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VERSION:2.0
METHOD:PUBLISH
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ORGANIZER;CN='8th ECIC & 9th ICSTI 2022':MAILTO:info@ecic-icsti.com
LOCATION:Room „Focke Wulf“
SUMMARY:Simulation aided extraction of conversion rates of auxiliary reducing agents (ARAs)
DESCRIPTION:Injection of auxiliary reducing agents (ARAs) is a common approach to replace metallurgical coke in the blast furnace iron making process. A variety of ARAs is currently used, e.g. natural gas, coke oven gas, pulverized coal, heavy and waste oil, biomass, and carbonaceous dust. Conversion rates of ARAs are hardly available in literature, which makes the optimization of the ARA injection process and the evaluation of new ARAs troublesome. Identifying new ARAs requires suitable experimental setups and accurate methods for the extraction of the conversion rates. Experiments should reproduce the conversion conditions of the raceway zone of blast furnaces. Significant temperature and species concentration stratification might occur in such experimental equipment. A combined methodology using CFD simulations and experimental data can be used to obtain accurate conversion rates. Spatially resolved temperature, velocity, and species concentration profiles can be obtained via CFD simulations. In addition, accurate residence times can be extracted from these simulations via Lagrangian particle tracking. In case of strong stratification effects, the simulated profiles are superior to the typically assumed constant temperature, velocity, and species concentrations. Usually residence times are estimated by assuming plug flow. These residence times deviate from the experimental ones, since flow phenomena, e.g. vortexes or radial velocity profile, are neglected when assuming plug flow. Using realistic temperature and species concentration profiles as well as residence times refines the accuracy of the extracted conversion rates and kinetic parameters.
In this work, we first introduce a CFD approach for the simulation of experimental equipment and the methods to determine the transient temperature and species concentration profiles. Subsequently, we introduce and discuss a computer aided kinetic extraction algorithm and compare their results with kinetic parameters determined by traditional approaches.

CLASS:PUBLIC
DTSTART:20220631T104500
DTEND:20220631T111000
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