Camber Modeling Method for Centrifugal Blade Profile Design Based on z-ɵ Rule

To help with the design of axial flow steam turbine blading a suite of flow analysis programs has been adapted and developed. Effort has been concentrated on improving the blade-to-blade analysis and developing a two-dimensional blade-to-blade profile design method. The development and verification of the analysis program have already been reported in detail (Willis, 1987 and Willis and Goulas, 1987). This paper presents the design or inverse solution. The analysis method uses an inviscid stream function solution coupled with an integral boundary layer calculation. In the design program the required changes in the blade geometry are effected via a transpiration type model. It is therefore a ‘profile refinement’, rather than an ‘original’ design procedure, and is necessarily an iterative solution. A required velocity distribution may be specified over only part of the blade surface. Two examples are presented in this paper to illustrate the capability of the design program.

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Turbine blade profile design method using Bezier curves

10.29008/etc2017-195 ◽

2017 ◽

Cited By ~ 1

Author(s):

Vladimir Gribin ◽

Aleksandr Tishchenko ◽

Ilya Gavrilov ◽

Victor Tishchenko ◽

Ivan Sorokin ◽

...

Keyword(s):

Turbine Blade ◽

Design Method ◽

Blade Profile ◽

Bezier Curves ◽

Bézier Curves ◽

Profile Design

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Optimization of stator blade profile design for last stages of steam turbines based on the features of coarse droplets movement in inter-blade channels

Journal of Physics Conference Series ◽

10.1088/1742-6596/1359/1/012038 ◽

2019 ◽

Vol 1359 ◽

pp. 012038 ◽

Cited By ~ 1

Author(s):

R A Alekseev ◽

V G Gribin ◽

A A Tishchenko ◽

I Yu Gavrilov ◽

V A Tishchenko ◽

...

Keyword(s):

Steam Turbines ◽

Blade Profile ◽

Stator Blade ◽

Profile Design

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The active working shoot modeling profile of the centrifugal microturbine

MATEC Web of Conferences ◽

10.1051/matecconf/201822601009 ◽

2018 ◽

Vol 226 ◽

pp. 01009

Author(s):

Nikolai N. Efimov ◽

Sergei V. Skubienko ◽

Vadim V. Kopitsa ◽

Igor Y. Kolodyazhny ◽

Evgeny A. Anisimov ◽

...

Keyword(s):

Initial Data ◽

Single Stage ◽

Steam Turbines ◽

Blade Profile ◽

Traditional Methods ◽

Distributed Power ◽

Software Simulation ◽

Advantages And Disadvantages ◽

Profile Design ◽

Optimum Profile

For the small distributed power, microturbines of electric 30-500 kW capacity are used: gas piston engines, gas and steam turbines, each of which has certain advantages and disadvantages. In the work, the active working blade profile is simulated for a single-stage, two-stream, centripetal microturbine, in order to determine the optimum profile design satisfying the reliability conditions and economy. The basis is a humidsteam microturbine of a horizontal electric version with a capacity of 30 kW. The initial data for software simulation were the microturbineactive stage characteristics, determined by the steam turbines calculation traditional methods.

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Automatic Genetic Optimization Approach to 2D Blade Profile Design for Steam Turbines

Volume 1: Aircraft Engine; Marine; Turbomachinery; Microturbines and Small Turbomachinery ◽

10.1115/97-gt-392 ◽

1997 ◽

Cited By ~ 4

Author(s):

M. A. Trigg ◽

G. R. Tubby ◽

A. G. Sheard

Keyword(s):

Systematic Approach ◽

Optimization Approach ◽

Genetic Optimization ◽

Steam Turbines ◽

Blade Profile ◽

Minimum Loss ◽

Profile Design ◽

Viscous Compressible Flow ◽

Lower Loss ◽

Profile Loss

In this paper a systematic approach to the optimization of 2D blade profiles is presented. A genetic optimizer has been developed which modifies the blade profile and calculates its profile loss. This process is automatic, producing profile designs significantly faster and with significantly lower loss than has previously been possible. The optimizer developed uses a genetic algorithm to optimize a 2D profile, defined using 17 parameters, for minimum loss with a given flow condition. The optimizer works with a “population” of 2D profiles with varied parameters. A CFD mesh is generated for each profile, and the result is analyzed using a 2D blade to blade solver, written for steady viscous compressible flow, to determine profile loss. The loss is used as the measure of a profile’s “fitness”. The optimizer uses this information to select the members of the next population, applying crossovers, mutations, and elitism in the process. Using this method the optimizer tends towards the best values for the parameters defining the profile with minimum loss.

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