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To improve predicting accuracy further, this paper modified original Pareto dominance relation among the candidate solutions, and proposed a new method named d-Pareto dominance prediction using nearest neighbor. Combined with the characteristics of multi-objective optimization, it described the framework of d-Pareto and the conclusion that a d-Pareto dominance prediction could obtain a lower average prediction error rate comparing with Pareto demonstrated dominance prediction. Besides, it also explored the interaction between d-Pareto dominance prediction and multi-objective evolutionary algorithms. Experiments on several classic MOPs were conducted and the simulation results show that prediction of d-Pareto dominance is feasible and effective. [ABSTRACT FROM AUTHOR]

Thrust vectoring can provide fighter with advantages regarding performance, survivability and detectability. Two types of fluidic control Convergent-Divergent nozzle thrust vector technology, which are Shock Vectoring controlling and Throat Shift, are numerically simulated and their performances are analyzed. A nozzle with fixed geometry from nozzle inlet to throat, and fixed length of divergent flap is researched. The relative position of the secondary injecting flow is fixed, and the injecting direction is always vertical to the nozzle main flow. The nozzle flow fields are obtained via CFD numerical simulation. It can be seen from the results that, Throat Shift method is suitable for the nozzle expansion ratio less than 1.5, and Shock Vectoring controlling method is contrary to Throat Shift method, which is suitable for the nozzle expansion ratio greater than 1.5. The Throat Shift method can restrict the nozzle mass flow besides thrust vectoring. The main influence of the secondary mass flow is the ratio of secondary total pressure to main flow total pressure. [ABSTRACT FROM AUTHOR]