Influence of the bed morphology in the direct reduction process

Abstract

Steel is the world’s most important engineering material. It is used in all aspects of everyday life, has been instrumental in shaping modern economies through technological advancements, and imagining today’s world without its influence is difficult. However, steel production is highly carbon intensive. On average, making one metric ton of steel results in 1.8 metric tons of CO2 emissions. Ironmaking through direct reduction stands out as the most promising alternative to the blast furnace to meet the ambitious decarbonization targets, leveraging green hydrogen as its primary reducing agent. Recent articles [1,2] have highlighted significant gaps in understanding the chemical, physical, and mechanical intricacies of direct reduction across various scales. The present contribution deals with the hydrogen reduction of 0.5 kg iron ore fixed-beds as a scale-bridging step in the endeavor development of advance simulation tools to optimize process conditions. In particular, the focus lies on the influence of the bed morphology in the direct reduction process. To this end, multiple three-dimensional reactive particle-resolved Computational Fluid Dynamics (CFD) simulations [3] have been conducted with varying degrees of accuracy of the bed of pellets. This ranges from uniform-sized spherical particles up to the direct reconstruction of a real bed from CT-scan data, as seen in Figure 1. The detailed simulations are used to comprehensively analyze local insights, such as the presence of gas pockets, the spatial distribution of the reduction, the prevailing limiting regime (internal diffusion, chemical reactions, external mass transfer) of the individual pellets. The CFD simulations are further used to output global results, including bulk bed porosity, overall conversion, and pressure drop across the bed. By comparing the results of different bed structures, we elucidate the effects of pellet shape irregularities and the degree of acceptable simplifications and we provide recommendations for further scale up.