Abstract
The Flameless Combustion (FC) regime has been pointed out as a promising combustion technique to lower the emissions of nitrogen oxides (NOx) while maintaining low CO and soot emissions, as well as high efficiencies. However, its accurate modeling remains a challenge. The prediction of pollutant species, especially NOx, is affected by the usually low total values that require higher precision from computational tools, as well as the incorporation of relevant formation pathways within the overall reaction mechanism that are usually neglected. The present work explores a multiple step modeling approach to tackle these issues. Initially, a CFD solution with simplified chemistry is generated [both the Eddy Dissipation Model (EDM) as well as the Flamelet Generated Manifolds (FGM) approach are employed]. Subsequently, its computational cells are clustered to form ideal reactors by user-defined criteria, and the resulting Chemical Reactor Network (CRN) is subsequently solved with a detailed chemical reaction mechanism. The capabilities of the clustering and CRN solving computational tool (AGNES—Automatic Generation of Networks for Emission Simulation) are explored with a test case related to FC. The test case is non-premixed burner based on jet mixing and fueled with CH4 tested for various equivalence ratios. Results show that the prediction of CO emissions was improved significantly with respect to the CFD solution and are in good agreement with the experimental data. As for the NOx emissions, the CRN results were capable of reproducing the non-monotonic behavior with equivalence ratio, which the CFD simulations could not capture. However, the agreement between experimental values and those predicted by CRN for NOx is not fully satisfactory. The clustering criteria employed to generate the CRNs from the CFD solutions were shown to affect the results to a great extent, pointing to future opportunities in improving the multi-step procedure and its application.
Highlights
Combustion of fossil fuels and industrial processes were estimated to contribute with around 65% of all anthropogenic greenhouse gases emissions in 2010, while being responsible for ∼85% of anthropogenic CO2 emissions (IPCC, 2014)
In an attempt to overcome the challenges in predicting emissions at affordable computational costs, a three-step approach is adopted in the current research: (1) solution of the flow-field with Computational Fluid Dynamics (CFD) using simplified chemistry and a turbulence-chemistry interaction model, (2) clustering of computational cells into ideal reactors based on criteria imposed to the CFD solution, and (3) solution of the generated Chemical Reactor Network (CRN) with detailed chemical reaction mechanisms
Velocity direction, YCH4 and YH2O are employed as clustering criteria, the nitrogen oxides (NOx) trend obtained with GRI 2.11 reaction mechanism is monotonic and its slope is the opposite of the experimental data: condition a had the highest NOx value
Summary
Combustion of fossil fuels and industrial processes were estimated to contribute with around 65% of all anthropogenic greenhouse gases emissions in 2010, while being responsible for ∼85% of anthropogenic CO2 emissions (IPCC, 2014). While there have been efforts to reduce emissions, the global CO2 emissions have been increasing every year (International Energy Agency, 2018). Most scenarios developed for the future energy supply largely involve the combustion of biofuels, biomass, synthetic fuels, or hydrogen (Ellabban et al, 2014; Scarlat et al, 2015; Nastasi and Basso, 2016). Progress in combustion technology is necessary for the energy transition and for the long term solutions that are being considered (Paltsev et al, 2018)
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