Deep learning estimation of scalar source distance for different turbulent and molecular diffusion environments
Author:
Affiliation:
1. Department of Mechanical and Aerospace Engineering, Tokyo University of Science
2. Chiyoda Corporation
Publisher
Japan Society of Mechanical Engineers
Link
https://www.jstage.jst.go.jp/article/jfst/19/2/19_2024jfst0020/_pdf
Reference42 articles.
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3. Batchelor, G.K., Small-scale variation of convected quantities like temperature in turbulent fluid Part 1. General discussion and the case of small conductivity, Journal of Fluid Mechanics, Vol. 5, No. 1 (1959a), pp. 113–133.
4. Batchelor, G.K., Small-scale variation of convected quantities like temperature in turbulent fluid Part 2. The case of large conductivity, Journal of Fluid Mechanics, Vol. 5, No. 1 (1959b), pp. 134–139.
5. Boschen, R.E., Rowden, A.A., Clark, M.R. and Gardner, J.P., Mining of deep-sea seafloor massive sulfides: A review of the deposits, their benthic communities, impacts from mining, regulatory frameworks and management strategies, Ocean & Coastal Management, Vol. 84 (2013), pp. 54–67.
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