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 …

This review covers the new developments in machine learning (ML) that are impacting the
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …

Combustion science is an interdisciplinary study that involves nonlinear physical and
chemical phenomena in time and length scales, including complex chemical reactions and …

Solving for detailed chemical kinetics remains one of the major bottlenecks for
computational fluid dynamics simulations of reacting flows using a finite-rate-chemistry …

This study introduces the gradient boosted decision tree (GBDT) as a machine learning
approach to circumvent the need for a direct integration of the typically stiff system of …

Flamelet-based reduced manifold tabulation is very useful to save computing time compared
to simulations of turbulent flames with detailed kinetics. However, conventional tabulation …

Chemical kinetics mechanisms are essential for understanding, analyzing, and simulating
complex combustion phenomena. In this study, a neural ordinary differential equation …

Many modeling approaches in large eddy simulation (LES) of turbulent combustion employ
a projection of the thermochemical state onto a low-dimensional manifold within state space …

The usage of artificial intelligence (AI) is increasing in many fields of research, since
complex physical problems can be 'learned'and reproduced by AI methods. Thus, instead of …

Recently, artificial neural networks (ANNs) have been frequently embedded in
computational fluid dynamics (CFD) solvers as surrogate tools for solving chemical reaction …