[HTML][HTML] Machine learning for combustion
Combustion science is an interdisciplinary study that involves nonlinear physical and
chemical phenomena in time and length scales, including complex chemical reactions and …
chemical phenomena in time and length scales, including complex chemical reactions and …
Searching for turbulence models by artificial neural network
M Gamahara, Y Hattori - Physical Review Fluids, 2017 - APS
An artificial neural network (ANN) is tested as a tool for finding a new subgrid model of the
subgrid-scale (SGS) stress in large-eddy simulation. An ANN is used to establish a …
subgrid-scale (SGS) stress in large-eddy simulation. An ANN is used to establish a …
Application and comparison of multiple machine learning techniques for the calculation of laminar burning velocity for hydrogen-methane mixtures
In the present discussion of transition the energy supply and sector coupling processes,
hydrogen and hydrogen/natural gas mixtures will play an important role in future gas usage …
hydrogen and hydrogen/natural gas mixtures will play an important role in future gas usage …
Artificial neural network based chemical mechanisms for computationally efficient modeling of hydrogen/carbon monoxide/kerosene combustion
To effectively simulate the combustion of hydrogen/hydrocarbon-fueled supersonic engines,
such as scramjet and rocket-based combined cycle (RBCC) engines, a detailed mechanism …
such as scramjet and rocket-based combined cycle (RBCC) engines, a detailed mechanism …
A chemistry tabulation approach via rate-controlled constrained equilibrium (RCCE) and artificial neural networks (ANNs), with application to turbulent non-premixed …
AK Chatzopoulos, S Rigopoulos - Proceedings of the Combustion Institute, 2013 - Elsevier
In this work we propose a chemistry tabulation approach based on Rate-Controlled
Constrained Equilibrium (RCCE) and Artificial Neural Networks (ANNs) and apply it to two …
Constrained Equilibrium (RCCE) and Artificial Neural Networks (ANNs) and apply it to two …
Real-time spatiotemporal forecast of natural gas jet fire from offshore platform by using deep probability learning
Blow-outs occurred on offshore platform and associated fires have been recurrent during the
previous few decades, and poses a potential safety hazard to humans, property and the …
previous few decades, and poses a potential safety hazard to humans, property and the …
[HTML][HTML] Modeling of turbulent flames with the large eddy simulation–probability density function (LES–PDF) approach, stochastic fields, and artificial neural networks
T Readshaw, T Ding, S Rigopoulos, WP Jones - Physics of Fluids, 2021 - pubs.aip.org
This work proposes a chemical mechanism tabulation method using artificial neural
networks (ANNs) for turbulent combustion simulations. The method is employed here in the …
networks (ANNs) for turbulent combustion simulations. The method is employed here in the …
A deep learning framework for hydrogen-fueled turbulent combustion simulation
The high cost of high-resolution computational fluid/flame dynamics (CFD) has hindered its
application in combustion related design, research and optimization. In this study, we …
application in combustion related design, research and optimization. In this study, we …
Deep residual networks for flamelet/progress variable tabulation with application to a piloted flame with inhomogeneous inlet
M Hansinger, Y Ge, M Pfitzner - Combustion Science and …, 2022 - Taylor & Francis
In this work, a deep neural network is presented which is trained on flamelet/progress
variable (FPV) tables and validated in a combustion large eddy simulation (LES) of the …
variable (FPV) tables and validated in a combustion large eddy simulation (LES) of the …
Analysis of deep learning neural network combined with experiments to develop predictive models for a propane vertical jet fire
H Mashhadimoslem, A Ghaemi, A Palacios - Heliyon, 2020 - cell.com
Fires are important responsible factors to cause catastrophic events in the process
industries, whose consequences usually initiate domino effects. The artificial neural network …
industries, whose consequences usually initiate domino effects. The artificial neural network …