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research-article

Supercritical CO2 Radial Turbine Design Performance as a Function of Turbine Size Parameters

[+] Author and Article Information
Jianhui Qi

Queensland Geothermal Energy Centre of Excellence The University of Queensland Brisbane, Australia, 4072
j.qi@uq.edu.au

Thomas Reddell

Queensland Geothermal Energy Centre of Excellences The University of Queensland Brisbane, Australia, 4072
t.reddell@uq.edu.au

Kan Qin

Queensland Geothermal Energy Centre of Excellence The University of Queensland Brisbane, Australia, 4072
k.qin1@uq.edu.au

Kamel Hooman

Queensland Geothermal Energy Centre of Excellence The University of Queensland Brisbane, Australia, 4072
k.hooman@uq.edu.au

Ingo Jahn

Centre for Hypersonics The University of Queensland Brisbane, Australia, 4072
i.jahn@uq.edu.au

1Corresponding author.

ASME doi:10.1115/1.4035920 History: Received August 10, 2016; Revised January 20, 2017

Abstract

Supercritical CO2 cycles are considered a promising technology for next generation concentrated solar thermal, waste heat recovery and nuclear applications. Particularly at small scale, where radial inflow turbines can be employed, using sCO2 results in both system advantages and simplifications of the turbine design, leading to improved performance and cost reductions. This paper aims to provide new insight towards the design of radial turbines for operation with sCO2 in the 100~200kW range. The quasi one dimensional mean line design code TOPGEN is enhanced to explore and map the radial turbine design space. This mapping process over a state space defined by Head and Flow coefficients allows the selection of an optimum turbine design, while balancing performance and geometrical constraints.By considering three operating points with varying power levels and rotor speeds the effect of these on feasible design space and performance is explored. This provides new insight towards the key geometric features and operational constraints that limit the design space as well as scaling effects. Finally review of the loss break-down of the designs elucidates the importance of the respective loss mechanisms. Similarly it allows the identification of a design directions that lead to improved performance. Overall this work has shown that turbine design with efficiencies in the range 78~82% are possible in this power range and provides insight into the design space that allows the selection of optimum designs.

Copyright (c) 2017 by ASME
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