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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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DOUBLE DIFFUSIVE NATURAL CONVECTION IN A SQUARE ENCLOSURE FILLED WITH COPPER-WATER NANOFLUID INDUCED BY OPPOSITE TEMPERATURE AND CONCENTRATION GRADIENTS

Volume 10, Numéro 4, 2018, pp. 307-320
DOI: 10.1615/ComputThermalScien.2018020672
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RÉSUMÉ

Double-diffusive natural convection in a Cu–water nanofluid-filled square enclosure neglecting the effect of Soret and Dufour is studied numerically. The horizontal walls are well insulated and impermeable, while the vertical walls are imposed to opposite temperature and concentration gradients. Brinkman, Maxwell–Garnett models are used to determine the effective dynamic viscosity and thermal conductivity of Cu–water nanofluid, respectively. A computational code based on the SIMPLE algorithm is used to solve the system of conservation equations of mass, momentum, energy, and species. Simulations are performed using the thermal Rayleigh number, the buoyancy ratio, and the solid volume fraction as independent variables. The numerical results are studied in terms of velocity profiles, streamlines, isotherms, iso-concentrations, local and average Nusselt numbers, and Sherwood number for a wide range of Rayleigh number Ra = 104–105, the buoyancy ratio N = 0.1–10 and the solid volume fraction (0 ≤ φ ≤ 0.1) with Prandtl number Pr = 5.0 and Lewis number Le = 1. It is found that utilizing Cu–water nanofluid enhances the heat transfer sufficiently while the enhancement is marginal for the mass transfer. It is also observed that the fluid flow behavior increases with increasing Rayleigh number but decreases with increasing solid volume fraction.

CITÉ PAR
  1. Natesan Saritha, Arumugam Senthil Kumar, Analysis of double diffusion natural convection in an enclosure filled with alumina water nanofluid using Buongioro's two phase model, International Journal of Numerical Methods for Heat & Fluid Flow, 29, 10, 2019. Crossref

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