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 …
Computational load imbalance is a well-known performance issue in multiprocessor reacting flow simulations utilizing directly integrated chemical kinetics. We introduce an …
T Yang, Y Yin, H Zhou, Z Ren - Acta Mechanica Sinica, 2021 - Springer
Predictive simulation of the combustion process in engine is crucial to understand the complex underlying physicochemical processes, improve engine performance, and reduce …
T Readshaw, LLC Franke, WP Jones… - Combustion and …, 2023 - Elsevier
The numerical integration of the differential equations describing chemical kinetics consumes the majority of computational time in combustion simulations that involve direct …
W Zhang, S Karaca, J Wang, Z Huang… - Combustion and Flame, 2021 - Elsevier
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 …
A bluff-body stabilised turbulent jet flame burning in a stratified mode of combustion for fuel- lean methane/air mixtures is investigated by a flame-resolved simulation. A tabulated …
M Pfitzner, M Klein - Combustion and Flame, 2021 - Elsevier
A new chemical reaction rate source term in the transport equation of a single progress variable is proposed and implications for premixed flame modelling are discussed. This …
Modeling micro-mixing remains a primary challenge for the transported probability density function (TPDF) method. In this study, the pairwise mixing with kernel constraint (KerM) …
S Sammak, Z Ren, P Givi - Modeling and Simulation of Turbulent Mixing …, 2020 - Springer
An overview is presented of recent developments in filtered density function (FDF) methodology as utilized for large eddy simulation (LES) of turbulent flows. The review is …