GEP-based Modeling for Predicting Sponge Iron Metallization in Persian Direct Reduction (PERED) Method

 The Persian direct reduction method (PERED) is a suitable method for producing sponge iron on an industrial scale. The challenge of all sponge iron production plants is to supply sponge iron with suitable metallization to steel factories. Accordingly, determining and adjusting the various parameters affecting metallization in each plant is necessary to produce the appropriate amount and quality of sponge iron. In this study, first, the effects of output rate, process flow, water- steam flow rate, bustle temperature, bustle CH۴ level, CO۲ reform, average pellet size (PIDa), pellet strength (CCS), process gas water temperature, and furnace bed average temperature on spongy iron metallization were investigated. Then, an attempt was made to model the sponge iron grade produced by the PERED method using the Gene Expression Programming (GEP) software. To carry out modeling, data on the affecting variables of metallization were collected for ۵۸ days. The best R۲ values for the training and testing sets were ۰.۹۷۴ and ۰.۲۷ with a low error rate for both (۰.۰۴۷ and ۰.۳۷۶ in RMSE and ۰.۰۰۱ and ۰.۱۴۱ in MSE, respectively. The results of the sensitivity test indicated that CO۲ reform gas, bustle CH۴ level, and average pellet size had the most significant effect on metallization.

Keywords:

PERED , Direct Reduced Iron (DRI) , Gene Expression Programming (GEP) , Mathematical Modeling