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 …
S Zhang, C Zhang, B Wang - Combustion and Flame, 2024 - Elsevier
Recently, artificial neural networks (ANNs) have been frequently embedded in computational fluid dynamics (CFD) solvers as surrogate tools for solving chemical reaction …