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dc.contributor.authorZhang, Baoqiang
dc.contributor.authorGuo, Qintao
dc.contributor.authorWang, Yan
dc.contributor.authorZhan, Ming
dc.date.accessioned2019-09-18T09:00:43Z
dc.date.available2019-09-18T09:00:43Z
dc.date.copyright3/14/2019 12:00:00 AM
dc.date.issued2019
dc.identifier.issn1555-1415
dc.identifier.othercnd_014_05_051006.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4257854
dc.description.abstractExtensive research has been devoted to engineering analysis in the presence of only parameter uncertainty. However, in modeling process, model-form uncertainty arises inevitably due to the lack of information and knowledge, as well as assumptions and simplifications made in the models. It is undoubted that model-form uncertainty cannot be ignored. To better quantify model-form uncertainty in vibration systems with multiple degrees-of-freedom, in this paper, fractional derivatives as model-form hyperparameters are introduced. A new general model calibration approach is proposed to separate and reduce model-form and parameter uncertainty based on multiple fractional frequency response functions (FFRFs). The new calibration method is verified through a simulated system with two degrees-of-freedom. The studies demonstrate that the new model-form and parameter uncertainty quantification method is robust.
dc.publisherAmerican Society of Mechanical Engineers (ASME)
dc.titleModel-Form and Parameter Uncertainty Quantification in Structural Vibration Simulation Using Fractional Derivatives
dc.typeJournal Paper
dc.journal.volume14
dc.journal.issue5
dc.journal.titleJournal of Computational and Nonlinear Dynamics
dc.identifier.doi10.1115/1.4042689
dc.journal.fristpage51006
dc.journal.lastpage051006-12
dc.treeJournal of Computational and Nonlinear Dynamics:;2019:;volume( 014 ):;issue: 005
dc.contenttypeFulltext


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