Multi-objective collaborative optimization of metallurgical properties of iron carbon agglomerates using response surface methodology

Abstract

Iron carbon agglomerates (ICA) are used to realize low-carbon blast furnace ironmaking. In this study, the central composite design based on response surface methodology was used to synergistically optimize the compressive strength, reactivity, and post-reaction strength of ICA. Results show that the iron ore addition ratio significantly influences the compressive strength, reactivity, and post-reaction strength of ICA. The iron ore addition ratio and carbonization temperature or the iron ore addition ratio and carbonization time exert significant interaction effects on the compressive strength and reactivity of ICA, but it has no interaction effects on the post-reaction strength of ICA. In addition, the optimal process parameters are as follows: iron ore addition ratio of 15.30wt%, carbonization temperature of 1000°C, and carbonization time of 4.27 h. The model prediction results of compressive strength, reactivity, and post-reaction strength are 4026 N, 55.03%, and 38.24%, respectively, which are close to the experimental results and further verify the accuracy and reliability of the models.

Keywords

iron carbon agglomerates / compressive strength / reactivity / post-reaction strength / multi-objective collaborative optimization / response surface methodology

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