Multi-objective Optimization of Burner Arrangement in a Regenerative Aluminum Melting Furnace Based on Non-dominated Sorting Genetic Algorithm-II
WANG Ji-min, YAN Hong-jie ZHOU Jie-min LI Shi-xuan， GUI Guang-chen，
School of Metallurgy and Resource, Anhui University of Technology School of Energy and Power Engineering, Central South University School of Energy and Power Engineering, Central South University SuZhou Longray Thermal Technology Co. Ltd. SuZhou Longray Thermal Technology Co. Ltd.
Abstract：Based on the features of melting process of regenerative aluminum melting furnaces, a mathematical model with user-developed burner reversing and burning capacity model and melting model, was established. Based on validating results by heat balance test for an aluminum melting furnace, CFD software FLUENT was used to simulate the coupling field between aluminum bath and combustion space. Considering influence analysis of burner arrangement on the performance of regenerative aluminum melting furnace, the relationship between burner arrangement and evaluation criteria was built using non-linear regression. Non-dominated sorting genetic algorithm-II was used to deal with multi-objective optimization for burner arrangement. The results show that the minimum RSD (relative standard deviation) of aluminum temperature (2.65%), dimensionless melting time (0.82) and RSD of furnace temperature (14.03%) could be obtained under the optimum conditions of vertical angle of burner 23.56o, height of burner 1471.81 mm, and horizontal angle between burners 62.05o.
2012, Vol. 12 
