A mathematical and computational model of furnaces for continuous steel strip processing

Abstract This study presents the development of a mathematical and computational model for simulating and controlling of an annealing process of a silicon steel strip that occurs in an industrial combustion furnace. Both the combustion process and the strip heating are simulated by using energy and mass balances inside the industrial furnace. These balances are performed considering important variables, such as composition, temperature and pressure of gas components, adiabatic flame and environmental temperature. Besides the balances, an optimization technique is implemented in order to estimate the temperature distribution of the strip at any time. The optimization technique used is the Golden section algorithm that minimizes a least square function based on difference of the experimental and theoretical temperature in two different locations of the strip. All steps of the software development are presented here: the combustion and annealing process, the energy and mass balance and the fundamentals of the optimization process. The efficiency of the software is then demonstrated through an analysis and application of data acquired from operational conditions in continuous annealing lines of a steel company. This study is concluded presenting a discussion about the uncertainty and error sources the can be present in the results. The software SIMCO—RB2 seems to be a very powerful tool in the simulation of metal annealing processes.