A fully dynamic mixing time‐scale model for the sparse Lagrangian multiple mapping conditioning approach

Multiple mapping conditioning / large eddy simulation (MMC-LES) is a promising model for turbulence-chemistry interactions, successfully applied to simulate different combustion regimes involving gaseous, liquid, and solid fuels. MMC-LES attempts produce accurate molecular mixing by localising in an independent, composition-like reference space. In the MMC model, between two stochastic particles defined based on Lagrangian time-scale τL, which as ratio of subgrid-scale mixture fraction variance (fL′2˜) scalar dissipation rate (χL), typically modelled algebraically, fixed values global constants at all spatial locations. Accurate modelling τL essential towards predicting conditional fluctuations, otherwise highly challenging if same set static are used locations complex flames with varying extinction/re-ignition. Herein, fully dynamic (dyn-aISO) proposed within framework, dynamically evaluates fL′2˜ χL, essentially local coefficient variable turbulent Schmidt number, respectively, eliminating need specifying tuneable constants. This novel dyn-aISO pilot-stabilised Sandia flame series increasing extinction levels. The unconditional profiles compositional scalars from new compared those (st-aISO) uses constant (stCf-aISO). Numerical results timescale models deviate each other F having high jet Reynolds number. With improvement micro-mixing accurately captures transient behaviour complete series, could be obtained tuning role mass diffusivities, residual fraction, distance, predictions reactive also explored.