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 …

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 …

Despite well-known limitations of Reynolds-averaged Navier–Stokes (RANS) simulations,
this methodology remains the most widely used tool for predicting many turbulent flows due …

In this paper, we propose a deep learning model to detect combustion instability using high-
speed flame image sequences. The detection model combines Convolutional Neural …

Due to the significant improvement in computing power and the rapid advancement of data
processing technologies, artificial intelligence (AI) has introduced new tools and …

In the past decades, Deep Learning (DL) frameworks have demonstrated excellent
performance in modeling nonlinear interactions and are a promising technique to move …

While the world is already facing substantial impacts of global warming, the transition
towards a sustainable-energy future is slow because of the sheer scale of global energy …

Numerical modeling of non-inertial particles dynamics is usually addressed by solving a
population balance equation (PBE). In addition to space and time, a discretization is …