Effect of distribution of iron concentrates between pelletized and matrix feed on the preparation of blast furnace burdens from two different kinds of fine iron concentrates (magnetite and hematite) by composite agglo...Effect of distribution of iron concentrates between pelletized and matrix feed on the preparation of blast furnace burdens from two different kinds of fine iron concentrates (magnetite and hematite) by composite agglomeration process (CAP) was explored. It was found that when the mass ratio of iron concentrate A (magnetite) to iron concentrate B (hematite) in the mixed feed was constant, the proportion of iron concentrate A in the pelletized and matrix feed significantly affected the quality of CAP products. Particularly, as the proportion of iron concentrate A in the pelletized feed increased from 0 to 100%, the yield decreased from 82.11% to 79.19% and the tumbler index decreased from 71.33% to 68.27%. The mineralization characterization results indicated that when 100% iron concentrate A was used as the pelletized feed, the crystallization styles of the outer layer and the inner layer of the pellet were different, and a lot of pores exist around hematite and magnetite phases in the pelletized part, with the weak connection of pelletized and matrix part, resulting in poor strength of agglomeration product.展开更多
Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multip...Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.展开更多
基金supported by the National Natural Science Foundation of China under Grant U1960114,51774337,and U1660206the Open Sharing Fund for the Large-scale Instruments and Equipments of Central South University under Grant CSUZC201905the Fundamental Research Funds for the Central Universities of Central South University under Grant 2018zzts220.
文摘Effect of distribution of iron concentrates between pelletized and matrix feed on the preparation of blast furnace burdens from two different kinds of fine iron concentrates (magnetite and hematite) by composite agglomeration process (CAP) was explored. It was found that when the mass ratio of iron concentrate A (magnetite) to iron concentrate B (hematite) in the mixed feed was constant, the proportion of iron concentrate A in the pelletized and matrix feed significantly affected the quality of CAP products. Particularly, as the proportion of iron concentrate A in the pelletized feed increased from 0 to 100%, the yield decreased from 82.11% to 79.19% and the tumbler index decreased from 71.33% to 68.27%. The mineralization characterization results indicated that when 100% iron concentrate A was used as the pelletized feed, the crystallization styles of the outer layer and the inner layer of the pellet were different, and a lot of pores exist around hematite and magnetite phases in the pelletized part, with the weak connection of pelletized and matrix part, resulting in poor strength of agglomeration product.
基金Supported by the National Natural Science Foundation of China(21276078)"Shu Guang"project of Shanghai Municipal Education Commission,973 Program of China(2012CB720500)the Shanghai Science and Technology Program(13QH1401200)
文摘Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.
