, Steven; Méjean, Serge; Blanchard, Eric; Chen, Xiao; Schuck, Pierre; Jeantet, Romain

doi:10.1080/07373937.2010.501928

Cited by 21 publications

(13 citation statements)

References 14 publications

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“…In other words, this equation is the "fingerprint" of a material's drying behavior. These kinetics data can be implemented into simulation programs home-made [41,42] or commercially available computational fluid dynamics modeling software with specific user established operating files for scale up studies and industrial spray dryer design [43][44][45][46].…”

Section: Drying Modeling Based On Single Droplet Experimentsmentioning

confidence: 99%

Drying colloidal systems: Laboratory models for a wide range of applications

et al. 2018

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Abstract. The drying of complex fluids provides a powerful insight into phenomena that take place on time and length scales not normally accessible. An important feature of complex fluids, colloidal dispersions and polymer solutions is their high sensitivity to weak external actions. Thus, the drying of complex fluids involves a large number of physical and chemical processes. The scope of this review is the capacity to tune such systems to reproduce and explore specific properties in a physics laboratory. A wide variety of systems are presented, ranging from functional coatings, food science, cosmetology, medical diagnostics and forensics to geophysics and art.

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Section: Drying Modeling Based On Single Droplet Experimentsmentioning

confidence: 99%

Drying colloidal systems: Laboratory models for a wide range of applications

et al. 2018

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“…Among the theoretical drying models available are the characteristic drying curve approach, the diffusion based model, and the reaction engineering approach (REA) (Fyhr and Kemp 1998;Mezhericher et al 2010). The robustness of REA in predicting drying performance, as well as for process design evaluation, has been demonstrated in various case studies (Woo et al 2008;Zhu et al 2011;Putranto et al 2011a,b;Rogers et al 2012). This approach only requires a small number of accurate experimental runs and does not require many coefficients that are experimentally difficult to obtain, in order to be applied for a dryer-wide modelling (Putranto et al 2010).…”

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confidence: 99%

Capturing the effect of initial concentrations on the drying kinetics of high solids milk using reaction engineering approach

Chew

Woo

et al. 2013

Dairy Sci. & Technol.

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Many industries practice trial and error method to achieve optimum process conditions for desired powdered product quality in the event of fluctuations in the feed concentration, which happens more often than not and leads to wastage in product, time and energy. This paper presents the thermal-moisture drying histories for skim milk droplets from 37 to 43 wt%, in order to study the effects of initial solids variation on drying kinetics. The changes in droplet temperature, diameter and moisture content during drying were directly obtained using a glass filament single droplet drying technique. The experimental data were interpreted using the reaction engineering approach, an activation energy-based model where drying is dependent on vapour density gradient at the material-air interface. It was shown that the drying profile was sensitive to the initial solid content of droplet at this range of concentrations, since attempts to apply a single master activation energy curve to describe drying kinetics yielded less accurate predictions. The model's predictions were validated experimentally for both moisture content and temperature profiles during drying. The proposed approach enables drying histories of high solids milk to be modelled more accurately and could potentially assist in evaluating process design for high solids milk drying.

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“…This approach has been tested for over 30 different dairy concentrates and several spray dryers according to different scales (from 5 kg h À1 to 6 t h À1 ). A good match between measured and predicted parameters (±1-5% error) has been reported Zhu et al, 2011). A predictive tool based on this drying by desorption method is now marketed under the name 'Spray drying parameter simulation and determination software' SD 2 P Ò in order to determine or optimize the key process parameters.…”

Section: Introductionmentioning

confidence: 94%

“…As shown in figure 1, drying by desorption can be divided into two periods: the constant evaporation rate stage (from the beginning to about 100 min for a skim milk concentrate at 40% TS, which includes a preheating stage for the first 10 min (not visible in figure 1) (Zhu et al, 2011)) and the decreasing evaporation rate stage (time above 100 min.). The boundary between these two periods can slightly vary for different concentrates.…”

Section: Calculation Of Evaporation Ratementioning

confidence: 99%