Optimization of a High-Pressure Steam Turbine Stage for a Wide Flow Coefficient Range

TitleOptimization of a High-Pressure Steam Turbine Stage for a Wide Flow Coefficient Range
Publication TypeConference Paper
Year of Publication2012
AuthorsBellucci J, Rubechini F, Arnone A, Arcangeli L, Maceli N, Dossena V
Conference NameASME Turbo Expo 2012: Turbine Technical Conference and Exposition
Volume6: Oil and Gas Applications; Concentrating Solar Power Plants; Steam Turbines; Wind Energy
Conference LocationCopenhagen, Denmark, June 11 - June 15, 2012
ISBN Number978-0-7918-4472-4
Accession NumberWOS:000324957800059
Other NumbersScopus 2-s2.0-84881141475
KeywordsArtificial Neural Networks, Optimization, Steam turbines

In this paper a multi-objective, aerodynamic optimization of a high-pressure steam turbine stage is presented. The overall redesign strategy relies on a neural-network-based approach, aimed at maximizing the turbine’s efficiency, while at the same time increasing the stage loading and reducing the blade count. The stage under investigation is composed of prismatic blades, usually employed in a repeating stage environment and in a wide range of operating conditions. For this reason, two different optimizations are carried out, at high and low flow coefficients. The optimized geometries are chosen taking into account aerodynamic constraints, such as limitation of the pressure recovery in the uncovered part of the suction side, as well as mechanical constraints, such as root tensile stress and dynamic behavior. As a result, an optimum airfoil is selected and its performance are characterized over the whole range of operating conditions. Parallel to the numerical activity, both optimized and original geometries are tested in a linear cascade, and experimental results are available for comparison purposes in terms of loading distributions and loss coefficients. Comparisons between measurements and calculations are presented and discussed for a number of incidence angles and expansion ratios.


ASME paper GT2012-69529.

Refereed DesignationRefereed