Optimization of operating conditions in the steam turbine blade cascade using the black-box method

Water droplets cause corrosion and erosion, condensation loss, and thermal efficiency reduction in low-pressure steam turbines. In this study, multi-objective optimization was carried out using the black-box method through the automatic linking of a genetic algorithm (GA) and a computational fluid dynamics (CFD) code to find the optimal values of two design variables (inlet stagnation temperature and cascade pressure ratio) to reduce wetness in the last stages of turbines. The wet steam flow numerical model was used to calculate the optimization parameters, including wetness fraction rate, mean droplet radius, erosion rate, condensation loss rate, kinetic energy rate, and mass flow rate. Examining the validation results showed a good agreement between the experimental data and the numerical outcomes. According to the optimization results, the inlet stagnation temperature and the cascade pressure ratio were proposed to be 388.67 (K) and 0.55 (−), respectively. In particular, the suggested optimal temperature and pressure ratio improved the liquid mass fraction and mean droplet radius by about 32% and 29%, respectively. Also, in the identified optimal operating state, the ratios of erosion, condensation loss, and kinetic energy fell by 76%, 32.7%, and 15.85%, respectively, while the mass flow rate ratio rose by 0.68%.