Statistical and modal analysis of surface pressure fluctuations in tornado-like vortices
Bibliographic record
Abstract
Surface pressure measurement is a general tool for evaluating wind flow qualitatively and quantitatively. Due to its complex temporal and spatial features, modal analysis is an interesting tool to be used for interpretation and discussion. The most common technique for modal representation is proper orthogonal decomposition (POD), also referred to as principal component analysis. However, it is believed that POD sometimes fails to extract meaningful features of the pressure field. To remove the non-physical POD modes and provide a closer physical description of the pressure field, an advanced method independent component analysis (ICA) is applied. Furthermore, these two methods are generalized in the frequency domain, called dynamic POD and dynamic ICA, to provide the temporal evolutions of coherent structures over the spatial domain. Modal analysis is used to isolate the different coherent structures in tornado-like vortices, e.g., wandering, vortex breakdown, and two-cell structure, and find the spectral characteristic of each phenomenon. Moreover, a comparison of modal analysis between the current paper and the previous paper on the velocity field {see Karami et al., [“Coherent structures in tornado-like vortices,” Phys. Fluids 31, 085118 (2019)]} presents new insight into the pressure–velocity correlation of the POD modes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".