Combustion machine learning: Principles, progress and prospects
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
[HTML][HTML] Improving aircraft performance using machine learning: A review
This review covers the new developments in machine learning (ML) that are impacting the
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …
[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 …
An interpretable framework of data-driven turbulence modeling using deep neural networks
Reynolds-averaged Navier–Stokes simulations represent a cost-effective option for practical
engineering applications, but are facing ever-growing demands for more accurate …
engineering applications, but are facing ever-growing demands for more accurate …
Experimental velocity data estimation for imperfect particle images using machine learning
We propose a method using supervised machine learning to estimate velocity fields from
particle images having missing regions due to experimental limitations. As a first example, a …
particle images having missing regions due to experimental limitations. As a first example, a …
Advances and challenges of the conditional source-term estimation model for turbulent reacting flows
Abstract Conditional Source-term Estimation (CSE) is a turbulence–chemistry interaction
model to simulate reacting flows. This model is similar to the Conditional Moment Closure …
model to simulate reacting flows. This model is similar to the Conditional Moment Closure …
Structure of a heterogeneous two-phase rotating detonation wave with ethanol–hydrogen–air mixture
In this short Letter, the structure of a rotating detonation wave (RDW) fueled by biofuel is
revealed and expounded. A simulation is carried out under an Eulerian–Lagrangian …
revealed and expounded. A simulation is carried out under an Eulerian–Lagrangian …
Spray characteristics of diesel, biodiesel, polyoxymethylene dimethyl ethers blends and prediction of spray tip penetration using artificial neural network
Y Liu, J Tian, Z Song, F Li, W Zhou, Q Lin - Physics of Fluids, 2022 - pubs.aip.org
Spray characteristics of diesel, biodiesel, polyoxymethylene dimethyl ethers blends and
prediction of spray tip penetration using artificial neural network | Physics of Fluids | AIP …
prediction of spray tip penetration using artificial neural network | Physics of Fluids | AIP …
A priori assessment of convolutional neural network and algebraic models for flame surface density of high Karlovitz premixed flames
Accurate modeling of the unresolved flame surface area is critical for the closure of reaction
source terms in the flame surface density (FSD) method. Some algebraic models have been …
source terms in the flame surface density (FSD) method. Some algebraic models have been …
Field inversion for transitional flows using continuous adjoint methods
Transition modeling represents one of the key challenges in computational fluid dynamics.
While numerical efforts were traditionally devoted to either improving Reynolds-averaged …
While numerical efforts were traditionally devoted to either improving Reynolds-averaged …