Advanced Materials Research Vol. 771

Abstract: This paper gives the numerical analysis method for heat transfer through climate adaptive window materials. Using the weather data in a typical city in hot summer and cold winter zone, an analysis of the application potential of climate adaptive window materials is given. The result shows that climate adaptive windows are capable of blocking solar radiation in summer while penetrating sunlight in winter and thus are suitable for building applications in this area.

Abstract: A kind of shape memory alloy (SMA) differential drive method and its experiment equipment can be used in swing joint of a micro amphibious robot is presented. According to its motion character, motion principle of the swing joint differential driven by SMA is analyzed. The basic thermodynamic performance of the SMA springs with different structural parameters is researched by experimentation. Aiming at the SMA differential actuator composed by SMA springs in different structural parameters, experimental research and analysis on the response ability of the SMA actuator is carried out in various driving condition and environment, which can be used to provide experimental base and data support for applying SMA drive technique in propulsive area of underwater vehicles.

Abstract: Sinter is the main raw material for ironmaking. It is very important to control sinter chemical composition and comprehensive performance. In this paper, a predictive system for sinter chemical composition FeO and the sinter yield was established based on BP neural network, which was trained by actual production data. The MATLAB m file editor was used to write code directly in this paper.The application results show that the prediction system has high accuracy rate, stability and reliability, the sintering productivity was improved effectively.

Abstract: The principal objective of blast furnace is to produce high quality molten iron at a high rate with a low consumption. It is very important to control sinter chemical composition and comprehensive performance. This is because the sinter is the main raw material for ironmaking. In this paper, a predictive system for sinter chemical composition TFe and the solid fuel consumption was established based on BP neural network, which was trained by actual production data. The MATLAB m file editor was used to write code directly in this paper. Practical application shows the applications of the system not only can reduce the work difficulty of technical personnel, but also can improve the hit ratio of production index and the productivity.