Multi-objective optimization of the effects of superheat degree and blade pitch on the wet steam parameters

Abstract

Steam expansion in the low-pressure stages of the steam turbines, due to the supercooled flow, causes the nucleation phenomenon and the two-phase flow, which leads to an efficiency drop and severe mechanical damage to the turbine. In this research, the impacts of the inlet steam superheat degree and variation of blade pitch in the turbine blade cascade have been investigated. Then, optimizing the concurrent effects of the inlet steam superheat degree and blade pitch to keep the inlet mass flow rate fixed are studied utilizing the genetic algorithm. Moreover, wetness fraction, pressure losses, momentum, and economic cost are the objective functions of the present study. Based on the results, as the inlet steam superheat degree increases, the inlet mass flow rate of the turbine blade decreases; and the blade pitch increase can increase the mass flow rate. Case B is chosen as the optimal case in which, when the inlet mass flow rate is fixed compared to the original case, the wetness fraction, the droplet average radius, and the pressure losses decrease by 56%, 65%, and 3.4%, respectively, and the momentum increases by 5%; in addition, the economic cost is 1.5 ($/hour) in the optimal case.