Data-driven Flow Regime Identification
Data-Driven Flow Regime Identification is a methodology in fluid dynamics that uses empirical data and machine learning techniques to classify flow regimes without relying on first-principles models or predefined physical assumptions.
16
Publications
737
Citations
45
Authors
23
Institutions
Publications per year
2017–2026
14
Parents
16
1–5 of 16
45
2
h-index
2
h-index
2
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1–5 of 45
23

China University of Petroleum, Beijing
Beijing, China
2 h-index
6 publications
156 citations

Universiti Teknologi Petronas
Ipoh, Malaysia
2 h-index
3 publications
48 citations
University of the Philippines Diliman
Quezon City, Philippines
2 h-index
1 publications
16 citations
University of Washington
Seattle, United States
1 h-index
1 publications
73 citations

Washington University in St. Louis
St Louis, United States
1 h-index
2 publications
136 citations
Paul Scherrer Institute
Villigen, Switzerland
1 h-index
2 publications
66 citations
Tsinghua University
Beijing, China
1 h-index
2 publications
52 citations

University of Minnesota
Minneapolis, United States
1 h-index
1 publications
73 citations
1–8 of 23
2 publications · 154 citations
2
h-index
1 publications · 16 citations
1
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1 publications · 33 citations
1
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1 publications · 58 citations
1
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1 publications · 27 citations
1
h-index
1–5