A blackbox optimization of volumetric heating rate for reducing the wetness of the steam flow through turbine blades

This paper proposes to use a blackbox optimization obtain the optimal volumetric heating required reduce wetness at last stages of steam turbines. For this purpose, global multiobjective is utilized through automatic linking genetic algorithm and CFD code, where function evaluations are performed by runs. The logarithm number droplets per volume (LND), droplet average radius (DAR), integral local entropy (ILE) end cascade (after condensation location) minimized, while rate parameter. Eulerian–Eulerian approach implemented model two-phase wet turbulent flow numerical results validated against well-established experiments. Since higher rates DAR LND, increase ILE, according results, there an optimum for reach best performance case studies presented in work, 5.21 × 10 8 4.67 W / m 2 obtained two different cases supersonic subsonic outlets, respectively. Particularly, these improve 45.7% 57.5%, LND 6.0% 7.8% respective cases. • A considered. used turbine blades. Optimization process automatically linked with computational fluid dynamic code. Optimal turbines determined. reduced 45.7%.