[HTML][HTML] Data driven analysis and prediction of MILD combustion mode
K Jigjid, C Tamaoki, Y Minamoto, R Nakazawa… - Combustion and …, 2021 - Elsevier
Direct numerical simulation (DNS) data of moderate or intense low-oxygen dilution (MILD)
combustion and a planar flame are analysed to identify quantities influencing the unique …
combustion and a planar flame are analysed to identify quantities influencing the unique …
[HTML][HTML] SGS Reaction rate modelling for MILD combustion based on machine-learning combustion mode classification: Development and a priori study
A neural network (NN) aided model is proposed for the filtered reaction rate in moderate or
intense low-oxygen dilution (MILD) combustion. The framework of the present model is …
intense low-oxygen dilution (MILD) combustion. The framework of the present model is …
3D DNS of MILD combustion: a detailed analysis of heat loss effects, preferential diffusion, and flame formation mechanisms
Moderate or intense low oxygen dilution (MILD) combustion is a relatively new technology
which combines low emissions with high efficiency. As the name suggests, it requires high …
which combines low emissions with high efficiency. As the name suggests, it requires high …
[HTML][HTML] A priori direct numerical simulation assessment of MILD combustion modelling in the context of large eddy simulation
HSAM Awad, K Abo-Amsha, N Chakraborty - Fuel, 2024 - Elsevier
Abstract A priori Direct Numerical Simulation (DNS) assessment of the closures for the
filtered reaction rate and the Favre-filtered scalar dissipation rate (SDR) for large eddy …
filtered reaction rate and the Favre-filtered scalar dissipation rate (SDR) for large eddy …
[HTML][HTML] Augmenting filtered flame front displacement models for LES using machine learning with a posteriori simulations
Abstract The Flame Surface Density (FSD) model is an affordable combustion model that
has been widely used in simulating turbulent premixed flames. In Large Eddy Simulations …
has been widely used in simulating turbulent premixed flames. In Large Eddy Simulations …
Species reaction rate modelling based on physics-guided machine learning
R Nakazawa, Y Minamoto, N Inoue, M Tanahashi - Combustion and Flame, 2022 - Elsevier
Deep neural network (DNN) is applied to mean reaction rate modelling. Two DNN
structures, species-dependent (SD) and species-independent (SI), are considered. 1 Due to …
structures, species-dependent (SD) and species-independent (SI), are considered. 1 Due to …
Application of machine learning for filtered density function closure in MILD combustion
ZX Chen, S Iavarone, G Ghiasi, V Kannan… - Combustion and …, 2021 - Elsevier
A machine learning algorithm, the deep neural network (DNN) 1, is trained using a
comprehensive direct numerical simulation (DNS) dataset to predict joint filtered density …
comprehensive direct numerical simulation (DNS) dataset to predict joint filtered density …
Modelling paradigms for MILD combustion
Y Minamoto, N Swaminathan - … of Advances in Engineering Sciences and …, 2014 - Springer
Abstract Three-dimensional Direct Numerical Simulation (DNS) data of methane-air MILD
combustion is analysed to study the behaviour of MILD reaction zones and to identify a …
combustion is analysed to study the behaviour of MILD reaction zones and to identify a …
Study of MILD combustion using LES and advanced analysis tools
A cylindrical confined combustor operating under MILD condition is investigated using LES.
The combustion and its interaction with turbulence are modeled using two reactor based …
The combustion and its interaction with turbulence are modeled using two reactor based …
An a priori DNS analysis of scale similarity based combustion models for LES of non-premixed jet flames
In this work, recently developed finite-rate dynamic scale similarity (SS) sub-grid scale (SGS)
combustion models have been a priori assessed and compared with the Eddy Dissipation …
combustion models have been a priori assessed and compared with the Eddy Dissipation …