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    Selecting dryer type using fuzzy logic

    , Article CHISA 2006 - 17th International Congress of Chemical and Process Engineering, Prague, 27 August 2006 through 31 August 2006 ; 2006 ; 8086059456 (ISBN); 9788086059457 (ISBN) Shariati, R. P ; Sharif University of Technology
    2006
    Abstract
    Due to variety of industrial dryers and also importance of selecting appropriate dryer to achieve the required quality of product as well as considering economical aspects, using methods and algorithms which take all effective factors into account and present the best selection is regarded by engineers and researchers. In this paper selection of dryer applying fuzzy logic is presented and the advantages of this method are investigated. For this a program is written using MATLAB programming software and its result compared with real cases. It has been found that there is a good agreement between the prepared program results and industrial experiences. Selection of dryer for a specific... 

    H∞ Robust control of continuous fluidized tea bed dryer

    , Article ASME International Mechanical Engineering Congress and Exposition, Proceedings, 13 November 2009 through 19 November 2009, Lake Buena Vista, FL ; Volume 10, Issue PART A , 2010 , Pages 321-327 ; 9780791843833 (ISBN) Moradl, H ; Hajikolaei, K. H ; Motamedi, M ; Vossoughi, G. R ; Sharif University of Technology
    American Society of Mechanical Engineers (ASME)  2010
    Abstract
    During drying processes, moisture control of food products, such as dried tea, is of great importance. Improving dryer control, results in consistent production and reduction of energy consumption. However, the dryer is a complex system associated with model uncertainties. In this paper, a realistic uncertain model of a fluidized tea bed dryer is considered. Moisture content and temperature of tea leaves (or other products) are controlled at desired values by manipulating tea leaves heating rate. Developing a code by Robust Control Toolbox of MATLAB and modeling uncertainties, a robust controller is designed based on ′-synthesis with DK-iteration algorithm. Results show that in the presence... 

    Moisture diffusivity and shrinkage of broad beans during bulk drying in an inert medium fluidized bed dryer assisted by dielectric heating

    , Article Journal of Food Engineering ; Volume 92, Issue 3 , 2009 , Pages 331-338 ; 02608774 (ISSN) Hashemi, G ; Mowla, D ; Kazemeini, M ; Sharif University of Technology
    2009
    Abstract
    Drying behavior of broad beans (Vicia faba) was studied in a pilot scaled fluidized bed dryer with inert particles assisted by dielectric heating. The effective diffusion coefficient of moisture transfer was determined by Fickian method at four different air drying temperatures of 35, 45, 55 and 65 °C. Correlations for moisture diffusivity as a function of moisture content and temperature of the drying medium were developed. The values of moisture diffusivity were obtained within the range of 1.27 × 10-9-6.48 × 10-9 m2/s and the activation energies for FBD and FBD + DE were found to be 27.71 and 17.10 kJ/mol, respectively. The shrinkage behavior of the broad beans was also investigated by... 

    Determination of a suitable thin layer drying curve model for saffron (Crocus sativus L) stigmas in an infrared dryer

    , Article Scientia Iranica ; Volume 18, Issue 6 , 2011 , Pages 1397-1401 ; 10263098 (ISSN) Akhondi, E ; Kazemi, A ; Maghsoodi, V ; Sharif University of Technology
    Abstract
    The drying of saffron stigma was investigated in a laboratory infrared dryer. The effect of temperature on the drying rate of samples at various temperatures (60,70...110 °C) was studied. The drying time decreased with an increase in drying air temperature. The constant-rate period is absent from the drying curve. The drying of saffron occurred in the falling rate period. Four, thin-layer drying models, namely, Lewis, Handerson and Pabis, Page, and Midilli and Kucuk, were fitted to drying data. The performance of these models was investigated by comparing the determination of coefficient ( R2) and Root Mean Square Error (RMSE) between the observed and predicted moisture ratios. Among these...