[HTML][HTML] Predicting the effect of hydrogen enrichment on the flame describing function using machine learning
Y Shen, AS Morgans - International Journal of Hydrogen Energy, 2024 - Elsevier
As a promising strategy to mitigate carbon emissions, hydrogen enrichment of conventional
fuels is gaining increasing interest, but can lead to increased propensity to damaging …
fuels is gaining increasing interest, but can lead to increased propensity to damaging …
Linear and nonlinear flame response prediction of turbulent flames using neural network models
N Tathawadekar, A Ösün, AJ Eder… - … Journal of Spray …, 2024 - journals.sagepub.com
Modelling the flame response of turbulent flames via data-driven approaches is challenging
due, among others, to the presence of combustion noise. Neural network methods have …
due, among others, to the presence of combustion noise. Neural network methods have …
[HTML][HTML] A parsimonious system of ordinary differential equations for the response modeling of turbulent swirled flames
In this work, we present a parsimonious set of ordinary differential equations (ODEs),
describing with good precision and over a wide range of frequencies the linear and …
describing with good precision and over a wide range of frequencies the linear and …
[HTML][HTML] RF-PINNs: Reactive Flow Physics-Informed Neural Networks for Field Reconstruction of Laminar and Turbulent Flames using Sparse Data
V Yadav, M Casel, A Ghani - Journal of Computational Physics, 2024 - Elsevier
Abstract Physics-Informed Neural Networks (PINNs) have emerged as a promising tool to
model flow fields by embedding physical laws into neural networks and thereby reducing the …
model flow fields by embedding physical laws into neural networks and thereby reducing the …
Segmentation of high-speed flow fields using physics-informed clustering
The advent of data-based modeling has provided new methods and algorithms for analyzing
the complex flow fields in high-speed combustion applications. These techniques can be …
the complex flow fields in high-speed combustion applications. These techniques can be …
Application of Fuzzy Neural Networks in Combustion Process Diagnostics
Ż Grądz, W Wójcik, K Gromaszek, A Kotyra, S Smailova… - Energies, 2023 - mdpi.com
Coal remains one of the key raw materials used in the energy industry to generate electricity
and heat. As a result, diagnostics of the combustion process is still an important topic of …
and heat. As a result, diagnostics of the combustion process is still an important topic of …
[HTML][HTML] Neural Network-Based Analysis of Flame States in Pulverised Coal and Biomass Co-Combustion
Ż Grądz, W Wójcik, B Imanbek, B Yeraliyeva - Energies, 2025 - mdpi.com
In the European Union, coal consumption in the power industry has been declining over
time. Energy sources such as renewable energy, nuclear energy, and natural gas are being …
time. Energy sources such as renewable energy, nuclear energy, and natural gas are being …
Evaluation of Data-Driven Classifiers for an Ignition Forecast of Large Gas Turbines
F Lang, M Savtschenko… - … of Engineering for …, 2025 - asmedigitalcollection.asme.org
Prediction of successful ignition is a challenging task that requires knowledge of the local
thermochemical state in highly turbulent flow conditions. For typical industrial gas turbine …
thermochemical state in highly turbulent flow conditions. For typical industrial gas turbine …
A Dual-Path neural network model to construct the flame nonlinear thermoacoustic response in the time domain
Traditional numerical simulation methods require substantial computational resources to
accurately determine the complete nonlinear thermoacoustic response of flames to various …
accurately determine the complete nonlinear thermoacoustic response of flames to various …
Incomplete to complete multiphysics forecasting: a hybrid approach for learning unknown phenomena
Modeling complex dynamical systems with only partial knowledge of their physical
mechanisms is a crucial problem across all scientific and engineering disciplines. Purely …
mechanisms is a crucial problem across all scientific and engineering disciplines. Purely …