Study On The Influence Mechanism And Multi-Objective Optimization Of Air Excess Coefficient In Steel Rolling Heating Furnace

The reheating furnace is the main atmospheric thermal equipment in the steel industry.Furnace thermal efficiency,pollution emissions,and the oxidation and burning loss of billets are important indicators for evaluating the heating quality of a heating furnace.The air excess coefficient is the decisive factor affecting the above three indicators.Therefore,exploring the relationship between furnace thermal efficiency,NO_x pollution emissions,billet oxidation and burning loss with air excess coefficient in different heating sections,and finding out reasonable parameters for setting air excess coefficient in different heating units to guide production has important value for energy conservation and emission reduction in iron and steel enterprises,as well as improving production efficiency.This study took a regenerative heating furnace and its billet as research objects,studied the relationship between the air excess coefficient with the furnace thermal efficiency,pollution emissions,oxidation and burning loss of billets in different heating stages,and found the optimal solution for setting the air excess coefficient under different heating conditions through genetic algorithms.The regenerative heating furnace was divided into five heating units along the furnace length direction.The combustion conditions of different heating sections were simulated by changing the inlet boundary conditions of air and gas.Taking the heating flux between furnace gas and the upper surface of the billet as the boundary conditions,establishing the mathematical model for the internal heat conduction of the billet.The problem of reversing the burners in a regenerative heating furnace was simplified by averaging the nodes at both ends of the billet.In Fluent,the k-epsilon turbulent flow model,DO radiation model,component transport model,and NO_x generation mechanism model were used to perform unsteady simulation numerical calculations on the flow field,temperature field,average NO_x emission at the outlet,thermal efficiency,billet temperature,and oxidation and burning loss of the unit furnace under different air excess coefficients,in conjunction with UDF self programming.Through the simulation results analyzed the relationship between air excess coefficient and furnace thermal efficiency,NO_x emissions,billet oxidation and burning loss under different heating unit.Based on the analysis of the results of each heating section,as the excess air coefficient increases,the trend of changes in furnace thermal efficiency,NO_x emissions,and steel billet oxidation and burning loss is first increasing and then decreasing.Finally,used different economic calculation parameters as conversion indicators,and using the average NO_x emissions in different heating stages as limiting conditions,the thermal efficiency and yield under different air excess coefficients were converted into economic costs.The three-objective optimization problem was transformed into a single objective problem,an adaptive equation was established and a genetic algorithm was used to optimize the results to find the optimal solution for the air excess coefficient under different heating stages.Used the average emission of NO_x at the outlet less than50 mg/m~3 as the limiting condition,and the economic loss caused by oxidation and burning of steel billets as 4000 yuan/t,and the price of gas as 0.1 yuan/m~3,the optimal air excess coefficient operating parameters for each heating section are obtained as follows:preheating sectionα=1.275,the first heating sectionα=1.100,the second heating sectionα=1.025,the third heating sectionα=1.025,soaking sectionα=1.000.