Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

Essentially non-oscillatory (ENO) and weighted ENO (WENO) schemes were designed for
solving hyperbolic and convection–diffusion equations with possibly discontinuous solutions …

This investigation outlines a data-assisted approach that employs random forest classifiers
for local and dynamic submodel assignment in turbulent-combustion simulations. This …

In this work, a set of techniques is developed for the efficient temporal integration of
compressible turbulent reacting flows with stiff chemistry. The proposed approach combines …

The role of evaporation on chemical reactions in counterflow spray flames remains a key
issue due to the non-linear inter-phase interactions through mass, momentum, and energy …

Predictive high-fidelity simulations of turbulent spray combustion must capture the combined
effects of complex chemistry, multiphase evaporating flow and spray-flame interactions to …

Large eddy simulations of transcritical injection and auto-ignition of n-dodecane in a
combustion chamber are performed. To this end, a diffuse-interface method is employed that …

The Darmstadt multi-regime turbulent flame MRB26b is modelled using the Flamelet-
Generated Manifold (FGM) in the context of Large Eddy Simulation (LES). Laminar free …

Turbulence closure models that are based on a regularized deconvolution method (RDM)
are proposed for application to implicitly filtered Large-Eddy Simulation (LES). This method …