Preparation process of cold bonded pellets with iron-bearing dust and sludge from steel production process

Blast furnace dust (BFD) and converter sludge (CS) were used as raw materials for preparing of cold bonded pellets (CBPs). The results showed that BFD contained high content of C, Fe and harmful element of Zn. Conversely, the CS had more Fe and Ca content and less Zn. BFD particles are mostly large and irregular in shape with poor hydrophilicity, whereas CS particles are generally smaller spherical and could bond together easily. Additionally, the main factors influencing the performance of CBPs are the binder, moisture, and pressing pressure. By controlling the mixing ratio of BFD and CS, selecting the appropriate binder and binder amount, and controlling the moisture and pressure, CBPs with a compressive strength and a falling strength of up to 142.7 N and 8.34 times, respectively, can be prepared, thus meeting the requirements of the rotary hearth furnace and the OxyCup production process.

Post-combustion artificial neural network modeling of nickel-producing multiple hearth furnace

In a nickel-producing multiple hearth furnace, there is a problem associated to the automatic operation of the temperature control loops in two of the hearths, since the same flow of air is split into two branches. A neural model of the post-combustion sub-process is built and served to increase the process efficiency of the industrial furnace. Data was taken for a three-months operating time period to identify the main variables characterizing the process and a model of multilayer perceptron type is built. For the validation of this model, process data from a four-months operating time period in 2018 was used and prediction errors based on a measure of closeness in terms of a mean square error criterion measured through its weights for the temperature of two of the hearths (four and six) versus the air flow to these hearths. Based on a rigorous testing and analysis of the process, the model is capable of predicting the temperature of hearth four and six with errors of 0.6 and 0.3 °C, respectively. In addition, the emissions by high concentration of carbon monoxide in the exhaust gases are reduced, thus contributing to the health of the ecosystem.