A two-zone jet approach for reactor network modeling of a bubbling fluidized bed boilers: NOx emission prediction method

Accurate prediction of NO x emissions from biomass and waste-derived fuels in bubbling fluidized bed (BFB) boilers relies on the correct representation of turbulent air–fuel mixing as it strongly influences nitrogen conversion pathways. This study presents a chemical reactor network (CRN) methodology for modeling turbulent reacting air jets without relying on CFD-imposed flow or temperature fields. In this approach, the jet is discretized into axial elements, each containing coupled inner and outer reactors. Lateral mass exchange between these reactors is computed from mass and momentum balances, while composition and temperature within the reactors are calculated using detailed chemistry coupled with a simplified heat transfer model. The jet model is applied to the secondary and tertiary air jets of a 107 MWth BFB boiler operating under three conditions with different fuel compositions, bed temperatures, and air flow rates. This model is combined with plug-flow reactors for other sections of the BFB boiler, forming a unified CRN that is calibrated solely using measured temperature profiles from a single operating condition. Validation against full-scale measurements, including axial concentration profiles of carbon and nitrogen species as well as stack emissions, shows good agreement, with predicted stack NO exhibiting relative errors of 22%, 8%, and 10% for the three operating conditions. Comparison with a single-zone jet model demonstrates that gradual mixing within the two-zone formulation is essential for capturing NO reduction in the jet region. Sensitivity analysis shows that the model predictions exhibit limited sensitivity to moderate variations in model parameters, supporting the use of this framework as a standalone approach for predicting NO x emissions in BFB boilers.