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A novel method to extract vanadium from vanadium-bearing steel slag using sodium carbonate solution

Gao M., Xue X., Li L., Yang H., Bai R., Wang H.

Physicochemical Problems of Mineral Processing

2018

Vol. 54, iss. 3

911--921

A new method using sodium carbonate solution to treat a vanadium-bearing steel slag is proposed. The effects of the particle size, solid-to-liquid ratio, initial concentration of sodium carbonate solution, leaching temperature and stirring speed on the leaching rate of vanadium were investigated. The leaching kinetics of vanadium from the vanadium-bearing steel slag was studied, which indicated that the leaching rate was controlled by the step of diffusion through the solid layer around the unreacted core. The apparent activation energy for the process was 13.75 kJ/mol. By using this process, vanadium could be extracted effectively with the leaching rate of more than 80%.

Population diversity maintenance in brain storm optimization algorithm

Cheng S., Shi Y., Qin Q., Zhang Q, Bai R.

Journal of Artificial Intelligence and Soft Computing Research

2014

Vol. 4, No. 2

83--97

The convergence and divergence are two common phenomena in swarm intelligence. To obtain good search results, the algorithm should have a balance on convergence and divergence. The premature convergence happens partially due to the solutions getting clustered together, and not diverging again. The brain storm optimization (BSO), which is a young and promising algorithm in swarm intelligence, is based on the collective behavior of human being, that is, the brainstorming process. The convergence strategy is utilized in BSO algorithm to exploit search areas may contain good solutions. The new solutions are generated by divergence strategy to explore new search areas. Premature convergence also happens in the BSO algorithm. The solutions get clustered after a few iterations, which indicate that the population diversity decreases quickly during the search. A definition of population diversity in BSO algorithm is introduced in this paper to measure the change of solutions’ distribution. The algorithm’s exploration and exploitation ability can be measured based on the change of population diversity. Different kinds of partial reinitialization strategies are utilized to improve the population diversity in BSO algorithm. The experimental results show that the performance of the BSO is improved by part of solutions re-initialization strategies.