Access the full text.
Sign up today, get DeepDyve free for 14 days.
C. Wen, L. Fan (1975)
Models for flow systems and chemical reactors
J. Villermaux (1993)
Génie de la réaction chimique — conception et fonctionnement des réacteurs
(2002)
Génie des procédés alimentaires - des bases aux applications
(1993)
Génie de la réaction chimique - conception et fonctionnement des réacteurs, Lavoisier
P. Schuck (2002)
Spray drying of dairy products: state of the artLait, 82
P. Schuck, M. Roignant, G. Brûlé, Serge Mejean, J. Bimbenet (1998)
Caractérisation énergétique d'une tour de séchage par atomisation multiple effet, 115
(1991)
Spray Drying, Ed
M. Sougnez (1983)
L'évolution du séchage par atomisation
F. Ducept, M. Sionneau, J. Vasseur (2002)
Superheated steam dryer: simulations and experiments on product dryingChemical Engineering Journal, 86
R. Carr (1965)
EVALUATING FLOW PROPERTIES OF SOLIDSChemical Engineering, 72
K. Masters (1994)
SCALE-UP OF SPRAY DRYERSDrying Technology, 12
K. Masters (1991)
Spray Drying
P. Schuck, S. Méjean, A. Dolivet, R. Jeantet (2005)
Thermohygrometric sensor: A tool for optimizing the spray drying processInnovative Food Science and Emerging Technologies, 6
R. Verdurmen, H. Straatsma, M. Verschueren, J. Haren, E. Smit, G. Bargeman, P. Jong (2002)
Modelling spray drying processes for dairy productsLait, 82
Dairy powders are mainly obtained by spray drying, which is an effective process as it makes possible long-term storage at an ambient temperature. However, the control and design of this operation is still based on empirical knowledge. Improvement in product quality, which is governed by time/temperature history, thus involves greater understanding of the process via physico-chemical, thermodynamic and kinetic approaches. With regard to the latter, the residence time distribution (RTD) of the product provides valuable information about the product flow pattern in the dryer according to the operating conditions. The aim of this study was to determine the RTD of skim milk in a drying plant with different configurations, according to fine particle recycling (top of the chamber or internal fluid bed) and internal fluid bed thickness (4 to 16 cm). The RTD signal of the atomisation device was established first; then the RTD signals of the different spraydryer configurations were obtained by deconvolution of the experimental curves obtained and the RTD signal of the atomisation device, and modelled according to a combination of four reactor sets. The mean residence time of the product was only slightly modified by the dryer configuration (range 9.5 to 12 min). However, the results showed that a thicker internal fluid bed tends to increase mean residence time due to higher product retention, whereas top recycling of fine particles tends to decrease the mean residence time because of better agglomeration. RTD modelling provides additional information concerning the product flow rate fraction and the residence time distribution of each part of the dryer (chamber, cyclones and fluid bed), indicating that 60 to 80% of the powder passes through the cyclones, depending on the configuration. This study provides greater understanding of dryer operation, and allows further correlation between process parameters and biochemical changes (protein denaturation, Maillard reaction, etc.).
Dairy Science & Technology – Springer Journals
Published: May 21, 2011
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.