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    Structural Design Space Exploration Using Principal Component Analysis

    Source: Journal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 006::page 061014-1
    Author:
    Bunnell, Spencer
    ,
    Gorrell, Steven
    ,
    Salmon, John
    ,
    Thelin, Christopher
    ,
    Ruoti, Christopher
    DOI: 10.1115/1.4047428
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Design space exploration (DSE) is the process whereby a designer seeks to understand some results across a set of design variations. Structural DSE of turbomachinery compressor blades is often challenging because the large number of design variables make it difficult to learn the effect that each variable has upon the stress contours. Principal component analysis (PCA) of the stress contours is used as a way to understand how the stress contours change over the design space. Two methods are introduced to address the challenge of understanding how the stress changes over a large number of variables. First, a two-point correlation is applied to relate the design variables to the scores of each principal component. Second, a coupling of the stress and coordinate location of each node in PCA is developed which also indicates how the stress variations relate to geometric variations. These provide insight to how design variables influence the stress. It is shown how these methods use PCA as DSE tools to better explore the structural design space of compressor blades. Better DSE can improve compressor blades and the computational cost needed for their design.
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      Structural Design Space Exploration Using Principal Component Analysis

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4274923
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    contributor authorBunnell, Spencer
    contributor authorGorrell, Steven
    contributor authorSalmon, John
    contributor authorThelin, Christopher
    contributor authorRuoti, Christopher
    date accessioned2022-02-04T22:07:30Z
    date available2022-02-04T22:07:30Z
    date copyright7/9/2020 12:00:00 AM
    date issued2020
    identifier issn1530-9827
    identifier otherjcise_20_6_061014.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4274923
    description abstractDesign space exploration (DSE) is the process whereby a designer seeks to understand some results across a set of design variations. Structural DSE of turbomachinery compressor blades is often challenging because the large number of design variables make it difficult to learn the effect that each variable has upon the stress contours. Principal component analysis (PCA) of the stress contours is used as a way to understand how the stress contours change over the design space. Two methods are introduced to address the challenge of understanding how the stress changes over a large number of variables. First, a two-point correlation is applied to relate the design variables to the scores of each principal component. Second, a coupling of the stress and coordinate location of each node in PCA is developed which also indicates how the stress variations relate to geometric variations. These provide insight to how design variables influence the stress. It is shown how these methods use PCA as DSE tools to better explore the structural design space of compressor blades. Better DSE can improve compressor blades and the computational cost needed for their design.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleStructural Design Space Exploration Using Principal Component Analysis
    typeJournal Paper
    journal volume20
    journal issue6
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4047428
    journal fristpage061014-1
    journal lastpage061014-10
    page10
    treeJournal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 006
    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