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    A Methodology for Determining Experimental Uncertainties in Regressions

    Source: Journal of Fluids Engineering:;1998:;volume( 120 ):;issue: 003::page 445
    Author:
    K. K. Brown
    ,
    H. W. Coleman
    ,
    W. Glenn Steele
    DOI: 10.1115/1.2820683
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A methodology to determine the experimental uncertainties associated with regressions is presented. When a regression model is used to represent experimental information, the uncertainty associated with the model is affected by random, systematic, and correlated systematic uncertainties associated with the experimental data. The key to the proper estimation of the uncertainty associated with a regression is a careful, comprehensive accounting of systematic and correlated systematic uncertainties. The methodology presented in this article is developed by applying uncertainty propagation techniques to the linear regression analysis equations. The effectiveness of this approach was investigated and proven using Monte Carlo simulations. The application of that methodology to the calibration of a venturi flowmeter and its subsequent use to determine flowrate in a test is demonstrated. It is shown that the previously accepted way of accounting for the contribution of discharge coefficient uncertainty to the overall flowrate uncertainty does not correctly account for all uncertainty sources, and the appropriate approach is developed, discussed, and demonstrated.
    keyword(s): Flowmeters , Engineering simulation , Calibration , Discharge coefficient , Equations , Regression analysis , Regression models , Venturi tubes AND Uncertainty ,
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      A Methodology for Determining Experimental Uncertainties in Regressions

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/120602
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    • Journal of Fluids Engineering

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    contributor authorK. K. Brown
    contributor authorH. W. Coleman
    contributor authorW. Glenn Steele
    date accessioned2017-05-08T23:56:55Z
    date available2017-05-08T23:56:55Z
    date copyrightSeptember, 1998
    date issued1998
    identifier issn0098-2202
    identifier otherJFEGA4-27132#445_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/120602
    description abstractA methodology to determine the experimental uncertainties associated with regressions is presented. When a regression model is used to represent experimental information, the uncertainty associated with the model is affected by random, systematic, and correlated systematic uncertainties associated with the experimental data. The key to the proper estimation of the uncertainty associated with a regression is a careful, comprehensive accounting of systematic and correlated systematic uncertainties. The methodology presented in this article is developed by applying uncertainty propagation techniques to the linear regression analysis equations. The effectiveness of this approach was investigated and proven using Monte Carlo simulations. The application of that methodology to the calibration of a venturi flowmeter and its subsequent use to determine flowrate in a test is demonstrated. It is shown that the previously accepted way of accounting for the contribution of discharge coefficient uncertainty to the overall flowrate uncertainty does not correctly account for all uncertainty sources, and the appropriate approach is developed, discussed, and demonstrated.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Methodology for Determining Experimental Uncertainties in Regressions
    typeJournal Paper
    journal volume120
    journal issue3
    journal titleJournal of Fluids Engineering
    identifier doi10.1115/1.2820683
    journal fristpage445
    journal lastpage456
    identifier eissn1528-901X
    keywordsFlowmeters
    keywordsEngineering simulation
    keywordsCalibration
    keywordsDischarge coefficient
    keywordsEquations
    keywordsRegression analysis
    keywordsRegression models
    keywordsVenturi tubes AND Uncertainty
    treeJournal of Fluids Engineering:;1998:;volume( 120 ):;issue: 003
    contenttypeFulltext
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