[HTML][HTML] Computational approaches to explainable artificial intelligence: advances in theory, applications and trends

JM Górriz, I Álvarez-Illán, A Álvarez-Marquina, JE Arco… - Information …, 2023 - Elsevier
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 …

[HTML][HTML] Machine learning for combustion

L Zhou, Y Song, W Ji, H Wei - Energy and AI, 2022 - Elsevier
Combustion science is an interdisciplinary study that involves nonlinear physical and
chemical phenomena in time and length scales, including complex chemical reactions and …

MILD combustion of low calorific value gases

S Zhou, B Yan, M Mansour, Z Li, Z Cheng, J Tao… - Progress in Energy and …, 2024 - Elsevier
The utilization of low calorific value gases (LCVG) in combustion devices presents particular
challenges in terms of ignition and sustained combustion stability due to the presence of non …

Challenges for turbulent combustion

AR Masri - Proceedings of the Combustion Institute, 2021 - Elsevier
Turbulent combustion will remain central to the next generation of combustion devices that
are likely to employ blends of renewable and fossil fuels, transitioning eventually to …

Identification of flame regimes in partially premixed combustion from a quasi-DNS dataset

T Zirwes, F Zhang, P Habisreuther, M Hansinger… - Flow, Turbulence and …, 2021 - Springer
Identifying combustion regimes in terms of premixed and non-premixed characteristics is an
important task for understanding combustion phenomena and the structure of flames. A …

Effect of fuel temperature on flame characteristics of supersonic turbulent combustion

JY Choi, U Unnikrishnan, WS Hwang, SM Jeong… - Fuel, 2022 - Elsevier
A comprehensive numerical study is undertaken to investigate the dynamics of hydrogen-air
supersonic turbulent flames in a shear coaxial configuration. The effects of fuel temperature …

Combustion regime identification from machine learning trained by Raman/Rayleigh line measurements

K Wan, S Hartl, L Vervisch, P Domingo, RS Barlow… - Combustion and …, 2020 - Elsevier
A combustion regime identification based on convolutional neural networks (CNNs) is
developed using the recently proposed gradient-free regime identification (GFRI) approach …

Assessing multi-regime combustion in a novel burner configuration with large eddy simulations using tabulated chemistry

S Popp, S Hartl, D Butz, D Geyer, A Dreizler… - Proceedings of the …, 2021 - Elsevier
Recent investigations on a novel multi-regime burner (MRB) configuration showed
significant deviations in the CO flame structure compared to the limiting cases of premixed …

[HTML][HTML] Application of a two-progress variable model for carbon monoxide emissions from turbulent premixed and partially premixed enclosed flames

JC Massey, Y Tanaka, N Swaminathan - Combustion and Flame, 2023 - Elsevier
A large eddy simulation study is undertaken with the objective of improving carbon
monoxide (CO) estimations compared to measurements of enclosed turbulent flames in …

Scalar gradient and flame propagation statistics of a flame-resolved laboratory-scale turbulent stratified burner simulation

E Inanc, AM Kempf, N Chakraborty - Combustion and Flame, 2022 - Elsevier
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 …