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Mass loss and direct reduction characteristics of iron ore-coal composite pellets under different technological parameters were investigated. Meanwhile, changes of iron phase at different temperatures were analyzed by using X-ray diffraction (XRD), and characteristics of crushed products were studied by using a scanning electron microscope (SEM). The results showed that heating rate had little influence on the reduction, but the temperature played an important role in the reduction process. The mass loss rate increased rapidly from 800 to 1100 °C. The reduction process can be divided into three steps which correspond to different temperature ranges. Fe2O3began to transform into Fe3O4below 500 °C, and FeO was reduced into Fe from 900 °C. At 900 °C, the reduction product showed a clear porous structure, which promoted the reduction progress. At 1000 °C, the metallic Fe dominated the sample, and the reduction reached a very high degree.

Mass loss and direct reduction characteristics of iron ore-coal composite pellets under different technological parameters were investigated. Meanwhile, changes of iron phase at different temperatures were analyzed by using X-ray diffraction (XRD), and characteristics of crushed products were studied by using a scanning electron microscope (SEM). The results showed that heating rate had little influence on the reduction, but the temperature played an important role in the reduction process. The mass loss rate increased rapidly from 800 to 1100 °C. The reduction process can be divided into three steps which correspond to different temperature ranges. Fe2O3began to transform into Fe3O4below 500 °C, and FeO was reduced into Fe from 900 °C. At 900 °C, the reduction product showed a clear porous structure, which promoted the reduction progress. At 1000 °C, the metallic Fe dominated the sample, and the reduction reached a very high degree.

According to the status of the current engineering construction field in our country, in order to adapt to the requirements of engineering construction project risk evaluation, this paper discuss establishing a reasonable risk evalluation index system and a model of effective risk evaluation. By analyzing the advantages and disadvantages of the general model of risk evaluation, determine the risk evaluation model combined with BP neural network with AHP; secondly,establish a risk evaluation index system; once again,illustrate the method which represents the correlation between evaluation index system and the degree of risk; finally, establish a reasonable BP neural network model.Key Word:Evaluation index; Risk Evaluation ;AHP;BP Neural Network; Model Construction