Data-Driven Approach for Predicting and Explaining Drag of Irregular Roughness in Turbulent Flow
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
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Karlsruhe, Karlsruher Institut für Technologie (KIT), Dissertation, 2024
- Keyword
-
Rauigkeit
Mathematisches Modell
- Event
-
Veröffentlichung
- (where)
-
Karlsruhe
- (who)
-
KIT-Bibliothek
- (when)
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2025
- Creator
-
Yang, Jiasheng
- Contributor
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Frohnapfel, Bettina
Sandham, Neil
Forooghi, Pourya
Stroh, Alexander
- DOI
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10.5445/IR/1000177686
- URN
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urn:nbn:de:101:1-2501290405591.998990120711
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:33 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Yang, Jiasheng
- Frohnapfel, Bettina
- Sandham, Neil
- Forooghi, Pourya
- Stroh, Alexander
- KIT-Bibliothek
Time of origin
- 2025
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Revisiting a Drag Partition Model For Canopy-Like Roughness Elements
Influence of Surface Anisotropy on Turbulent Flow Over Irregular Roughness
Numerical modelling of the wind over forests: roughness versus canopy drag
Assessment of Roughness Characterization Methods for Data-Driven Predictions
Data-driven prediction of the equivalent sand-grain roughness
"DRAG"
"DRAG"
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A volume‐averaging and stochastic turbulence modeling framework for homogeneous roughness‐induced drag in turbulent flows
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