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    Optimization of solid circualtion rate in compartmented fluidized bed gasifier for power generation

    Access Status
    Fulltext not available
    Authors
    Chok, Vui
    Wee, Siaw
    Gorin, Alexander
    Chua, Han
    Mohd. Ariffin, M.Z.
    Yan, H.M.
    Date
    2008
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Chok, Vui and Wee, Siaw and Gorin, Alexander and Chua, Han. 2008. Optimization of solid circualtion rate in compartmented fluidized bed gasifier for power generation, in Barsoum, N. (ed), International Conference on Power Control and Optimzation: Innovation in Power Control for Optimal Industry, Jul 18 2008, pp. 301-304. Chiang Mai, Thailand: American Institute of Physics.
    Source Title
    AIP Conference Proceedings 2008
    Source Conference
    International Conference on Power Control and Optimzation
    DOI
    10.1063/1.3008684
    ISBN
    978-0-7354-0581-3
    Faculty
    Faculty Office
    Curtin Sarawak Campus
    School
    Curtin Sarawak - Faculty Office
    Remarks

    Copyright © 2008 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.

    This article appeared in AIP Conf. Proc. Volume 1052 Issue 1 and may be found at: http://link.aip.org/link/?APCPCS/1052/301/1

    URI
    http://hdl.handle.net/20.500.11937/4448
    Collection
    • Curtin Research Publications
    Abstract

    The present paper reports the optimization of solid circulation rate (SCR) in Compartmented Fluidized Bed Gasifier (CFBG), an indirectly heated fluidized bed that incorporates two sets of v-valves and risers to control the solid circulation across the two compartments, i.e. combustor and gasifier of a pilot plant scale (the height and ID are 1.8m and 0.66m respectively). Sand was used as inert fluidized by air. Four operating variables were studied i.e. bed height, riser, v-valve and main bed flowrate. Based on (2)*4 full factorial design of experiment in Yates' algorithm, at confidence level >=95%, ANOVA analysis showed that there are 6 important effects. The steepest ascent method was applied on linear regression generated from these effects to design the subsequent optimization experiments. The optimum values of SCR have been estimated for both low and high bed level at specific operating parameters.

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