Efficient two-dimensional scalar fields reconstruction of laminar flames from infrared hyperspectral measurements with a machine learning approach
The latest hyperspectral measurements of combustion flames by Rhoby et al.(2014)
provided extensive spatially and spectrally resolved information of flame radiation, which …
provided extensive spatially and spectrally resolved information of flame radiation, which …
Inverse methods in thermal radiation analysis and experiment
Most thermal radiation problems are analyzed in a “forward” manner, in which the aim is to
predict the response of a system based on well-defined boundary conditions. In practice …
predict the response of a system based on well-defined boundary conditions. In practice …
A machine learning based efficient and compact full-spectrum correlated k-distribution model
Y Zhou, C Wang, T Ren - Journal of Quantitative Spectroscopy and …, 2020 - Elsevier
The full-spectrum correlated-k-distribution (FSCK) look-up table previously developed by
Wang et al.(2018) provides an efficient means for accurate calculations of radiative …
Wang et al.(2018) provides an efficient means for accurate calculations of radiative …
Physics-trained neural network for sparse-view volumetric laser absorption imaging of species and temperature in reacting flows
A deep learning method for laser absorption tomography was developed to effectively
integrate physical priors related to flow-field thermochemistry and transport. Mid-fidelity …
integrate physical priors related to flow-field thermochemistry and transport. Mid-fidelity …
A machine learning based full-spectrum correlated k-distribution model for nonhomogeneous gas-soot mixtures
The machine learning based full-spectrum correlated k-distribution (FSCK) model previously
developed by Zhou et al.(2020), provides a compact prediction model with good efficiency …
developed by Zhou et al.(2020), provides a compact prediction model with good efficiency …
Machine learning-assisted soot temperature and volume fraction fields predictions in the ethylene laminar diffusion flames
Inferring local soot temperature and volume fraction distributions from radiation emission
measurements of sooting flames may involve solving nonlinear, ill-posed and high …
measurements of sooting flames may involve solving nonlinear, ill-posed and high …
[HTML][HTML] Machine learning prediction of electron density and temperature from He I line ratios
We propose to utilize machine learning to predict the electron density, ne, and temperature,
T e, from He I line intensity ratios. In this approach, training data consist of measured He I …
T e, from He I line intensity ratios. In this approach, training data consist of measured He I …
Efficient and robust CNN-LSTM prediction of flame temperature aided light field online tomography
ZT Niu, H Qi, AT Sun, YT Ren, MJ He… - Science China …, 2024 - Springer
Light field tomography, an optical combustion diagnostic technology, has recently attracted
extensive attention due to its easy implementation and non-intrusion. However, the …
extensive attention due to its easy implementation and non-intrusion. However, the …
Atmospheric CO2 retrieval from satellite spectral measurements by a two-step machine learning approach
In the present study, a two-step machine learning approach is proposed and tested based
on the Greenhouse gases Observing SATllite (GOSAT) spectral measurements to efficiently …
on the Greenhouse gases Observing SATllite (GOSAT) spectral measurements to efficiently …