A new optimization strategy for wet steam effect minimization in steam turbine using combined 2D non-equilibrium wet steam flow and mean-line analysis

Abstract

Wet steam flow in the low-pressure stage of a steam turbine reduces efficiency and causes blade erosion due to the formation of water droplets. To enhance efficiency and lifetime, shape optimization is a suitable method, but it requires computationally expensive numerical simulations of non-equilibrium condensation in 3D viscous flow. This study introduces a new and effective approach for shape optimization, which employs a mean-line method for two objectives: firstly, to calculate the aerodynamic losses without resorting to computationally expensive 3D viscous CFD simulation; secondly, to filter out the airfoils with high loss values before performing simulation in the optimization process. Instead of a 3D viscous simulation, a 2D inviscid one is employed that can estimate the wet steam loss and liquid droplet radius, which are beyond the capability of the mean-line method. The mean-line method is verified with experimental results of a steam turbine and the 2D inviscid flow simulation is validated with experimental results. The mean-line method and the 2D computational code are coupled with an airfoil generator code and integrated into a genetic algorithm. Moreover, the optimization process proposed in this study ensures that the mean-line method maintains the inlet and outlet flow of the blade under constant conditions, without affecting the other stages of the turbine. The cascade of a steam turbine serves as a test case for the optimization strategy, demonstrating its capability to decrease wet steam loss by 10 % and potentially reduce the erosion rate. This is achieved while being over ten times quicker than 3D optimization.