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.

Optimization of a High-Pressure Steam Turbine Stage for a Wide Flow Coefficient Range / J. Bellucci; F. Rubechini; A. Arnone; L. Arcangeli; N. Maceli; V. Dossena. - ELETTRONICO. - 6: Oil and Gas Applications; Concentrating Solar Power Plants; Steam Turbines; Wind Energy:(2012), pp. 615-625. (Intervento presentato al convegno ASME Turbo Expo 2012: Turbine Technical Conference and Exposition tenutosi a Copenhagen, Denmark nel 11-15 June, 2012) [10.1115/GT2012-69529].

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

BELLUCCI, JURI;RUBECHINI, FILIPPO;ARNONE, ANDREA;
2012

Abstract

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.
2012
Conference Proceedings
ASME Turbo Expo 2012: Turbine Technical Conference and Exposition
Copenhagen, Denmark
11-15 June, 2012
J. Bellucci; F. Rubechini; A. Arnone; L. Arcangeli; N. Maceli; V. Dossena
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/600575
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