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    Grain Temperature-Dependent Thermal Properties Estimation Using FI-QPSO Algorithm

    Source: Journal of Heat Transfer:;2021:;volume( 143 ):;issue: 009::page 093501-1
    Author:
    Xu, Hongmei
    ,
    Liu, Juan
    ,
    Wang, Kun
    ,
    Kong, Songtao
    ,
    Shi, Yong
    DOI: 10.1115/1.4051701
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A hybrid fuzzy inference-quantum particle swarm optimization (FI-QPSO) algorithm is developed to estimate the temperature-dependent thermal properties of the grain. The fuzzy inference scheme is established to determine the contraction-expansion coefficient according to the aggregation degree of particles. The heat transfer process in the grain bulk is solved using the finite element method, and the estimation task is formulated as an inverse problem. Numerical experiments are performed to study the effects of the surface heat flux, measurement errors, and the individual space on the estimation results. Comparison with the quantum particle swarm optimization (QPSO) algorithm and conjugate gradient method (CGM) is also conducted, and it shows the validity of the estimation method established in this paper.
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      Grain Temperature-Dependent Thermal Properties Estimation Using FI-QPSO Algorithm

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4278314
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    contributor authorXu, Hongmei
    contributor authorLiu, Juan
    contributor authorWang, Kun
    contributor authorKong, Songtao
    contributor authorShi, Yong
    date accessioned2022-02-06T05:34:32Z
    date available2022-02-06T05:34:32Z
    date copyright7/30/2021 12:00:00 AM
    date issued2021
    identifier issn0022-1481
    identifier otherht_143_09_093501.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4278314
    description abstractA hybrid fuzzy inference-quantum particle swarm optimization (FI-QPSO) algorithm is developed to estimate the temperature-dependent thermal properties of the grain. The fuzzy inference scheme is established to determine the contraction-expansion coefficient according to the aggregation degree of particles. The heat transfer process in the grain bulk is solved using the finite element method, and the estimation task is formulated as an inverse problem. Numerical experiments are performed to study the effects of the surface heat flux, measurement errors, and the individual space on the estimation results. Comparison with the quantum particle swarm optimization (QPSO) algorithm and conjugate gradient method (CGM) is also conducted, and it shows the validity of the estimation method established in this paper.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleGrain Temperature-Dependent Thermal Properties Estimation Using FI-QPSO Algorithm
    typeJournal Paper
    journal volume143
    journal issue9
    journal titleJournal of Heat Transfer
    identifier doi10.1115/1.4051701
    journal fristpage093501-1
    journal lastpage093501-7
    page7
    treeJournal of Heat Transfer:;2021:;volume( 143 ):;issue: 009
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian