American Journal of Energy Research
ISSN (Print): 2328-7349 ISSN (Online): 2328-7330 Website: http://www.sciepub.com/journal/ajer Editor-in-chief: Apply for this position
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American Journal of Energy Research. 2017, 5(3), 97-102
DOI: 10.12691/ajer-5-3-4
Open AccessArticle

Grid Dependency Analysis for Performance Prediction of an Automotive Mixed Flow Turbine

Ahmed Ketata1, and Zied Driss1,

1Laboratory of Electro-Mechanic Systems (LASEM), National School of Engineers of Sfax (ENIS), University of Sfax (US), B.P. 1173, Road Soukra km 3.5, 3038 Sfax, TUNISIA

Pub. Date: November 20, 2017

Cite this paper:
Ahmed Ketata and Zied Driss. Grid Dependency Analysis for Performance Prediction of an Automotive Mixed Flow Turbine. American Journal of Energy Research. 2017; 5(3):97-102. doi: 10.12691/ajer-5-3-4

Abstract

The turbocharger which consists essentially on a radial turbine and a centrifugal compressor is commonly embedded to internal combustion engines in order to enhance its performance. The use of a mixed flow turbine instead of a radial one leads to better aerodynamic efficiency. The present investigation shows our optimized numerical model under steady conditions in purpose to predict the overall performance for an automotive vanned mixed flow turbine. Using the CFX 17.0 package, numerical results are obtained by solving the Reynolds averaged Navier Stokes equations by means of a finite volume discretization method. The standard k-ε turbulence model is used to close these equations. Based on the numerical solutions, the turbine performance and the reaction degree are computed. Equally, the distribution of the turbine output torque and its blades loading as a function of the isentropic velocity ratio are plotted. The mesh choice is based on the solution independency. Our numerical results show a good agreement compared to the test data.

Keywords:
turbocharger mixed flow turbine performance mass flow Efficiency CFD turbulence

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