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Impingement cooling has been widely employed to cool gas turbine hot components such as combustor liners, combustor transition pieces, turbine vanes, and blades. A promising technology is proposed to enhance impingement cooling with water droplets injection. However, previous studies were conducted on blade shower head film cooling, and less attention was given to the transition piece cooling. As a continuous effort to develop a realistic mist impingement cooling scheme, this paper focuses on simulating mist impingement cooling under typical gas turbine operating conditions of high temperature and pressure in a double chamber model. Furthermore, the paper presents the effect of cooling effectiveness by changing the mass and size of the droplets. Based on the heat-mass transfer analogy, the results of these experiments prove that the mass of 3 − 3 kg/s droplets with diameters of 5-35 m could enhance 90% cooling effectiveness and reduce 122 K of wall temperature. The results of this paper can provide guidance for corresponding experiments and serve as the qualification reference for future more complicated studies with convex surface cooling.

The artificial bee colony (ABC) algorithm is a recently introduced swarm intelligence optimization algorithm based on the foraging behavior of a honeybee colony. However, many problems are encountered in the ABC algorithm, such as premature convergence and low solution precision. Moreover, it can easily become stuck at local optima. The scout bees start to search for food sources randomly and then they share nectar information with other bees. Thus, this paper proposes a global reconnaissance foraging swarm optimization algorithm that mimics the intelligent foraging behavior of scouts in nature. First, under the new scouting search strategies, the scouts conduct global reconnaissance around the assigned subspace, which is effective to avoid premature convergence and local optima. Second, the scouts guide other bees to search in the neighborhood by applying heuristic information about global reconnaissance. The cooperation between the honeybees will contribute to the improvement of optimization performance and solution precision. Finally, the prediction and selection mechanism is adopted to further modify the search strategies of the employed bees and onlookers. Therefore, the search performance in the neighborhood of the local optimal solution is enhanced. The experimental results conducted on 52 typical test functions show that the proposed algorithm is more effective in avoiding premature convergence and Communicated by improving solution precision compared with some other ABCs and several state-of-the-art algorithms. Moreover, this algorithm is suitable for optimizing high-dimensional space optimization problems, with very satisfactory outcomes.

Investigation of the effects of impingement cooling for the different turbulence models and study of the aerodynamic behavior of a simplified transition piece model (TP) are the two themes of this paper. A model (double chamber model) of a one-fourth cylinder is designed which could simulate the transition piece structure and performance. The relative strengths and drawbacks of renormalization group theoryk-ε(RNG), the realizablek-ε(RKE), thev2-f, the shear stress transportk-ω(SST), and large-eddy simulation (LES) models are used to solve the closure problem. The prediction of the inner wall temperature, cooling effectiveness, and velocity magnitude contours in various conditions are compared in five different turbulence models. Surprisingly, thev2-fand SST models can produce even better predictions of fluid properties in impinging jet flows. It is recommended as the best compromise between solution speed and accuracy.