Comprehensive knowledge of local flame displacement speed, S d, in turbulent premixed
flames is crucial towards the design and development of hydrogen fuelled next-generation …

Velocity dilatation and total, solenoidal, and dilatational dissipation rates of the total flow
kinetic energy are extracted from three different direct numerical simulation databases …

Direct numerical simulation data obtained from four pairs of turbulent, lean hydrogen–air,
complex-chemistry flames are analysed to explore the influence of molecular diffusion on …

An analytical framework is proposed to explore the structure and kinematics of iso-scalar
fields. It is based on a two-point statistical analysis of the phase indicator field which is used …

This study investigates the application of machine learning, specifically Fourier neural
operator (FNO) and convolutional neural network (CNN), to learn time-advancement …

Recent advancements in the integration of artificial intelligence (AI) and machine learning
(ML) with physical sciences have led to significant progress in addressing complex …

The gradients of the mixture fraction and the reaction progress variable (or equivalently their
scalar dissipation rates) play a major role in flamelet theory. Therefore, having appropriate …

The influence of water droplet injection on the propagation rate of statistically planar
stoichiometric n-heptane-air flames has been analysed based on three-dimensional carrier …

Starting with an integral formulation of average mass flow rate through an ensemble of
isotherms constituting a statistically planar, turbulent premixed flame, a scaling for the …

The Darrieus–Landau instability is studied using a data-driven, deep neural network
approach. The task is set up to learn a time-advancement operator mapping any given flame …