This paper reviews recent advances in understanding the structure of turbulent partially
premixed and stratified flames. The term “partially premixed” refers here to compositionally …

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 …

The goals of the present review paper are;(i) to introduce experimental facilities and
numerical tools applied to investigating inhomogeneously premixed flames,(ii) to summarize …

Detailed comparisons of LES results against measurement data are presented for the
turbulent lean and rich stratified Cambridge flame series. The co-annular methane/air burner …

In addition to the complexities arising in non-reacting turbulent shear flows, the presence of
highly exothermic chemical reactions introduces new difficulties. This central problem in …

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 …

Abstract The Cambridge/Sandia turbulent stratified flame (SwB5) is simulated with the LES
and Flamelet-Generated Manifolds (FGM) combustion model. Three 3D FGM manifolds are …

The low-temperature oxidation of hydrocarbon fuels has received increasing attention as
advanced engines seek to operate in less conventional combustion regimes. Large n …

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 …

The sub-grid scale probability density function equation is rearranged in order to separate
the resolved and sub-grid-scale (sgs) contributions to the sgs mixing term. This allows …