Abstract
The energy performance of the ore-thermal furnace is affected by the electrical and thermal parameters of the charge, which vary depending on its composition and heating temperature. Namely: specific electrical resistance (SER), mass heat capacity, specific density and coefficient of thermal conductivity. Many scientists experimentally established the mathematical dependence of these parameters on temperature. However, in order to ensure the adequacy of the complex model of the ore-thermal furnace in the mode of its adjustment for a specific process, it is necessary to determine the intervals of possible values of the specified parameters of the charge loaded into it. In the future, the optimization problem considers all possible combinations of their discrete values within the previously mentioned limits, and the one of them that provides the minimum prediction error of the model is determined. If we consider the charge as a whole, then the intervals of the value of the specific electrical resistance depending on the temperature range from 2.055 to 9.249 Ohm·m at low temperatures and from 0.002 to 0.018 Ohm·m in the range of 1200-13000С, depending on the percentage composition of its components. The largest fluctuations in the thermal conductivity values of the charge are present in the temperature range from 500 оС to 900 оС and are 0.754—1.93 W/m·оС. The largest fluctuations in the heat capacity values of the charge are characteristic of high temperatures. Among other input parameters of the complex model of the operation of the ore-thermal furnace, there is also the bulk density of the charge, which also has its fluctuation limits, but only the limits of its components are known. The formula for calculating the density of the charge as a whole is proposed and its maximum and minimum values are established. The obtained information is sufficient to carry out more accurate technological calculations regarding the specified properties at different temperatures and components of the charge from which certain grades of ferroalloys are smelted. Therefore, in order to set an optimization problem regarding the minimization of the possible forecast error of the proposed model, it is possible to determine their specific oscillation intervals. In the further selection of the parameter values, they will be used as input data in the complex mathematical model of the ore-thermal furnace operation, which makes it possible to dynamically monitor the electrical and thermal processes that are directly related to each other and occur during the smelting of ferroalloys.
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