Molten steel temperature prediction using a hybrid model based on information interaction-enhanced cuckoo search

This article presents a hybrid model for predicting the temperature of molten steel in a ladle furnace (LF). Unique to the proposed hybrid prediction model is that its neural network-based empirical part is trained in an indirect way since the target outputs of this part are unavailable. A modified cuckoo search (CS) algorithm is used to optimize the parameters in the empirical part. The search of each individual in the traditional CS is normally performed independently, which may limit the algorithm’s search capability. To address this, a modified CS, information interaction-enhanced CS (IICS), is proposed in this article to enhance the interaction of search information between individuals and thereby the search capability of the algorithm. The performance of the proposed IICS algorithm is first verified by testing on two benchmark sets (including 16 classical benchmark functions and 29 CEC 2017 benchmark functions) and then used in optimizing the parameters in the empirical part of the proposed hybrid prediction model. The proposed hybrid model is applied to actual production data from a 300 t LF at Baoshan Iron & Steel Co. Ltd, one of China's most famous integrated iron and steel enterprises, and the results show that the proposed hybrid prediction model is effective with comparatively high accuracy

Study on Thermophysical Properties of Arc Plasma for Melting Magnesium Oxide Crystals at Atmospheric Pressure

The thermodynamic and transport properties of magnesium oxide crystal arc plasma have been researched under local thermodynamic equilibrium in this paper. The pure CO2 plasma in the arc initiation stage and Mg-CO mixtures plasma in the stable melting stage were selected. The parameter-variation method combined with Levenberg–Marquardt algorithm (PVM-LMA) is used to solve the plasma equilibrium compositions model established by mass action law from higher to lower temperature in sequence. Taking Mg50%-CO50% plasma as an example, the plasma number density of 7500 K is calculated according to 8000 K. The results show that the PVM-LMA algorithm has the advantages of fast and high precision. The comparisons to the results of pure CO2 in previous literature are displayed and our work shows better agreement with theirs. The results of Mg-CO mixtures indicate that the chemical properties of Mg atoms are more active and easier to ionize, which can effectively improve the electrical conductivity and thermal conductivity of plasma and reduce its viscosity