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    Gradient Span Analysis Method: Application to the Multipoint Aerodynamic Shape Optimization of a Turbine Cascade

    Source: Journal of Turbomachinery:;2015:;volume( 137 ):;issue: 009::page 91006
    Author:
    Montanelli, Hadrien
    ,
    Montagnac, Marc
    ,
    Gallard, Franأ§ois
    DOI: 10.1115/1.4030016
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper presents the application of the gradient span analysis (GSA) method to the multipoint optimization of the twodimensional LS89 turbine distributor. The cost function (total pressure loss) and the constraint (mass flow rate) are computed from the resolution of the Reynoldsaveraged Navier–Stokes equations. The penalty method is used to replace the constrained optimization problem with an unconstrained problem. The optimization process is steered by a gradientbased quasiNewton algorithm. The gradient of the cost function with respect to design variables is obtained with the discrete adjoint method, which ensures an efficient computation time independent of the number of design variables. The GSA method gives a minimal set of operating conditions to insert into the weighted sum model to solve the multipoint optimization problem. The weights associated to these conditions are computed with the utopia point method. The singlepoint optimization at the nominal condition and the multipoint optimization over a wide range of conditions of the LS89 blade are compared. The comparison shows the strong advantages of the multipoint optimization with the GSA method and utopiapoint weighting over the traditional singlepoint optimization.
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      Gradient Span Analysis Method: Application to the Multipoint Aerodynamic Shape Optimization of a Turbine Cascade

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    http://yetl.yabesh.ir/yetl1/handle/yetl/159966
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    contributor authorMontanelli, Hadrien
    contributor authorMontagnac, Marc
    contributor authorGallard, Franأ§ois
    date accessioned2017-05-09T01:24:43Z
    date available2017-05-09T01:24:43Z
    date issued2015
    identifier issn0889-504X
    identifier otherturbo_137_09_091006.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/159966
    description abstractThis paper presents the application of the gradient span analysis (GSA) method to the multipoint optimization of the twodimensional LS89 turbine distributor. The cost function (total pressure loss) and the constraint (mass flow rate) are computed from the resolution of the Reynoldsaveraged Navier–Stokes equations. The penalty method is used to replace the constrained optimization problem with an unconstrained problem. The optimization process is steered by a gradientbased quasiNewton algorithm. The gradient of the cost function with respect to design variables is obtained with the discrete adjoint method, which ensures an efficient computation time independent of the number of design variables. The GSA method gives a minimal set of operating conditions to insert into the weighted sum model to solve the multipoint optimization problem. The weights associated to these conditions are computed with the utopia point method. The singlepoint optimization at the nominal condition and the multipoint optimization over a wide range of conditions of the LS89 blade are compared. The comparison shows the strong advantages of the multipoint optimization with the GSA method and utopiapoint weighting over the traditional singlepoint optimization.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleGradient Span Analysis Method: Application to the Multipoint Aerodynamic Shape Optimization of a Turbine Cascade
    typeJournal Paper
    journal volume137
    journal issue9
    journal titleJournal of Turbomachinery
    identifier doi10.1115/1.4030016
    journal fristpage91006
    journal lastpage91006
    identifier eissn1528-8900
    treeJournal of Turbomachinery:;2015:;volume( 137 ):;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