Complex multidisciplinary optimization of turbine blading systems

The paper describes the methods and results of direct optimization of turbine blading systems using a software package Opti_turb. The final shape of the blading is obtained from minimizing the objective function, which is the total energy loss of the stage, including the leaving energy. The current values of the objective function are found from 3D RANS computations (from a code FlowER) of geometries changed during the process of optimization. There are constraints imposed on the mass flow rate, exit swirl angle and reactions, as well as on changes of stresses in the metal.  Among the optimized parameters are those of the blade itself (such as the blade number and stagger angle as well as the stacking blade line parameters) and those of the blade section (profile). Two new hybrid stochastic-deterministic methods are used for the optimization of flow systems. The first method is a combination of a genetic algorithm and a simplex method of Nelder–Mead. The other method is a combination of a direct search method of Hooke–Jeeves and simulated annealing. Also two methods of parametrization of the blade profile are described. They make use of a set of circle arcs and Bezier functions.  In the course of optimization, the flow efficiency of a group of two low pressure (LP) exit stages of a 50 MW turbine operating over a wide range of load is increased by means of optimization of 3D blade stacking lines. Another practical example of efficiency optimization of turbine blading systems is modification of low load profiles PLK-R2 for high pressure (HP) steam turbine stages. It is shown that optimization of geometry of turbine blading systems can give considerable efficiency gains. Optimization of 3D blade stacking lines in LP turbine stages can give over a 2% efficiency rise. Up to 1% efficiency, increase can be obtained from optimization of HP blade profiles and their restaggering.

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