Development of a Fast Modeling Approach for the Prediction of Scrap Preheating in Continuously Charged Metallurgical Recycling Processes

Abstract

Improving the overall energy efficiency of processes is necessary to reduce costs, lower the specific energy consumption and thereby reduce the direct or indirect emission of gases that contribute to climate change. In many metallurgical processes, a large amount of energy is lost with the off-gas. In metallurgical recycling processes, off-gas often can be used to preheat the to-be-recycled metal scrap, leading to significantly higher energy efficiency. However, the application of preheating has the disadvantage that it often requires more precise planning in the design and better control of the process. In this paper, a simplified look at a continuously charged scrap preheating aggregate for the widely used electric arc furnace (EAF) in the steel processing industry is used as illustration. Continuous scrap charging in EAF-type furnaces in general has much higher demands on process control and general process knowledge, which is why they are found only very rarely. General issues and basic modeling approaches to mitigate such issues allowing a better process control will be described. In particular, a fast, one-dimensional modeling approach for the determination of the temperature distribution inside a constantly moving scrap bulk, with hot air (or exhaust gases) flowing through it, will be described. Possible modeling applications, assumptions, possible enhancements and limitations are shown. The first results indicate that this approach can be used as a solid basis for the modeling of scrap bulks with thermally thin parts, consisting of materials with similar thermodynamic material properties. Therefore, as a basis, this approach may help improve the design and control of future or existing preheating devices in metal recycling processes.