[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 …
Feature selection and feature learning in machine learning applications for gas turbines: A review
The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of gas turbine (GT) modelling. However, successful implementation of ML …
to the field of gas turbine (GT) modelling. However, successful implementation of ML …
Machine-learning-based condition assessment of gas turbines—A review
Condition monitoring, diagnostics, and prognostics are key factors in today's competitive
industrial sector. Equipment digitalisation has increased the amount of available data …
industrial sector. Equipment digitalisation has increased the amount of available data …
A generative adversarial network (GAN) approach to creating synthetic flame images from experimental data
Modern diagnostic tools in turbulent combustion allow for highly-resolved measurements of
reacting flows; however, they tend to generate massive data-sets, rendering conventional …
reacting flows; however, they tend to generate massive data-sets, rendering conventional …
Machine learning opportunities to conduct high-fidelity earthquake simulations in multi-scale heterogeneous geology
The 2019 Le Teil earthquake is an illustrative example of a moderate (MW 4.9) yet
damaging event, occurring at shallow depth (≈ 1 km) in a region with little to no geophysical …
damaging event, occurring at shallow depth (≈ 1 km) in a region with little to no geophysical …
Unsupervised quantitative judgment of furnace combustion state with CBAM-SCAE-based flame feature extraction
Y Lv, X Qi, X Zheng, F Fang, J Liu - Journal of the Energy Institute, 2024 - Elsevier
The furnace combustion state of coal-fired power plants is difficult to accurately monitor
during low-load and dynamic operation conditions, thus hindering the secure and economic …
during low-load and dynamic operation conditions, thus hindering the secure and economic …
Multi-fidelity prediction of spatiotemporal fluid flow
Data-driven prediction of spatiotemporal fields in fluid flow problems has received significant
interest lately. However, the scarcity of data often plagues the accuracy of the prevalent …
interest lately. However, the scarcity of data often plagues the accuracy of the prevalent …
Pre-trained combustion model and transfer learning in thermoacoustic instability
Z Qin, X Wang, X Han, Y Lin, Y Zhou - Physics of Fluids, 2023 - pubs.aip.org
In this paper, deep learning is involved to comprehend thermoacoustic instability more
deeply and achieve early warning more reliably. Flame images and pressure series are …
deeply and achieve early warning more reliably. Flame images and pressure series are …
Analysis of gas turbine compressor performance after a major maintenance operation using an autoencoder architecture
Machine learning algorithms and the increasing availability of data have radically changed
the way how decisions are made in today's Industry. A wide range of algorithms are being …
the way how decisions are made in today's Industry. A wide range of algorithms are being …
Investigations on multi-scale chaotic characteristics and hybrid prediction model for combustion system in a premixed lean-burn natural gas engine
H Ding, SF He, SL Ding, Y Ke, C Yao, EZ Song - Fuel, 2025 - Elsevier
This work investigates the multi-scale chaotic characteristics and prediction model of
combustion system in an electronically controlled natural gas engine with varying excess air …
combustion system in an electronically controlled natural gas engine with varying excess air …