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    Identification of Plastic Properties From Conical Indentation Using a Bayesian-Type Statistical Approach

    Source: Journal of Applied Mechanics:;2019:;volume( 086 ):;issue: 001::page 11002
    Author:
    Zhang, Yupeng
    ,
    Hart, Jeffrey D.
    ,
    Needleman, Alan
    DOI: 10.1115/1.4041352
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The plastic properties that characterize the uniaxial stress–strain response of a plastically isotropic material are not uniquely related to the indentation force versus indentation depth response. We consider results for three sets of plastic material properties that give rise to essentially identical curves of indentation force versus indentation depth in conical indentation. The corresponding surface profiles after unloading are also calculated. These computed results are regarded as the “experimental” data. A simplified Bayesian-type statistical approach is used to identify the values of flow strength and strain hardening exponent for each of the three sets of material parameters. The effect of fluctuations (“noise”) superposed on the “experimental” data is also considered. We build the database for the Bayesian-type analysis using finite element calculations for a relatively coarse set of parameter values and use interpolation to refine the database. A good estimate of the uniaxial stress–strain response is obtained for each material both in the absence of fluctuations and in the presence of sufficiently small fluctuations. Since the indentation force versus indentation depth response for the three materials is nearly identical, the predicted uniaxial stress–strain response obtained using only surface profile data differs little from what is obtained using both indentation force versus indentation depth and surface profile data. The sensitivity of the representation of the predicted uniaxial stress–strain response to fluctuations increases with increasing strain hardening. We also explore the sensitivity of the predictions to the degree of database refinement.
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      Identification of Plastic Properties From Conical Indentation Using a Bayesian-Type Statistical Approach

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    contributor authorZhang, Yupeng
    contributor authorHart, Jeffrey D.
    contributor authorNeedleman, Alan
    date accessioned2019-03-17T10:09:26Z
    date available2019-03-17T10:09:26Z
    date copyright10/1/2018 12:00:00 AM
    date issued2019
    identifier issn0021-8936
    identifier otherjam_086_01_011002.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4255953
    description abstractThe plastic properties that characterize the uniaxial stress–strain response of a plastically isotropic material are not uniquely related to the indentation force versus indentation depth response. We consider results for three sets of plastic material properties that give rise to essentially identical curves of indentation force versus indentation depth in conical indentation. The corresponding surface profiles after unloading are also calculated. These computed results are regarded as the “experimental” data. A simplified Bayesian-type statistical approach is used to identify the values of flow strength and strain hardening exponent for each of the three sets of material parameters. The effect of fluctuations (“noise”) superposed on the “experimental” data is also considered. We build the database for the Bayesian-type analysis using finite element calculations for a relatively coarse set of parameter values and use interpolation to refine the database. A good estimate of the uniaxial stress–strain response is obtained for each material both in the absence of fluctuations and in the presence of sufficiently small fluctuations. Since the indentation force versus indentation depth response for the three materials is nearly identical, the predicted uniaxial stress–strain response obtained using only surface profile data differs little from what is obtained using both indentation force versus indentation depth and surface profile data. The sensitivity of the representation of the predicted uniaxial stress–strain response to fluctuations increases with increasing strain hardening. We also explore the sensitivity of the predictions to the degree of database refinement.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleIdentification of Plastic Properties From Conical Indentation Using a Bayesian-Type Statistical Approach
    typeJournal Paper
    journal volume86
    journal issue1
    journal titleJournal of Applied Mechanics
    identifier doi10.1115/1.4041352
    journal fristpage11002
    journal lastpage011002-9
    treeJournal of Applied Mechanics:;2019:;volume( 086 ):;issue: 001
    contenttypeFulltext
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