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dc.contributor.authorBeisheim, J. R.
dc.contributor.authorSinclair, G. B.
dc.contributor.authorRoache, P. J.
dc.date.accessioned2019-09-18T09:06:59Z
dc.date.available2019-09-18T09:06:59Z
dc.date.copyright2/8/2019 12:00:00 AM
dc.date.issued2019
dc.identifier.issn2377-2158
dc.identifier.othervvuq_003_03_034501.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4259042
dc.description.abstractCurrent computational capabilities facilitate the application of finite element analysis (FEA) to three-dimensional geometries to determine peak stresses. The three-dimensional stress concentrations so quantified are useful in practice provided the discretization error attending their determination with finite elements has been sufficiently controlled. Here, we provide some convergence checks and companion a posteriori error estimates that can be used to verify such three-dimensional FEA, and thus enable engineers to control discretization errors. These checks are designed to promote conservative error estimation. They are applied to twelve three-dimensional test problems that have exact solutions for their peak stresses. Error levels in the FEA of these peak stresses are classified in accordance with: 1–5%, satisfactory; 1/5–1%, good; and <1/5%, excellent. The present convergence checks result in 111 error assessments for the test problems. For these 111, errors are assessed as being at the same level as true exact errors on 99 occasions, one level worse for the other 12. Hence, stress error estimation that is largely reasonably accurate (89%), and otherwise modestly conservative (11%).
dc.publisherAmerican Society of Mechanical Engineers (ASME)
dc.titleEffective Convergence Checks for Verifying Finite Element Stresses at Three-Dimensional Stress Concentrations
dc.typeJournal Paper
dc.journal.volume3
dc.journal.issue3
dc.journal.titleJournal of Verification, Validation and Uncertainty Quantification
dc.identifier.doi10.1115/1.4042515
dc.journal.fristpage34501
dc.journal.lastpage034501-4
dc.treeJournal of Verification, Validation and Uncertainty Quantification:;2019:;volume( 003 ):;issue: 003
dc.contenttypeFulltext


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