The purpose of this study is to obtain the optimal surface heating for a stationary cascade turbine blade in wet steam flow by a genetic algorithm. The numerical method is conducted by employing two-dimensional Navier–Stokes equations coupled with a SSTk − ω turbulence model. Nucleation and droplet growth equations are solved using the Eulerian-Eulerian approach. The numerical results show good agreement with wellestablished experiments. Nozzle effciency (NE), integral of local entropy changes at the outlet (ILE), mean wetness at the outlet (MWO), mean momentum at the outlet (MMO), and cost price (CP) are objective functions. The ultimate purpose is to minimize the (ILE), (MWO), and (CP) and maximize the (NE) and (MMO) together. Since higher surface heating rates decrease MWO and MMO, while increasing ILE, CP, and NE based on optimization results, there is an optimum for the surface heating rate to gain the best performance of steam turbines. According to the numerical results, the optimum – is equal to 0.04467 (cm kW2). In the optimal case compared to the non-heat case, NE and MWO are improved 0.26% and 19.94%, respectively. In addition, the ILE and MMO are degraded 0.9%, 0.32%, respectively, and CP is estimated 0.0027 (cm$2.h)

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