A pressure-coupled Representative Interactive Linear Eddy Model (RILEM) for engine simulations

Journal article, 2024

The Representative Linear Eddy Model (RILEM) was introduced by Lackmann et al. (2018) as an alternative modeling approach to simulate turbulent non-premixed combustion in engines. The model utilizes a RANS approach for turbulence and the Linear Eddy Model (LEM) with a presumed probability density function (PDF) approach for combustion closure. A distinct feature of RILEM is its potential to handle arbitrary combustion regimes and the consideration of complex physical phenomena such as differential diffusion effects. The original version of RILEM implemented a volume-based coupling between LEM and the flow solver. This work presents a new variant of RILEM, i.e., Multiple Representative Interactive Linear Eddy Model (MRILEM) based on a pressure-based coupling, to overcome some deficiencies of the original RILEM, namely statistical fidelity. Due to the introduced pressure coupling, the effects of heat losses (wall heat fluxes, latent heat of evaporation) on combustion are intrinsically included via the pressure trace. Furthermore, we introduce a new step function PDF for the progress variable defined by its mean value only. Issues with an incomplete solution space for mixture fraction and progress variable due to the stochastic nature of LEM are remedied with a PDF scaling technique, aided by a novel parameterization of the progress-variable PDF The new variant of RILEM is evaluated using part- and full-load cases of a heavy-duty metal engine. The impact of utilizing multiple LEM lines on the completeness of the solution space and its influence on the distribution of scalar values in the CFD domain was demonstrated. Results for pressure trace, flame structure, and CO emissions are analyzed and compared with simulations using the Multi-Zone Well-Mixed Model (MZWM) model and experiments. While pressure traces agree well among the different models and experiments, noteworthy differences are observed between the models regarding CO emissions and temperature. Effects of turbulence chemistry interaction were noticed when comparing MRILEM to the results of the MZWM simulation, namely flame brush and species mass fraction distribution.