[HTML][HTML] A Data-Based Hybrid Chemistry Acceleration Framework for the Low-Temperature Oxidation of Complex Fuels

S Alqahtani, KM Gitushi, T Echekki - Energies, 2024 - mdpi.com
The oxidation of complex hydrocarbons is a computationally expensive process involving
detailed mechanisms with hundreds of chemical species and thousands of reactions. For …

Large eddy simulation of bluff-body turbulent hydrogen/nitrogen flames using principal component transport models with differential diffusion effects

S Abdelwahid, MR Malik, H Tang, A Alfazazi… - International Journal of …, 2024 - Elsevier
This study investigates the combustion characteristics of nonpremixed bluff-body stabilized
H 2/N 2-air flames, with a specific focus on a fully cracked ammonia case. The motivation …

An a priori analysis on principal component analysis based conditional source-term estimation model for Sandia jet flames

N Sekularac, WK Bushe, XH Fang - Combustion and Flame, 2024 - Elsevier
Data from all spatial locations and two turbulent flames in the Sandia/TUD database are
used to explore the feasibility of adopting principal components (PC) as conditional …

Reduced-order modeling with reconstruction-informed projections

E Armstrong, JC Sutherland - Combustion and Flame, 2024 - Elsevier
Reduced-order models (ROMs) are commonly employed to address the large computational
cost of simulations for high-dimensional, dynamical systems such as those found in …

[PDF][PDF] Reduced-order modeling of turbulent reacting flows using data-driven approaches

K Zdybał - 2023 - researchgate.net
Numerical simulation of turbulent flames is a computationally challenging task. This remains
true even with the current advances in numerical algorithms and highperformance …

Machine learning applied to the computation of chemical source terms in reacting flows

X Chen - 2024 - pastel.hal.science
This thesis deals with the acceleration of chemical kinetics calculations in CFD simulations
by relying of machine learning methods. The principle is to replace the resolution of the …

[HTML][HTML] Improving reduced-order models through nonlinear decoding of projection-dependent outputs

K Zdybał, A Parente, JC Sutherland - Patterns, 2023 - cell.com
A fundamental hindrance to building data-driven reduced-order models (ROMs) is the poor
topological quality of a low-dimensional data projection. This includes behavior such as …