Nozzle Shape Optimization for Wet-Steam Flows

The present work investigates the feasibility of a methodolody for the shape optimization of wet-steam nozzles. This is done by means of a wet-steam flow solver coupled with a multi-objective genetic algorithm. A moment method is used to describe the evolution of liquid droplets. The droplet size distribution is partially modelled by means of transport equations for the lowest-order moments of the droplet spectrum, which allows evaluating the wetness fraction and the mean radius of the droplets. These additial equations are coupled with the Euler equations that govern the motion of the two-phase mixture. The system of the governing equations is solved numerically through an uncoupled procedure: the main equations for the mixture are solved first, then the main flow properties are frozen and used to solve the additional equations. The numerical solver is then coupled with a genetic algorithm to obtain a proper design for the shape of nozzles in which steam and liquid droplets coexist. Several optimization strategies are investigated for both low- pressure and high pressure nozzles, and the pros and cons of each are pointed out.