The simulation of turbulent flames fully resolving the smallest flow scales and the thinnest
reaction zones goes along with specific requirements, which are discussed from …

A unified modelling framework for all unresolved terms in the filtered progress variable
transport equation in large-eddy simulations of turbulent premixed flames is proposed, using …

A purely data-driven modelling approach using deep convolutional neural networks is
discussed in the context of Large Eddy Simulation (LES) of turbulent premixed flames. The …

This paper presents results of Artificial Neural Networks (ANN) applications to sub-grid
Large Eddy Simulation (LES) model. The training data for the ANN is provided by simulation …

Data-driven modelling in fluid mechanics is a promising alternative given the continuous
increase of computational power and data-storage capabilities. Highly non-linear flows …

In the context of large eddy simulations, deconvolution is an attractive alternative for
modeling the unclosed terms appearing in the filtered governing equations. Such methods …

Discrete filters are used in numerous digital signal processing applications and numerical
simulations, for anti-aliasing, de-noising, and post-processing. Our specific interest is for …

The functionality of computational fluid dynamics (CFD) for turbulent flows is limited by huge
computational demands which prevent any detailed long-term studies. In this publication, we …

In large-eddy simulations (LES) of multicomponent and fully compressible flows, the
spatially filtered pressure needs to be evaluated, ie the pressure averaged over a volume …

The unresolved scalar variance in large-eddy simulations of turbulent flows is a fundamental
physical and modelling parameter. Despite its importance, relatively few algebraic models …