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Computational Thermal Sciences: An International Journal

Publication de 6  numéros par an

ISSN Imprimer: 1940-2503

ISSN En ligne: 1940-2554

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: 1.5 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 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.3 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: 0.00017 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: 0.28 SJR: 0.279 SNIP: 0.544 CiteScore™:: 2.5 H-Index: 22

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MIXED CONVECTION OF NANOFLUID OVER A BACKWARD FACING STEP UNDER THE EFFECTS OF A TRIANGULAR OBSTACLE AND INCLINED MAGNETIC FIELD

Volume 10, Numéro 6, 2018, pp. 521-543
DOI: 10.1615/ComputThermalScien.2018020085
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RÉSUMÉ

In this study, laminar mixed convection of CuO–water nanofluid over a backward facing step with the presence of a triangular obstacle and under the effect of magnetic field was numerically investigated. Finite volume method was used to solve the governing equations for the range of parameters: Richardson number (between 0.01 and 100), Hartmann number (between 0 and 50), nanoparticle volume fraction (between 0 and 0.04), and horizontal location of the triangular obstacle (between 0.5H and 2H). It was observed that average heat transfer is a decreasing function of Richardson number and an increasing function of nanoparticle volume fraction. The dependence of average heat transfer on the magnetic field parameters shows a resonant-type behavior. The obstacle affects the local Nusselt number distribution near the step especially for lower values of Richardson number and Hartmann number. Artificial neural networks were used to develop models that can be used instead of high-fidelity computational fluid dynamics simulations for fast and accurate thermal performance predictions of the considered system.

CITÉ PAR
  1. Lv Jun, Huang Qinghua , Yu Xinping , Qi Yongjie , HYDROTHERMAL PERFORMANCE IMPROVEMENT OF MICROSCALE BACKWARD-FACING STEP CHANNEL BY EMPLOYING VORTEX GENERATORS AND NANOFLUIDS , Computational Thermal Sciences: An International Journal, 15, 1, 2023. Crossref

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