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Comparison of CFD predictions of supercritical carbon dioxide axial flow turbines using a number of turbulence models

AbdElDayem, A., White, M. ORCID: 0000-0002-7744-1993 and Sayma, A. I. ORCID: 0000-0003-2315-0004 (2021). Comparison of CFD predictions of supercritical carbon dioxide axial flow turbines using a number of turbulence models. In: Proceedings of the ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition. . New York, USA: ASME. ISBN 9780791885048

Abstract

A detailed loss assessment of an axial turbine stage operating with a supercritical carbon dioxide (sCO2) based mixture, namely titanium tetrachloride (CO2-TiCl4 85-15%), is presented. To assess aerodynamic losses, computational fluid dynamics (CFD) simulations are conducted using a geometry generated using mean-line design equations which is part of the work delivered to the SCARABEUS project [1]. The CFD simulations are 3D steady state and employ a number of turbulence models to investigate various aerodynamic loss mechanisms. Two categories of turbulence models are used: Eddy Viscosity and Reynold's Stress models (RSM). The Eddy Viscosity models are the k-?, k-? RNG, k-?, k-? SST and k-? Generalized while the RSM models are BSL, LRR, w-RSM and k-? EARSM. The comparison between different turbulence models showed minor deviations in mass-flow rate, power output and blade loading while significant deviations appear in the loss coefficients and the degree of reaction. It is noted that the k-? model gives the highest loss coefficients and the lowest isentropic efficiencies while most of the RSM models indicate higher efficiencies and lower loss coefficients. At off-design conditions a sensitivity study revealed that the k-? RNG model records the sharpest drop in the isentropic efficiency of 8.24% at low mass flowrate reaching 30% off-design. The efficiency sensitivity is found to be less for the other tested models getting 3.1% drop in efficiency for the LRR RSM model.

Publication Type: Conference or Workshop Item (Paper)
Subjects: T Technology > TJ Mechanical engineering and machinery
Departments: School of Mathematics, Computer Science & Engineering > Engineering > Mechanical Engineering & Aeronautics
Date available in CRO: 02 Dec 2021 08:38
Date deposited: 24 November 2021
Date of first online publication: 16 September 2021
URI: https://openaccess.city.ac.uk/id/eprint/27128
[img] Text - Accepted Version
This document is not freely accessible due to copyright restrictions.

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