Analysis and multi-objective optimization of slag powder process

open access articleSlag powder is a process with characters of multivariables, strongly coupling and nonlinearity. The material layer thickness plays an important role in the process. It can reflect the dynamic balance between the feed volume and discharge volume in the vertical mill. Keeping the material layer thickness in a suitable range can not only improve the quality of powder, but also save electrical power. Previous studies on the material layer thickness did not consider the relationship among the material layer thickness, quality and yield. In this paper, the yield and quality factors are taken into account and the variables that affect the material layer thickness, yield and quality are analyzed. Then the models of material layer thickness, yield and quality are established based on generalized regression neural network. The production process demands for highest yield, best production quality and smallest error of material layer thickness at the same time. From this point of view, the slag powder process can be regarded as a multi-objective optimization problem. To improve the diversity of solutions, a CT-NSGAII algorithm is proposed by introducing the clustering-based truncation mechanism into solution selection process. Simulation shows that the proposed method can solve the multi-objective problem and obtain solutions with good diversity

Special quasirandom structures to study the (K0.5Na0.5)NbO3 random alloy

The local structure of K0.5Na0.5NbO3 is investigated using first-principles methods with an optimized special quasirandom structure (SQS). Through a comparison of the computed pair distribution functions with those from neutron powder diffraction data, the SQS approach demonstrates its ability to accurately capture the local structure patterns derived from the random distribution of K and Na on the perovskite A-site. Using these structures, local variations in Na-O interactions are suggested to be the driving force behind the R3c to Pm phase transition. A comparison between the SQS and a rocksalt structure shows the inability of the latter to account for the local variability present in a random solid solution. As such, the predictive nature of the SQS demonstrated here suggests that this approach may provide insight in understanding the properties of a wide range of bulk oxide alloys or solid solutions