Yicheng Zhang, Yongkang Han, Ya Zhou, Tao Ren, Xunchen Liu. Machine-Learning-Based Reconstruction of Flame Temperature and CO2 Concentration Fields[J]. Acta Optica Sinica, 2020, 40(23): 2312003
- Acta Optica Sinica
- Vol. 40, Issue 23, 2312003 (2020)
Fig. 1. Schematic of temperature and CO2 concentration fields measurements for axisymmetric flames
Fig. 2. Schematics of traditional measurement method. (a) Reconstruction of temperature and CO2 concentration fields based on axial and radial laser spectral absorption measurements; (b) reconstruction of temperature and CO2 concentration fields based on axial laser spectral absorption measurement
Fig. 3. Machine-learning-based reconstruction model for temperature and concentration fields retrieval
Fig. 4. Numerical simulation of CH4-air laminar coaxial diffusion flame. (a) Computation grid and boundary conditions for simulating flame; (b) temperature field; (c) CO2 concentration field
Fig. 5. True flame temperature and CO2 concentration fields, as well as machine-learning-based model predicted fields with 2%, 5% and 10% Gaussian random noises. (a) Temperature fields; (b) CO2 concentration fields
Fig. 6. Comparisons of true temperature and CO2 concentration fields (ideal) with machine-learning-based model predicted ones (MLP) with different random noises. (a) 2% random noise; (b) 5% random noise; (c) 10% random noise
Fig. 7. Comparisons of true temperature and CO2 concentration distributions (ideal) at the height above burner of 40 mm with machine-learning-based model predicted ones (MLP). (a) 2% random noise; (b) 5% random noise; (c) 10% random noise
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