A new approach to the particle swarm optimization (PSO) is proposed for the solution of non-linear optimization problems with constraints, and is applied to the reliability-based optimum design of laminated composites. Special mutation-interference operators are introduced to increase swarm variety and improve the convergence performance of the algorithm. The reliability-based optimum design of laminated composites is modelled and solved using the improved PSO. The maximization of structural reliability and the minimization of total weight of laminates are analysed. The stacking sequence optimization is implemented in the improved PSO by using a special coding technique. Examples show that the improved PSO has high convergence and good stability and is efficient in dealing with the probabilistic optimal design of composite structures.

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Recently, heat treatment between 250 °C and 500 °C has been attempted to improve quality factor (Q) of superconducting radio-frequency cavities at FNAL and KEK. Experiments of such medium temperature (mid-T) bake with furnaces have also been carried out at IHEP. Firstly, over ten 1.3 GHz 1-cell cavities were treated with different temperatures at a small furnace, which all demonstrated improvement of Q and anti-Q-slope phenomenon. The average quality factor has reached 3.6×10 10 when the gradient is 16 MV/m，while the highest Q is 4.9×10 10 @16MV/m; the maximum gradients of these 1-cell cavities are between 25.1 and 36.9 MV/m. Then, the recipe of mid-T furnace bake at 300 °C for 3 hours has been applied to six 1.3 GHz 9-cell cavities at a new big furnace, which have all shown higher Q and anti-Q-slope at medium field (16~24 MV/m). The average quality factor has reached 3.8×10 10 when the gradient is 16 MV/m. The maximum gradients of the 9-cell cavities are between 22.7 and 26.5 MV/m.