Fast Prediction of Two-Dimensional Flowfields with Fuel Injection into Supersonic Crossflow via Deep Learning
Author:
Affiliation:
1. Department of Aeronautics and Astronautics, Kyushu University
Publisher
Japan Society for Aeronautical and Space Sciences
Subject
Space and Planetary Science,Aerospace Engineering
Link
https://www.jstage.jst.go.jp/article/tjsass/66/5/66_T-22-59/_pdf
Reference29 articles.
1. 1) McClinton, C. R.: X-43–Scramjet Power Breaks the Hypersonic Barrier Dryden Lectureship in Research for 2006, AIAA Paper 2006-0001, 2006.
2. 2) Smart, M. K., Hass, N. H., and Paull, A.: Flight Data Analysis of the HyShot 2 Scramjet Flight Experiment, AIAA J., 44 (2006), pp. 2366–2375.
3. 3) Erdem, E. and Kotis, K.: Numerical and Experimental Investigation of Transverse Injection Flow, Shock Waves, 20 (2010), pp. 103–118.
4. 4) Wang, Z., Jiang, C., Gau, Z., and Lee, C.: Prediction for the Separation Length of Two-Dimensional Sonic Injection with High-Speed Crossflow, AIAA J., 55 (2017), pp. 832–847.
5. 5) Huang, W., Liu, W., Li, S., Xia, Z., Liu, J., and Wang, Z.: Influence of the Turbulence Mode and the Slot Width on the Transverse Slot Injection Flow Field in Supersonic Flows, Acta Astronaut., 73 (2012), pp. 1–9.
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