Transient Buoyant Convection of A Highly Thermodependant Viscous Fluid in A 3D Cylindrical Drum
Bibliographic record
Abstract
The study of the thermal behaviour of highly thermodependant fluids is primordial in the management of radioactive bituminous waste products (BWP) contained in drums. Bitumen has indeed a large thermodependancy: more than 6 decades in viscosity ratio between the hot and cold parts. To do so, a transient 3D convective system with the configuration of a constant temperature stress on the vertical boundary is considered. To estimate the key features of the physics involved, an analytical study is undertaken to draw a first general understanding of the system behaviour. Numerical simulations on a 3D Finite Element solver with the Boussinesq approximation are then carried out for various parameters to confirm the analytical results. Four phases are enhanced: a diffusive thermal choc, a vertical boundary layer convection, a global convection lead by the collapse of the cold inner core, and finally the heating of the remaining cold area by diffusion. Additional simulations with non-newtonian rheological laws (such as Hershel-Bulkley model) were also tested. The addition of a yield stress reduces the convection and thus the intensity of the second and third phases.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".