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A multiscale combustion model formulation for NOx predictions in hydrogen enriched jet flames

par Iavarone, Salvatore ;Cafiero, Marianna ;Ferrarotti, Marco ;Contino, Francesco ;Parente, Alessandro
Référence International journal of hydrogen energy, 44, 41, page (23436-23457)
Publication Publié, 2019-08-01

Article révisé par les pairs

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Résumé :

The present paper investigates the role of combustion models and kinetic mechanisms on the prediction of NOx emissions in a turbulent combustion system where conventional and unconventional routes are equally important for NOx formation. To this end, a lab-scale combustion system working in Moderate and Intense Low-oxygen Dilution (MILD) conditions, namely the Adelaide Jet in Hot Co-flow (JHC) burner, is targeted. The Eddy Dissipation Concept (EDC) and the Partially-Stirred Reactor (PaSR) models are used for turbulence-chemistry interactions. The KEE and GRI2.11 chemical mechanisms are employed. The results show that the choice of the combustion model has a higher impact than the selection of the kinetic mechanism for the investigated cases, indicating that biases in the turbulent reactive flow closure are as important, if not more, as the level of the accuracy of the chemical scheme employed. Moreover, the sensitivity of the NO emissions to the uncertain kinetic parameters of the rate-limiting reactions of the NNH pathway is found to be significant when a detailed kinetic mechanism is used. An engineering modification of the PaSR combustion model is proposed to account for the different chemical time scales of fuel oxidation reactions and NOx formation pathways. It shows an equivalent impact on the emissions of NO than the uncertainty in the NNH pathway kinetics. At the cost of introducing a negligible mass imbalance, the adjustment leads to improved predictions of NO. The investigation establishes a possibility for the engineering modeling of NO formation in turbulent flames with a finite-rate chemistry combustion model that can incorporate a detailed mechanism at an affordable computational cost.