Implementation of the Scalar Dissipation Rate in the REDIM Concept and its Validation for the Piloted Non-Premixed Turbulent Jet Flames

In order to address the impact of the concentration gradients on the chemistry – turbulence interaction in turbulent flames, the REDIM reduced chemistry is constructed incorporating the scalar dissipation rate, which is a key quantity describing the turbulent mixing process. This is achieved by providing a variable gradient estimate in the REDIM evolution equation. In such case, the REDIM reduced chemistry is tabulated as a function of the reduced coordinates and the scalar dissipation rate as an additional progress variable. The constructed REDIM is based on a detailed transport model including the differential diffusion, and is validated for a piloted non-premixed turbulent jet flames (Sandia Flame D and E). The results show that the newly generated REDIM can reproduce the thermo-kinetic quantities very well, and the differential molecular diffusion effect can also be well captured.

An out-of-distribution-aware autoencoder model for reduced chemical kinetics

<p style='text-indent:20px;'>While detailed chemical kinetic models have been successful in representing rates of chemical reactions in continuum scale computational fluid dynamics (CFD) simulations, applying the models in simulations for engineering device conditions is computationally prohibitive. To reduce the cost, data-driven methods, e.g., autoencoders, have been used to construct reduced chemical kinetic models for CFD simulations. Despite their success, data-driven methods rely heavily on training data sets and can be unreliable when used in out-of-distribution (OOD) regions (i.e., when extrapolating outside of the training set). In this paper, we present an enhanced autoencoder model for combustion chemical kinetics with uncertainty quantification to enable the detection of model usage in OOD regions, and thereby creating an OOD-aware autoencoder model that contributes to more robust CFD simulations of reacting flows. We first demonstrate the effectiveness of the method in OOD detection in two well-known datasets, MNIST and Fashion-MNIST, in comparison with the deep ensemble method, and then present the OOD-aware autoencoder for reduced chemistry model in syngas combustion.</p>

Validation of an Eulerian Stochastic Fields Solver Coupled with Reaction–Diffusion Manifolds on LES of Methane/Air Non-premixed Flames

The Eulerian stochastic fields (ESF) combustion model can be used in LES in order to evaluate the filtered density function to describe the process of turbulence–chemistry interaction. The method is typically computationally expensive, especially if detailed chemistry mechanisms involving hydrocarbons are used. In this work, expensive computations are avoided by coupling the ESF solver with a reduced chemistry model. The reaction–diffusion manifold (REDIM) is chosen for this purpose, consisting of a passive scalar and a suitable reaction progress variable. The latter allows the use of a constant parametrization matrix when projecting the ESF equations onto the manifold. The piloted flames Sandia D–E were selected for validation using a 2D-REDIM. The results show that the combined solver is able to correctly capture the flame behavior in the investigated sections, although local extinction is underestimated by the ESF close to the injection plate. Hydrogen concentrations are strongly influenced by the transport model selected within the REDIM tabulation. A total solver performance increase by a factor of 81% is observed, compared to a full chemistry ESF simulation with 19 species. An accurate prediction of flame F instead required the extension of the REDIM table to a third variable, the scalar dissipation rate.