Particle swarm optimization (PSO) algorithm is generally improved by adaptively adjusting the inertia weight or combining with other evolution algorithms. However, in most modified PSO algorithms, the random values are always generated by uniform distribution in the range of [0, 1]. In this study, the random values, which are generated by uniform distribution in the ranges of [0, 1] and [−1, 1], and Gauss distribution with mean 0 and variance 1 ( $U\left[0,1\right]$ , $U\left[-1,1\right]$ and $G(0,1)$ ), are respectively used in the standard PSO and linear decreasing inertia weight (LDIW) PSO algorithms. For comparison, the deterministic PSO algorithm, in which the random values are set as 0.5, is also investigated in this study. Some benchmark functions and the pressure vessel design problem are selected to test these algorithms with different types of random values in three space dimensions (10, 30, and 100). The experimental results show that the standard PSO and LDIW-PSO algorithms with random values generated by $U\left[-1,1\right]$ or $G(0,1)$ are more likely to avoid falling into local optima and quickly obtain the global optima. This is because the large-scale random values can expand the range of particle velocity to make the particle more likely to escape from local optima and obtain the global optima. Although the random values generated by $U\left[-1,1\right]$ or $G(0,1)$ are beneficial to improve the global searching ability, the local searching ability for a low dimensional practical optimization problem may be decreased due to the finite particles.

In this paper, the sintering neck growth process of metal fibers under the surface diffusion mechanism is simulated by using the Lattice Boltzmann method (LBM). The surface diffusion model is developed considering the geometrical characteristic of metal fibers. Then, the LBM scheme is constructed for solving the developed surface diffusion model. The sintering neck growth process of two metal fibers with different fiber angles is simulated by LBM. The simulated morphologies of sintering metal fibers well agree with ones obtained by experiments. Moreover, the numerical simulation results show that the sintering neck radius of two metal fibers is increased with the increase of fiber angle, which implies that the initial geometrical characteristic plays an important role in the sintering neck formation and growth of metal fibers.

The quench sensitivity of 7085 aluminum alloy with different contents of the main alloying elements (Zn, Mg and Cu) was investigated using time-temperature-transformation (TTT) curves and end quenching experiments. Then, the quenching microstructure was analyzed using transmission electron microscopy. With increasing the contents of the main alloying elements, the transitions and nose temperatures of the TTT curves are obviously increased, while the incubation time of 0.5% η (MgZn₂) phase precipitation content is decreased. In addition, as the contents of the main alloying elements decrease, the conductivity of the quenched samples is increased, but the hardness of the quenched samples is decreased. Moreover, the size and area fraction of the η phase are increased with increasing the contents of the main alloying elements. Based on the experimental results, the increase of Mg and Cu contents can decrease the stability of supersaturated solid solution and increase the lattice distortion energy, which can increase the quench sensitivity of 7085 aluminum alloy.