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    Putting Statistics into the Statistical Energy Analysis of Automotive Vehicles

    Source: Journal of Vibration and Acoustics:;1997:;volume( 119 ):;issue: 004::page 629
    Author:
    C. J. Radcliffe
    ,
    X. L. Huang
    DOI: 10.1115/1.2889773
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Sound and vibration transmission modeling methods are important to the design process for high quality automotive vehicles. Statistical Energy Analysis (SEA) is an emerging design tool for the automotive industry that was initially developed in the 1960’s to estimate root-mean-square sound and vibration levels in structures and interior spaces. Although developed to estimate statistical mean values, automotive design application of SEA needs the additional ability to predict statistical variances of the predicted mean values of sound and vibration. This analytical ability would allow analysis of vehicle sound and vibration response sensitivity to changes in vehicle design specifications and their statistical distributions. This paper will present an algorithm to extend the design application of the SEA method through prediction of the variances of RMS. responses of vibro-acoustic automobile structures and interior spaces from variances in SEA automotive model physical parameters. The variance analysis is applied to both a simple, complete illustrative example and a more complex automotive vehicle example. Example variance results are verified through comparison with a Monte Carlo test of 2,000 SEA responses whose physical parameters were given Gaussian distributions with means at design values. Analytical predictions of the response statistics agree with the statistics generated by the Monte Carlo method but only require about 1/300 of the computational effort.
    keyword(s): Automobiles , Seas , Sound , Design , Vibration , Space , Automotive design , Gaussian distribution , Monte Carlo methods , Statistical distributions , Algorithms , Automotive industry , Acoustics , Modeling AND Vehicles ,
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      Putting Statistics into the Statistical Energy Analysis of Automotive Vehicles

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    contributor authorC. J. Radcliffe
    contributor authorX. L. Huang
    date accessioned2017-05-08T23:55:16Z
    date available2017-05-08T23:55:16Z
    date copyrightOctober, 1997
    date issued1997
    identifier issn1048-9002
    identifier otherJVACEK-28840#629_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/119693
    description abstractSound and vibration transmission modeling methods are important to the design process for high quality automotive vehicles. Statistical Energy Analysis (SEA) is an emerging design tool for the automotive industry that was initially developed in the 1960’s to estimate root-mean-square sound and vibration levels in structures and interior spaces. Although developed to estimate statistical mean values, automotive design application of SEA needs the additional ability to predict statistical variances of the predicted mean values of sound and vibration. This analytical ability would allow analysis of vehicle sound and vibration response sensitivity to changes in vehicle design specifications and their statistical distributions. This paper will present an algorithm to extend the design application of the SEA method through prediction of the variances of RMS. responses of vibro-acoustic automobile structures and interior spaces from variances in SEA automotive model physical parameters. The variance analysis is applied to both a simple, complete illustrative example and a more complex automotive vehicle example. Example variance results are verified through comparison with a Monte Carlo test of 2,000 SEA responses whose physical parameters were given Gaussian distributions with means at design values. Analytical predictions of the response statistics agree with the statistics generated by the Monte Carlo method but only require about 1/300 of the computational effort.
    publisherThe American Society of Mechanical Engineers (ASME)
    titlePutting Statistics into the Statistical Energy Analysis of Automotive Vehicles
    typeJournal Paper
    journal volume119
    journal issue4
    journal titleJournal of Vibration and Acoustics
    identifier doi10.1115/1.2889773
    journal fristpage629
    journal lastpage634
    identifier eissn1528-8927
    keywordsAutomobiles
    keywordsSeas
    keywordsSound
    keywordsDesign
    keywordsVibration
    keywordsSpace
    keywordsAutomotive design
    keywordsGaussian distribution
    keywordsMonte Carlo methods
    keywordsStatistical distributions
    keywordsAlgorithms
    keywordsAutomotive industry
    keywordsAcoustics
    keywordsModeling AND Vehicles
    treeJournal of Vibration and Acoustics:;1997:;volume( 119 ):;issue: 004
    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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