Acta Optica Sinica, Volume. 45, Issue 16, 1612003(2025)
Scalar Field Velocimetry Based on Deep Optical Flow Neural Network
Fig. 6. Distributions of centreline mass fractions in vertical sections of 45° jets. (a) 20D; (b) 30D
Fig. 7. Scalar and velocity fields of 45° jet. (a)(b) Instantaneous scalar field images of two adjacent frames; (c) reference velocity field; velocity fields predicted from scalar fields using (d) SIV-RAFT, (e) PWC-Net, and (f) HS algorithms, respectively
Fig. 8. Error analysis results of jet velocity fields. (a) SIV-RAFT; (b) PWC; (c) HS
Fig. 11. Distributions of velocity in vertical sections at different centreline distances of 45° jets. (a) 20D; (b) 30D
Fig. 12. Velocity amplitude maps of DNS turbulent flow (t=30). (a) Velocity amplitude map of real DNS; (b) SIV-RAFT; (c) PWC; (d) HS
Fig. 13. Vorticity maps of DNS turbulent flow (t=30). (a) Instantaneous vorticity map of real DNS; (b) SIV-RAFT; (c) PWC; (d) HS
Fig. 14. Velocity spectra of DNS turbulent flow (t=30). (a) Horizontal direction; (b) vertical direction
Fig. 15. Velocity spectrum error of DNS turbulent flow (t=30). (a) Horizontal direction; (b) vertical direction
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Mingtao Jiang, Wenjie Xu, Wei Chen. Scalar Field Velocimetry Based on Deep Optical Flow Neural Network[J]. Acta Optica Sinica, 2025, 45(16): 1612003
Category: Instrumentation, Measurement and Metrology
Received: Apr. 24, 2025
Accepted: May. 26, 2025
Published Online: Aug. 18, 2025
The Author Email: Wei Chen (wchen@zjou.edu.cn)
CSTR:32393.14.AOS251001