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    Maximizing Design Confidence in Sequential Simulation Based Optimization

    Source: Journal of Mechanical Design:;2013:;volume( 135 ):;issue: 008::page 81004
    Author:
    Li, Jing
    ,
    Mourelatos, Zissimos P.
    ,
    Kokkolaras, Michael
    ,
    Papalambros, Panos Y.
    ,
    Gorsich, David J.
    DOI: 10.1115/1.4024470
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Computational simulation models support a rapid design process. Given model approximation and operating conditions uncertainty, designers must have confidence that the designs obtained using simulations will perform as expected. The traditional approach to address this need consists of model validation efforts conducted predominantly prior to the optimization process. We argue that model validation is too daunting of a task to be conducted with meaningful success for design optimization problems associated with highdimensional space and parameter spaces. In contrast, we propose a methodology for maximizing confidence in designs generated during the simulationbased optimization process. Specifically, we adopt a trustregionlike sequential optimization process and utilize a Bayesian hypothesis testing technique to quantify model confidence, which we maximize by calibrating the simulation model within local domains if and when necessary. This ensures that the design iterates generated during the sequential optimization process are associated with maximized confidence in the utilized simulation model. The proposed methodology is illustrated using a cantilever beam design subject to vibration.
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      Maximizing Design Confidence in Sequential Simulation Based Optimization

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    http://yetl.yabesh.ir/yetl1/handle/yetl/152533
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    • Journal of Mechanical Design

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    contributor authorLi, Jing
    contributor authorMourelatos, Zissimos P.
    contributor authorKokkolaras, Michael
    contributor authorPapalambros, Panos Y.
    contributor authorGorsich, David J.
    date accessioned2017-05-09T01:00:57Z
    date available2017-05-09T01:00:57Z
    date issued2013
    identifier issn1050-0472
    identifier othermd_135_8_081004.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/152533
    description abstractComputational simulation models support a rapid design process. Given model approximation and operating conditions uncertainty, designers must have confidence that the designs obtained using simulations will perform as expected. The traditional approach to address this need consists of model validation efforts conducted predominantly prior to the optimization process. We argue that model validation is too daunting of a task to be conducted with meaningful success for design optimization problems associated with highdimensional space and parameter spaces. In contrast, we propose a methodology for maximizing confidence in designs generated during the simulationbased optimization process. Specifically, we adopt a trustregionlike sequential optimization process and utilize a Bayesian hypothesis testing technique to quantify model confidence, which we maximize by calibrating the simulation model within local domains if and when necessary. This ensures that the design iterates generated during the sequential optimization process are associated with maximized confidence in the utilized simulation model. The proposed methodology is illustrated using a cantilever beam design subject to vibration.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMaximizing Design Confidence in Sequential Simulation Based Optimization
    typeJournal Paper
    journal volume135
    journal issue8
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.4024470
    journal fristpage81004
    journal lastpage81004
    identifier eissn1528-9001
    treeJournal of Mechanical Design:;2013:;volume( 135 ):;issue: 008
    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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