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    Estimating the Probabilistic Size and Shape Distributions of 3D Anomalies From Sectioning Measurements Using the Stereological Unfolding Approach

    Source: Journal of Engineering for Gas Turbines and Power:;2012:;volume( 134 ):;issue: 005::page 52506
    Author:
    Wuwei Liang
    ,
    Michael P. Enright
    DOI: 10.1115/1.4004727
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The accuracy of probabilistic risk assessment of rotor disks is strongly dependent on the accurate description of the size and shape distributions of anomalies in alloys. These size-shape distributions of anomalies are often derived from planar sectioning data measurements using stereological unfolding algorithms. Since it is impossible to accurately predict the shape and orientation parameters of a general ellipsoid based on measurements obtained from two-dimensional sectioning data, the anomaly model should be limited to a spheroid. In this study, an unfolding algorithm was implemented and verified that can be used to estimate the probabilistic dimensions and orientations of 3D spheroids based on 2D section data. It is shown that the accuracy of the predicted spheroid model is dependent on the number of sections and the discretization of the mesh used to characterize the data.
    keyword(s): Dimensions , Algorithms , Equations , Measurement , Shapes , Particulate matter AND Risk assessment ,
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      Estimating the Probabilistic Size and Shape Distributions of 3D Anomalies From Sectioning Measurements Using the Stereological Unfolding Approach

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    http://yetl.yabesh.ir/yetl1/handle/yetl/148852
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    contributor authorWuwei Liang
    contributor authorMichael P. Enright
    date accessioned2017-05-09T00:50:21Z
    date available2017-05-09T00:50:21Z
    date copyrightMay, 2012
    date issued2012
    identifier issn1528-8919
    identifier otherJETPEZ-27192#052506_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/148852
    description abstractThe accuracy of probabilistic risk assessment of rotor disks is strongly dependent on the accurate description of the size and shape distributions of anomalies in alloys. These size-shape distributions of anomalies are often derived from planar sectioning data measurements using stereological unfolding algorithms. Since it is impossible to accurately predict the shape and orientation parameters of a general ellipsoid based on measurements obtained from two-dimensional sectioning data, the anomaly model should be limited to a spheroid. In this study, an unfolding algorithm was implemented and verified that can be used to estimate the probabilistic dimensions and orientations of 3D spheroids based on 2D section data. It is shown that the accuracy of the predicted spheroid model is dependent on the number of sections and the discretization of the mesh used to characterize the data.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleEstimating the Probabilistic Size and Shape Distributions of 3D Anomalies From Sectioning Measurements Using the Stereological Unfolding Approach
    typeJournal Paper
    journal volume134
    journal issue5
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4004727
    journal fristpage52506
    identifier eissn0742-4795
    keywordsDimensions
    keywordsAlgorithms
    keywordsEquations
    keywordsMeasurement
    keywordsShapes
    keywordsParticulate matter AND Risk assessment
    treeJournal of Engineering for Gas Turbines and Power:;2012:;volume( 134 ):;issue: 005
    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
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