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dc.contributor.authorSeshadri, Pranay
dc.contributor.authorDuncan, Andrew
dc.contributor.authorThorne, George
dc.date.accessioned2022-05-08T08:57:16Z
dc.date.available2022-05-08T08:57:16Z
dc.date.copyright3/3/2022 12:00:00 AM
dc.date.issued2022
dc.identifier.issn0889-504X
dc.identifier.otherturbo_144_8_081004.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4284550
dc.description.abstractThis paper introduces the Bayesian mass average and details its computation. Owing to the complexity of flow in an engine and the limited instrumentation and the precision of the sensor apparatus used, it is difficult to rigorously calculate mass averages. Building upon related work, this paper views any thermodynamic quantity’s spatial variation at an axial plane in an engine (or a rig) as a Gaussian random field. In cases where the mass flowrate is constant in the circumferential direction but can be expressed via a polynomial or spline radially, this paper presents an analytical calculation of the Bayesian mass average. In cases where the mass flowrate itself can be expressed as a Gaussian random field, a sampling procedure is presented to calculate the Bayesian mass average. Examples of the calculation of the Bayesian mass average for temperature are presented, including with a real engine case study where velocity profiles are inferred from stagnation pressure measurements.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleBayesian Mass Averaging in Rigs and Engines
dc.typeJournal Paper
dc.journal.volume144
dc.journal.issue8
dc.journal.titleJournal of Turbomachinery
dc.identifier.doi10.1115/1.4053534
dc.journal.fristpage81004-1
dc.journal.lastpage81004-9
dc.page9
dc.treeJournal of Turbomachinery:;2022:;volume( 144 ):;issue: 008
dc.contenttypeFulltext


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