Hierarchical Clustering of Modes in Numerical Turbulence Fields
We propose an automated method for decomposing turbulence, where the modes are derived by applying singular value decomposition to the electrostatic potential field in turbulence simulations. After classifying the modes into zonal flows and turbulence based on azimuthal integration, the turbulence is further decomposed into finer components through hierarchical clustering. This approach systematically breaks down the turbulence into hierarchical levels, providing flexible control over the degrees of freedom in the mode decomposition process.
Authors
- Akifumi Okuno (ORCID: https://orcid.org/0000-0001-9621-8853)
- Takumi Kodahara
- M. Sasaki (ORCID: https://orcid.org/0000-0001-6835-1569)
Institutions
- Nihon University (JP)
- Kyushu University (JP)
- RIKEN Center for Advanced Intelligence Project (JP)
- The Institute of Statistical Mathematics (JP)
- College of Industrial Technology (JP)
Publication Details
- Journal
- Plasma and Fusion Research
- Published
- 2024-12-25
- DOI
- https://doi.org/10.1585/pfr.19.1201035
- Citations
- 2
- Primary Topic
- Fluid Dynamics and Turbulent Flows
- Type
- article
- Field-Weighted Citation Impact
- 0.75
Funders
- Research Organization of Information and Systems
- Korea Institute of Science and Technology
- Kalinga Institute of Industrial Technology
- Japan Society for the Promotion of Science
- Research Institute for Applied Mechanics, Kyushu University