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国际流体力学研究期刊

每年出版 6 

ISSN 打印: 2152-5102

ISSN 在线: 2152-5110

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.1 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.3 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0002 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.33 SJR: 0.256 SNIP: 0.49 CiteScore™:: 2.4 H-Index: 23

Indexed in

Computation of Flow in Mixing Units with Lobe Extensions

卷 22, 册 3-4, 1995, pp. 94-105
DOI: 10.1615/InterJFluidMechRes.v22.i3-4.60
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摘要

A method for computation of three-dimensional turbulent flows in mixing units of bypass turbojet engines in which lobe extensions are used to intensify mixing is suggested. The flow upstream of the lobe extension exit is subdivided into a potential core and a boundary layer. The potential flow is computed by the Boundary Integral Equations Method, and the viscous flow is calculated by an integral method for three-dimensional turbulent boundary layer. The flow in the mixing chamber is computed by the parabolic Reynolds equations and a one-parametric turbulence model. Flows in a set of mixing devices have been computed. The results are shown to be in agreement with experimental data.

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