Abstract

Abstract The direct-fired supercritical-CO2 (sCO2) cycle has demonstrated the ability to produce clean energy by burning hydrocarbon feed stocks under oxy-fuel conditions. High-pressure operation of the direct-fired cycle allows for more economic extraction of CO2 for carbon capture and storage. However, the presence of nitrogen impurities in the oxidizer (i.e., N2) and in fuel feed stocks (e.g., NH3) can generate NOx in the exhaust. The presence of NOx in the recycled-CO2 stream can impact the combustion process as well as the structural integrity of the system. Also, even trace amounts of nitrogen oxides (considered acid gases) can be detrimental for CO2 capture, transportation and storage at supercritical conditions. Therefore, it is critical to understand and accurately model the effects of nitrogen impurities on NOx formation and the impact of NOx in the recycled CO2 on combustion kinetics under oxy-fuel sCO2 conditions. It is also important to understand the effects of pressure with a sCO2 medium as the direct-fired sCO2 cycle operates up to 300 atm pressure. In this work, experimental and modeling work were performed to study the effect of nitrogen species on emissions as well as effect of NOx on ignition of CH4 and syngas fuels at sCO2 conditions. A chemical reactor network simulation was used to investigate the effects of nitrogen impurities in fuel and oxidizer stream on emissions from a direct-fired combustor condition. Monte Carlo simulations were also carried out to study the impact of model input variables on the emission profile. High-pressure shock tube ignition delay time experiments were performed to investigate the effect of NOx on ignition at conditions relevant to direct-fired oxy-fuel sCO2 combustion. The ignition delay time measurements were made for syngas and CH4 fuels with and without NO addition using CO2 as bulk diluent at nominal pressures around 100 atm. Experimental data showed that the presence of NO promotes the ignition at the oxyfuel sCO2 combustion conditions. Reaction sensitivity analyses and model uncertainty analyses were conducted to identify important reactions and their rate uncertainty on the model predictions, respectively.

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