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A comparison of axial turbine loss models for air, sCO₂ and ORC turbines across a range of scales

Salah, S., White, M. ORCID: 0000-0002-7744-1993 & Sayma, A. I. ORCID: 0000-0003-2315-0004 (2022). A comparison of axial turbine loss models for air, sCO₂ and ORC turbines across a range of scales. International Journal of Thermofluids, 15, 100156. doi: 10.1016/j.ijft.2022.100156

Abstract

Loss models are used to evaluate the aerodynamic performance of axial turbines at the preliminary design stage. The commonly used loss models were derived for air and steam turbines and have not been sufficiently investigated for turbines working with non-conventional working fluids, relevant to new power systems, such as organic fluids and supercritical CO (sCO). Thus, the aim of this study is to explore the deviation between the performance predictions of different loss models, namely Dunham and Came, Kacker and Okapuu, Craig and Cox and Aungier, for non-conventional working fluids where turbines may differ in design and operation than conventional air or steam turbines. Additionally, this paper aims to investigate the effect of the turbine scale on the trends in the performance predictions of these models. Three different case-studies are defined for air, organic Rankine cycle (ORC) and sCO turbines and each one is evaluated at two different scales. It is found that the selected loss models resulted in varying loss predictions; particularly for predicting the losses due to the clearance gap for all small scale designs. Furthermore, large variations were found in predicting the effect of the flow regime on the turbine performance for all models.

Publication Type: Article
Additional Information: © 2022 Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Publisher Keywords: Performance analysis, Non-conventional working fluids, Loss models, Air turbines, sCO2 turbines, ORC turbines
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments: School of Mathematics, Computer Science & Engineering > Engineering > Mechanical Engineering & Aeronautics
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