Quasi-Direct Numerical Simulation of Turbulence–Flame Interactions in a High-Karlovitz-Number Ammonia Premixed Jet Flame

Ammonia (NH3) is considered a key fuel for future carbon-neutral energy systems. Understanding its combustion characteristics under intense turbulence with high Karlovitz (Ka) numbers is crucial for industrial applications. In this study, a three-dimensional quasi-direct numerical simulation (quasi-DNS) is performed on an experimental premixed ammonia jet flame at a Ka number of 1643. The simulation is conducted using the open-source computational platform DeepFlame, employing a minimum grid resolution of 56 μm and second-order spatial and temporal discretization schemes. The chemical system is modeled using a semi-detailed mechanism comprising 26 species and 100 elementary reactions. The simulation results show good agreement with laser-based diagnostic measurements. The general flame structure obtained from the simulation is consistent with fundamental combustion theory. In particular, turbulent eddies are observed to penetrate and broaden the reaction zone, with this effect intensifying downstream. Based on these results, turbulence–chemistry interactions and NO formation characteristics are systematically analyzed. For turbulence–chemistry interactions, the flame surface density transport theory is employed to clarify the roles of tangential strain rate, curvature stretch, and convection in governing the flame surface density distribution. Regarding NO formation, NO is primarily generated through the HNO and thermal pathways and consumed via the N2O and NHi pathways, leading to a net positive production on the product side of the flame. Furthermore, the influence of progress variable definitions is demonstrated in both turbulence–chemistry interactions and NO formation. It is found that the H2O-based progress variable captures more comprehensive information about the spatial and temporal distribution of chemical processes. These findings provide valuable insights into ammonia combustion under high-Ka conditions and contribute to the development of high-fidelity simulation databases essential for future modeling efforts.