Corrosion Mechanism of Alumina-magnesia Dry Materials for Smelting Manganese/chromium Steel in Coreless Medium Frequency Induction Furnaces

Alumina-magnesia dry materials are widely used in induction furnace linings, but they show different kinds of damage when melting different kinds of alloy steel. In this paper, the chemical composition, phase composition, and microstructure of the post-use dry materials for the working liners melting different kinds of steel were evaluated. Furthermore, the corrosion mechanism of the steel on the furnace lining materials was comprehensively analyzed. The findings reveal a significant ability of the Mn element in the molten steel to diffuse and penetrate into the refractories. Mn oxidizes to form MnO at the steel-refractory interface, and then forms a liquid phase with Al_(2)O_(3). The Cr element is dissolved into corundum and spinel of the refractories, resulting in lattice defects and structural damage of the materials. TiO2reacts with Al_(2)O_(3) to form Al_(2)TiO_(5), which plays a crucial role in preventing crack formation and propagation. Part of Ti4+dissolves into magnesia-alumina(MA), densifying the materials. TiO2also slows down the reaction between the Cr element and refractory components, further improving the corrosion resistance of the materials.

Numerical investigation on freeze-drying of aqueous material frozen with pre-built pores

Freeze-drying of the initially porous frozen material with pre-built pores from liquid material was found experimentally to save drying time by over 30% with an initial saturation being 0.28 compared with the conventional operation with the initial saturation being 1, using mannitol as the solid material. In order to understand the mass and heat transfer phenomena of this novel process, a two-dimensional mathematical model of coupled mass and heat transfer was derived with reference to the cylindrical coordinate system. Three adsorption–desorption equilibrium relationships between the vapour pressure and saturation value namely, power-law, Redhead's style and Kelvin's style equation, were tested. Kelvin's style in exponential form of adsorption equilibrium relation gave an excellent agreement between the model prediction and experimental measurement when the equation parameter, γ, of 5000 was applied. Analyses of temperature and ice saturation profiles show that additional heat needs to be supplied to increase the sample temperature in order to promote the desorption process. Simulation also shows that there is a threshold initial porosity after which the drying time decreased with the increase in the initial porosity. Enhanced freeze-drying is expected to be achieved by simultaneously enhancing mass and heat transfer of the process.

Temperature and Humidity Control System Identification Based on Neural Network in Heating and Drying System

Artificial neural network has unique advantages for massively parallel processing, distributed storage capacity and self-learning ability. The paper mainly constructs neural network identifier and neural network controller for system identification and control on temperature and hmnidity of heating and drying system of materials. And the paper introduces the structure and principles of neural network, and focuses on analyzing learning algorithm, training algorithm and limitation of the most widely applied multi-layer feed-forward neural network （ BP network） , based on which the paper proposes introducing momentum to improve BP network.