Integrated Experimental and Computational Studies Of MILD Oxy-Coal Combustion

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1704141 Sutherland, James C.Oxy-coal combustion (OCC) is a viable technology that produces a concentrated carbon dioxide (CO2) stream suitable for sequestration. However, nearly all coal power plants in operation today, and most slated for construction, are air-fired power plants. Moderate and Intensive Low oxygen Dilution (MILD) combustion has been proposed as a technique to achieve higher combustion efficiencies, to produce higher uniformity in reaction zones, to reduce pollutant formation and to provide more uniform heat flux. This project aims to combine these two technologies and to investigate fundamental questions surrounding MILD oxy-coal combustion (MILD-OCC). Improved understanding of MILD-OCC can lead to viable retrofits or new designs for boilers that will not only improve efficiency but also provide sequestration-ready CO2 streams.This research is motivated by the hypothesis that simulation and experiments, analyzed together over a multi-scale range of conditions, can provide valuable insights into MILD-OCC systems. Such insights can be used to design cleaner, more efficient, and more reliable coal combustion systems. A multiscale, hierarchical approach will be undertaken whereby state of the art experiments obtained under well-controlled conditions can be used to study individual phenomena (particle ignition, char oxidation/gasification, etc.), and this understanding can be moved up-scale to more complex and practical systems. This research will combine existing experimental data of OCC with new data to be gathered at Tsinghua University on MILD-OCC systems and with multiscale modeling and simulation to improve understanding of MILD-OCC systems. The simulation and experimental work will be closely interwoven, with experimental results used to validate models and simulations used to guide experimental measurement needs. Additionally, focus on both instrument models (facilitating comparison between experiment and simulation) as well as techniques for upscaling models, beginning with high-fidelity models and coarsening to obtain models suitable for implementation, will be pursued. This award is co-funded by the CBET Environmental Sustainability program and the Office of International Science and Engineering.