Markus Klein

The effects of preferential diffusion and chemical kinetics on reaction zone structure and combustion characteristics in turbulent premixed syngas–air flames are investigated using direct numerical simulation. Freely propagating statistically planar flames with varying H2/CO composition, equivalence ratio, and turbulence intensity are analyzed within the thin reaction zones regime. The disparity in molecular diffusivities and reaction rates of H2 and CO leads to pronounced segregation of their isosurfaces, resulting in differences in propagation and consumption rates and flame surface wrinkling. Preferential diffusion of H2, characterized by its low Lewis number, promotes rapid transport and consumption within the reaction zone, whereas CO oxidation remains slower and is governed by OH availability. Local equivalence ratio varies non-monotonically across the flame front, with a decrease from the unburned gas side followed by a recovery toward the burned gas region. This behavior is attributed to preferential diffusion induced redistribution of hydrogen-, carbon-, and oxygen-containing species. Flame index analysis indicates a departure from the classical lean-premixed flame structure toward the burned gas side of the flame front. This departure occurs over a wider temperature range for H2 than for CO, reflecting the stronger influence of preferential diffusion on H2 transport. Local segregation modifies the transport–reaction balance experienced by fuel components within a lean-premixed syngas–air flame. The qualitative behavior remains consistent across the conditions considered. The results highlight the limitations of single-scalar modeling approaches and emphasize the need for high-fidelity models that account for preferential diffusion induced equivalence ratio stratification in turbulent premixed syngas–air flames.

Accurate prediction of Flame-Wall Interactions (FWI) is crucial for the design of compact, high-efficiency combustors but remains a significant challenge for Reynolds-Averaged Navier-Stokes (RANS) simulations. This study presents the development and validation of a lightweight data-driven closure for the mean reaction rate, trained on high-fidelity Direct Numerical Simulation (DNS) data of a V-shaped turbulent premixed flame. To ensure numerical stability and physical consistency, the training methodology incorporates a logarithmic transformation of the reaction rate target and a novel error-function transformation of the wall distance, effectively localizing the model’s sensitivity to the near-wall quenching zone. A-priori validation demonstrates that the neural network accurately captures the mean reaction rate statistics and extrapolates successfully to unseen spatial regions. However, a-posteriori assessment in coupled RANS simulations reveals a critical sensitivity to input feature consistency. The full-feature model (7 input parameters), which includes turbulent kinetic energy and dissipation rate as inputs, fails to predict the correct quenching behavior due to significant discrepancies between the DNS-extracted turbulence quantities used for training and the corresponding quantities obtained from RANS. In contrast, a reduced-feature model (3 input parameters), relying exclusively on the mean progress variable, its gradient, and the transformed wall distance, demonstrates remarkable robustness. By decoupling the prediction from uncertain turbulence quantities, the model with 3 input parameters accurately reproduces the V-flame structure, achieving performance comparable to a manually tuned algebraic closure. Furthermore, the reduced model exhibits strong generalization capabilities, successfully predicting the transient physics of a Head-On Quenching (HOQ) configuration that was not present in the training dataset. These findings highlight that for data-driven RANS closures, selecting input features that remain consistent across fidelity levels, is paramount for achieving predictive stability and generalization.

This study investigates the scale effect in hydrogen-air explosions using high-fidelity 2D and 3D numerical simulations with detailed chemistry. Simulations are conducted in an obstacle-laden channel, varying the geometric scaling factor, hydrogen mole fraction and dimensionality. Results show that flame acceleration increases significantly with geometric scale, primarily due to the enhanced growth of the turbulent flame surface area. Additionally, the local burning rate per unit flame area exhibits a complex dependency on scale and mixture composition, characterized by flame stretch and Markstein numbers, particularly in lean mixtures. It is found that the normalized critical distance to reach a specific velocity decreases as a power-law with increasing scale, confirming that explosions accelerate more effectively over shorter relative distances in larger facilities. While 2D simulations suggest that the corresponding power-law exponents are consistent across a wide range of equivalence ratios, 3D results reveal a critical deviation. The scale effect is significantly more pronounced in 3D than in 2D, where the flame acceleration is found to be significantly stronger and this holds particularly for lean mixtures. The findings are consistent with scale-dependent experimental results obtained in the laboratory-scale MiniRUT and the industrial-scale RUT facilities. They further demonstrate that two-dimensional approximations may substantially underpredict the scale sensitivity of lean hydrogen explosions. In this case, 3D effects are identified as crucial for accurately predicting the severity of hydrogen explosions.

The Taylor–Green vortex (TGV) serves as a canonical benchmark for studying the transition from laminar to turbulent flow in the absence of solid boundaries. Despite its widespread use in turbulence model validation, the degree to which the TGV exhibits true isotropy and homogeneity, particularly at late stages of decay, remains insufficiently examined. This study employs high-order numerical simulations to investigate these properties for both the standard and isotropic variants of the TGV. Statistical measures, including Reynolds stress anisotropy, coherent structure functions, homogeneity indices and integral length scales, are used to assess flow behaviour over time. Results show that the standard TGV remains anisotropic and inhomogeneous even during late decay stages, with unequal longitudinal length scales and directionally dependent homogeneity indices. The isotropic TGV maintains isotropy by design but still deviates from the characteristics of ideal homogeneous isotropic turbulence, exhibiting larger transverse than longitudinal length scales. Both configurations reveal persistent spatial inhomogeneities manifested as fixed peaks in turbulent kinetic energy and the coherent structure function of plane-averaged statistics. The findings highlight that while the isotropic TGV provides a more balanced and symmetric configuration, neither flow achieves fully homogeneous isotropic turbulence.

The present article is concerned with the modeling of primary atomization in Eulerian-Lagrangian Large Eddy Simulation of liquid jet breakup. Recent numerical studies have demonstrated that spray atomization does not strictly follow a large-to-small breakup cascade. Instead, numerous small droplets can directly be generated by the core jet. As these cannot be resolved in Large Eddy Simulations using interface capturing methods for primary atomization, modeling their formation by releasing small Lagrangian particles from the core jet might improve the predictive capabilities of such simulations. This study discusses a corresponding model proposed in the literature and demonstrates its application for a Large Eddy Simulation of a complex Diesel-like spray. The results indicate a promising performance, but also highlight the need for further investigation.